Time interval determination method, device, electronic device and program product

Abstract

The disclosed embodiments disclose a time interval determination method, device, electronic device, and program product, the method comprising: obtaining traffic light data on a target road; the traffic light data comprising road speed, queue dissipation characteristics in front of the light, traffic light spatial topology characteristics, and traffic light signal time characteristics; based on the traffic light data, determining a green light time interval corresponding to a target position within a preset distance range in front of a traffic light on the target road; wherein the green light time interval indicates that when the target time for a driving object to reach the target position is within the green light time interval, the driving object can pass through the traffic light under a green light state. This technical solution can guide driving objects to safely pass through the traffic light ahead, reduce the probability of driving objects waiting for a red light, and improve the overall traffic efficiency of the intersection.

Description

Technical Field

[0001] The present disclosure relates to the field of geographic information technology, and in particular to a time interval determination method, device, electronic device, and program product. Background Art

[0002] Traffic lights are a core part of road infrastructure and the user experience. Due to their checkpoint-like nature and the fact that some traffic lights do not count down, many users experience anxiety while waiting for traffic lights. "Running the green light" and "jumping the red light" lead to frequent accidents at intersections. Furthermore, reduced intersection capacity can lead to severe traffic congestion. If users could predict whether they could pass through the light directly before and after approaching it, as well as the speed at which they could do so without waiting, they could proactively prepare for changes in traffic light status, alleviate anxiety, and improve intersection efficiency.

[0003] To this end, researchers have proposed the concept of a "green wave belt" to improve intersection efficiency by coordinating traffic light signal control. A "green wave belt" refers to a road where traffic is coordinated to ensure that vehicles receive continuous green lights at controlled intersections, allowing them to pass through all the controlled intersections without stopping. However, one of the current technical challenges is how to identify the time intervals during which vehicles can pass through the preceding traffic light without stopping. Summary of the Invention

[0004] Embodiments of the present disclosure provide a method, device, electronic device, and program product for determining a time interval.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for determining a time interval, which includes:

[0006] Obtaining traffic light data on a target road; the traffic light data includes road traffic speed, queue dissipation characteristics in front of the light, traffic light spatial topology characteristics, and traffic light signal time characteristics;

[0007] Based on the traffic light data, a green light time interval corresponding to a target position within a preset distance range in front of a traffic light on the target road is determined; wherein, the green light time interval indicates that when the target time for the driving object to reach the target position is within the green light time interval, the driving object can pass the traffic light under the green light state.

[0008] Furthermore, the traffic light spatial topology feature includes a spatial positional relationship between a plurality of traffic lights arranged consecutively on the target road; and based on the traffic light data, determining a green light time interval corresponding to a target position within a preset distance range from the traffic light on the target road includes:

[0009] Based on the traffic light data, a green light time interval corresponding to a target position before a first one of the plurality of traffic lights and passing through one and / or a plurality of consecutive traffic lights is determined.

[0010] Furthermore, the queue dissipation feature includes a corresponding relationship between the queue length at the traffic light and the time it takes for the tail of the queue to pass the traffic light under the green light state; the traffic light signal time feature includes the green light duration interval of the traffic light; and based on the traffic light data, determining the green light duration interval corresponding to a target position within a preset distance range from the traffic light on the target road includes:

[0011] determining an offset time for the moving object to travel from the target location to the traffic light at the road speed;

[0012] Determining the queue waiting time of the traveling object before passing the traffic light based on the correspondence between the queue length and time;

[0013] A green light passing time interval for a traveling object arriving at the target position to pass through the traffic light in a green light state is determined based on the green light duration interval, the offset time, and the queue waiting time.

[0014] Furthermore, the green light duration interval includes time intervals corresponding to multiple consecutive green light states of the same traffic light; and determining the green light passing time interval for a traveling object arriving at the target location to pass through the traffic light in the green light state based on the green light duration interval, the offset time, and the queue waiting time includes:

[0015] Determine the passing start time of each of the green light passing time intervals based on the green light start time, offset time and queue waiting time of each of the green light duration intervals corresponding to a plurality of consecutive green light states;

[0016] The passing end time of each of the green light passing time intervals is determined based on the green light end time and the offset time of each of the green light duration intervals corresponding to a plurality of consecutive green light states.

[0017] Furthermore, the method further comprises:

[0018] The number of traffic lights that the traveling object can continuously pass through in a green light state from a target position is determined based on the green light time intervals corresponding to a plurality of consecutive traffic lights.

[0019] Furthermore, the method further comprises:

[0020] Obtaining the current position of the moving object;

[0021] When the current position is within the preset distance range, determining the green light time interval corresponding to the target position matching the current position;

[0022] Based on the green light passing time interval, recommendation information that the driving object can pass the traffic light in the green light state is outputted to the driving object.

[0023] Furthermore, the method further comprises:

[0024] The preset distance range, the green light time interval corresponding to at least one target position within the preset distance range, and the road traffic speed are pushed to the client of the driving object, so that the client can output recommendation information to the driving object that it can pass the traffic light in the green light state based on the current position of the driving object.

[0025] Furthermore, the method further comprises:

[0026] Obtaining the current position of the moving object;

[0027] determining a current distance from the traveling object to a preceding traffic light based on the current position;

[0028] A recommended driving speed for the driving object to pass through a single traffic light ahead in a green light state is determined based on the current distance, the current time, the characteristics of the queue dissipation in front of the traffic light, and the green light duration interval.

[0029] Furthermore, based on the current distance, the current time, the queue dissipation characteristics before the traffic light, and the green light duration interval, determining a recommended driving speed for the driving object to pass through a single traffic light ahead under a green light state includes:

[0030] When the current moment is within the green light duration interval of the traffic light, determining a lower limit of the recommended driving speed based on a first traffic light-passing speed, and setting an upper limit of the recommended driving speed to a first preset fixed value;

[0031] When the current moment is in the non-green light duration interval of the traffic light, the upper limit value of the recommended driving speed is determined based on the second green light speed, and the lower limit value of the recommended driving speed is set to a second preset fixed value; the first green light speed is lower than the second green light speed, and both are determined based on the current distance, the current moment, the queue dissipation characteristics in front of the light and the green light duration interval.

[0032] In a second aspect, an embodiment of the present invention provides a navigation method, which includes:

[0033] Get the planned path from the navigation starting point to the navigation destination;

[0034] Determine the green light time interval corresponding to the target road on the planned path using the method described in the first aspect;

[0035] Based on the current position of the navigated object and the green light passing time interval, relevant information about passing the traffic light ahead is outputted to the navigated object.

[0036] In a third aspect, an embodiment of the present invention provides a time interval determination device, comprising:

[0037] A first acquisition module is configured to acquire traffic light data on a target road; the traffic light data includes road traffic speed, queue dissipation characteristics before the light, traffic light spatial topology characteristics, and traffic light signal time characteristics;

[0038] The first determination module is configured to determine the green light time interval corresponding to the target position within a preset distance range in front of the traffic light on the target road based on the traffic light data; wherein, the green light time interval indicates that when the target time for the driving object to reach the target position is within the green light time interval, the driving object can pass the traffic light under the green light state.

[0039] In a fourth aspect, an embodiment of the present invention provides a navigation device, comprising:

[0040] A third acquisition module is configured to acquire a planned path from the navigation start point to the navigation destination;

[0041] A sixth determining module is configured to determine a green light time interval corresponding to a target road on the planned path using the apparatus according to the third aspect;

[0042] The second output module is configured to output relevant information of passing the traffic light ahead to the navigated object based on the current position of the navigated object and the green light passing time interval.

[0043] The functions can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the functions.

[0044] In one possible design, the apparatus includes a memory and a processor. The memory is configured to store one or more computer instructions that enable the apparatus to perform the corresponding method, and the processor is configured to execute the computer instructions stored in the memory. The apparatus may also include a communication interface for communicating with other devices or a communication network.

[0045] In a fifth aspect, an embodiment of the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method described in any one of the above aspects.

[0046] In a sixth aspect, an embodiment of the present disclosure provides a computer-readable storage medium for storing computer instructions used by any of the above-mentioned devices, and when the computer instructions are executed by a processor, they are used to implement the method described in any of the above-mentioned aspects.

[0047] In a seventh aspect, an embodiment of the present disclosure provides a computer program product, which includes computer instructions, and when the computer instructions are executed by a processor, they are used to implement the method described in any of the above aspects.

[0048] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0049] In an embodiment of the present disclosure, traffic light data on a target road is obtained, and the traffic light data includes the road speed on the target road, the queue dissipation characteristics in front of the light, the spatial topology characteristics of the traffic light, and the time characteristics of the traffic light signal; based on the traffic data mining, after the driving object reaches the target position in front of any traffic light on the target road, the green light time interval in which the driving object can directly pass the traffic light ahead under the green light state from the target position is determined. After the green light time interval is mined, it can be used in applications such as online navigation to recommend a driving speed for the driving object, thereby guiding the driving object to smoothly pass the traffic light ahead while driving at the recommended driving speed. The embodiment of the present disclosure guides the driving object to safely pass the traffic light ahead by mining the green light time interval in which the driving object can pass the traffic light on the target road in real time, and recommending the driving speed for the driving object to pass the traffic light in advance, thereby reducing the probability of the driving object waiting for the red light and improving the overall traffic efficiency of the intersection.

[0050] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Other features, objectives and advantages of the present disclosure will become more apparent through the following detailed description of non-limiting embodiments in conjunction with the accompanying drawings. In the accompanying drawings:

[0052] Figure 1 A flowchart of a method for determining a time interval according to an embodiment of the present disclosure is shown.

[0053] Figures 2A-2B A schematic diagram showing the correspondence between green light passing time intervals and green light duration intervals on a target road according to an embodiment of the present disclosure is shown.

[0054] Figure 3 A schematic diagram of a single-lamp over-lighting effect according to an embodiment of the present disclosure is shown.

[0055] Figure 4 A flowchart of a navigation method according to an embodiment of the present disclosure is shown.

[0056] Figure 5 A structural block diagram of a time interval determination device according to an embodiment of the present disclosure is shown.

[0057] Figure 6 A structural block diagram of a navigation device according to an embodiment of the present disclosure is shown.

[0058] Figure 7 It is a structural diagram of an electronic device suitable for implementing the time interval determination method and / or navigation method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0059] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, parts not related to the description of the exemplary embodiments are omitted in the accompanying drawings.

[0060] In the present disclosure, it should be understood that terms such as "including" or "having" are intended to indicate the presence of features, numbers, steps, behaviors, components, parts, or combinations thereof disclosed in the present specification, and do not exclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof exist or are added.

[0061] It should also be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0062] In the existing technology, relevant personnel have proposed to realize the green wave band by controlling the red and green light status of traffic lights. This method is more static data. There are also vehicle-road cooperative systems that provide users with traffic light status information, green light start reminders, recommended speed for passing lights, red light running warnings and road information broadcasts, and these functions are displayed by accessing the above-mentioned static data. This method has a small coverage range and is difficult to promote.

[0063] To this end, embodiments of the present disclosure propose a time interval determination method. In this method, traffic light data on a target road is obtained, including the road speed, queue dissipation characteristics, spatial topological characteristics of the traffic lights, and time characteristics of the traffic light signals. Based on the traffic data, a driver is mining the traffic data to determine a green light time interval during which the driver can directly pass the preceding traffic light from the target location under the green light condition. Once the green light time interval is mined, it can be used in applications such as online navigation to recommend a driving speed for the driver, thereby guiding the driver to successfully pass the preceding traffic light at the recommended speed. By mining the green light time interval (i.e., the width of the "green wave") for the driver to pass the preceding traffic light in real time on the target road and pre-recommending a driving speed (i.e., the speed of the "green wave") for the driver to pass the preceding traffic light, the disclosed embodiment guides the driver to safely pass the preceding traffic light, reduces the probability of the driver waiting for a red light, and improves overall traffic efficiency at the intersection.

[0064] Compared with the existing technology, the embodiment of the present disclosure conducts empirical analysis based on the actual data of traffic lights, and at the same time takes into account real-time road characteristics (such as road conditions, queue dissipation characteristics, and road travel speed, etc.) in combination with the big data of driving objects; the embodiment of the present disclosure can guide the real-time vehicle speed of driving objects based on the real-time dynamic data of driving objects, increase the probability of driving objects being passable on the target road, and improve the data coverage.

[0065] The details of the embodiments of the present disclosure are described in detail below through specific examples.

[0066] Figure 1 FIG. 1 is a flow chart showing a method for determining a time interval according to an embodiment of the present disclosure. Figure 1 As shown, the time interval determination method includes the following steps:

[0067] In step S101, traffic light data on a target road is obtained; the traffic light data includes road traffic speed, queue dissipation characteristics before the light, traffic light spatial topology characteristics, and traffic light signal time characteristics;

[0068] In step S102, based on the traffic light data, the green light time interval corresponding to the target position within a preset distance range in front of the traffic light on the target road is determined; wherein, the green light time interval indicates that when the target time for the driving object to reach the target position is within the green light time interval, the driving object can pass the traffic light under the green light state.

[0069] In this embodiment, the time interval determination method can be executed on the server and / or client. The target road can be a road where a "green wave belt" is to be mined. In some embodiments, the target road can be a straight road, and one or more traffic lights can be set on the target road.

[0070] Traffic light data on the target road may include road traffic speed, queue dissipation characteristics in front of the light, traffic light spatial topological characteristics, and traffic light signal time characteristics.

[0071] In some embodiments, the road speed may be the speed of a driving object on a target road. The road speeds at different traffic lights on different roads may be different. In some embodiments, the driving object may be a vehicle, an intelligent driving object, or the like. In some embodiments, the road speed may be obtained by aggregating the historical speeds of historical vehicles on the target road. The road speed may reflect the traffic capacity of the target road. In addition, after obtaining the speed by aggregating the historical speeds of historical vehicles traveling on the target road, the speed limit characteristics of the target road may be used to perform speed correction to ensure that the corrected road speed is no higher than the speed limit of the target road. In addition, the corrected road speed may be multiplied by 5 so that the road speed is an integer multiple of 5. The road speed is multiplied by 5 so that when the road speed is recommended to the user, the user can more intuitively understand the magnitude of the speed value.

[0072] In some embodiments, the queue dissipation feature can be the corresponding relationship between the queue length of vehicles waiting to pass the green light at a traffic light on a target road and the time it takes to pass the green light. For example, if the time it takes for vehicles queuing 100 meters (queue length) at a traffic light to pass the green light is 10 seconds, then the queue length is 100 meters and the corresponding queue waiting time is 10 seconds. In some embodiments, the queue waiting time corresponding to any queue length within a certain distance from the traffic light can be pre-calculated to form the above-mentioned queue dissipation feature.

[0073] In some embodiments, the aforementioned queue dissipation feature can be constructed by capturing the trajectory data of floating vehicles within the influence range of traffic lights, inferring the parking position of floating vehicles at the intersection and the time it takes to pass through the intersection. During the construction process, abnormal samples can be first filtered out, and then the parking position and time it takes for a single vehicle to pass through the intersection can be calculated. Then, all vehicles within a certain period of time are counted, and the features of the vehicles at the intersection are aggregated. Finally, the minute-dimensional queue dissipation feature is calculated, which is the corresponding relationship between the length of the queue at the corresponding traffic light and the time it takes the vehicle at the end of the queue to pass through the traffic light for each minute of the day. In other words, the queue dissipation feature includes the corresponding relationship between the queue length at the traffic light and the queue dissipation time. In some embodiments, to improve the real-time performance of the data, the functional relationship between the queue length at the traffic light and the queue dissipation time is also captured, so that the client can calculate the queue dissipation time of the traveling object based on this functional relationship during the real-time guidance of the traveling object. In some embodiments, the queue dissipation feature corresponding to different traffic lights can be different.

[0074] In some embodiments, the spatial topological relationship of traffic lights may include but is not limited to the spatial position of traffic lights on the target road, and in the case of multiple traffic lights, the relative positional relationship between the multiple traffic lights.

[0075] In some embodiments, traffic light signal temporal features may include, but are not limited to, a sequence of duration intervals for the red, yellow, and green signal states of a traffic light, each of which includes the start and end times of the corresponding signal state. For example, the sequence of duration intervals for the green light state of traffic light A on a target road can be represented as: [t0, t1][t2, t3]…[tn-1, tn]; where [t0, t1] is assumed to be the green light duration interval for the first green light state, [t2, t3] is the green light duration interval for the second green light state, and so on.

[0076] The traffic light signal time characteristics can be calculated based on the actual changing conditions of the traffic lights on the target road. For details, please refer to the existing technology and no specific limitations are given here. Of course, the traffic light signal time characteristics can also be provided by relevant departments.

[0077] After obtaining the aforementioned traffic light data, the green light passing time interval within which a driving object can pass the traffic light under a green light condition after reaching a target location before a traffic light on a target road can be determined based on the traffic light data. In some embodiments, considering that in online applications, it is necessary to provide the driving object with a recommended driving speed in advance for passing the preceding traffic light under a green light condition, a preset distance range can be set. After the driving object enters the preset distance range, a prediction is made as to whether the driving object can pass the preceding traffic light under a green light condition, and the recommended driving speed in such a case is also predicted.

[0078] To achieve the above objective, multiple locations within a preset distance range can be selected, and a corresponding green light time interval can be determined for each selected location. The target location can be one of the selected locations. The green light time interval can be for a single traffic light or for multiple consecutive traffic lights. The green light time interval for a single traffic light represents the target time for a vehicle to reach the target location. During this green light time interval, the vehicle can pass the single traffic light ahead with a green light if traveling at the recommended speed. The green light time interval for multiple consecutive traffic lights represents the target time for a vehicle to reach the target location. During this green light time interval, the vehicle can pass the multiple consecutive traffic lights ahead with a green light if traveling at the recommended speed. The green light time intervals corresponding to the multiple consecutive target locations within a distance range are equivalent to the bandwidth of the "green wave band" mentioned above. During the time interval corresponding to this "green wave band," a vehicle traveling at a certain speed from the target location can pass the single or multiple traffic lights ahead with a green light.

[0079] In some embodiments, a preset distance range can be predefined based on actual application requirements. The preset distance range can be a preset distance range before any traffic light on the target road, for example, a distance range of 200-250 meters before the traffic light. In some embodiments, when there are multiple consecutive traffic lights on the target road, the preset distance range can be the distance range before the first traffic light. Of course, in other embodiments, when there are multiple consecutive traffic lights on the target road, the preset distance range can be set for one or more of the traffic lights. Multiple preset distance ranges can be set, and the green light time interval of the traffic light can be determined for each location within the preset distance range.

[0080] In some embodiments, the green light transition time interval may correspond to a green light duration interval of a traffic light. The green light duration interval can be a sequence of time intervals corresponding to continuous cycles of the green light state, that is, the green light duration interval of the traffic light is a series of green light duration intervals, and each green light passing time interval corresponds to one of the series of green light duration intervals. The upper and lower boundary values ​​of the green light passing time interval are related to the upper and lower boundary values ​​of the corresponding green light duration interval. For example, the upper boundary value of the green light passing time interval (the earlier boundary value) is the value obtained after considering the driving time and queue waiting time of the current distance from the target position to the traffic light on the basis of the upper boundary value (the earlier boundary value) of the corresponding green light duration interval, and the lower boundary value of the green light passing time interval (the later boundary value) is the value obtained after considering the driving time of the current distance from the target position to the traffic light on the basis of the lower boundary value (the later boundary value) of the corresponding green light duration interval. That is to say, there is a linear relationship between the upper boundary value of the green light passing time interval and the upper boundary value of the corresponding green light duration interval, and there is a linear relationship between the lower boundary value of the green light passing time interval and the lower boundary value of the corresponding green light duration interval.

[0081] In some embodiments, the green light time interval of the traffic light may be the green light time interval of one of the traffic lights on the target road. In other embodiments, the green light time interval of the traffic light may also be the green light time interval of multiple consecutive traffic lights on the target road. When the driving object travels at a certain speed at the target position corresponding to the green light time interval, it can pass through multiple traffic lights continuously under the green light state. In other embodiments, the green light time interval may also be the green light time interval of some of the multiple consecutive traffic lights on the target road. For example, if there are three traffic lights on the target road, the green light time interval corresponding to any one of the three traffic lights, the green light time interval corresponding to two consecutive traffic lights, and / or the green light time interval corresponding to three consecutive traffic lights, etc. may be determined separately. It can be understood that the green light time interval is associated with the traffic light and the position in front of the traffic light, which means that when the driving object reaches the position in front of one or more consecutive traffic lights associated with the green light time interval at any time within the green light time interval, the driving object can drive through the one or more consecutive traffic lights at a certain speed in the green light state.

[0082] In some embodiments, the target location may be any location within a preset distance range, and a corresponding green light passing time interval may be calculated in advance for each location within the preset distance range.

[0083] In some embodiments, the green light time interval can be predetermined by the server, and the server sends the green light time interval and other relevant data to the client. In other embodiments, the green light time interval can also be determined directly in real time by the client.

[0084] Through the above method, the green light time interval corresponding to each position within a preset distance range in front of the traffic light can be mined for the target road, thereby forming the bandwidth of the "green wave band".

[0085] This green light time interval can be applied in location-based online services. For example, during online navigation, the navigation system can determine whether the driving object can pass the traffic light ahead and the maximum number of traffic lights that can be passed based on the current location of the driving object and the current time. It can also determine the recommended driving speed for passing the traffic light ahead and output the above information to the driving object.

[0086] In some embodiments, after determining the green light time intervals corresponding to all or part of the locations within a preset distance range, a driving speed can be recommended in real time for the driving object. The client of the driving object can obtain the current location of the driving object in real time, and when the current location is within the preset distance range, determine the green light time interval corresponding to the current location, and determine whether the current time is within the green light time interval. If the current time is within the green light time interval, it can be considered that the driving object can pass the traffic light ahead at a certain driving speed under the green light state, and therefore a recommended driving speed can be pushed to the driving object. The recommended driving speed can be the road speed corresponding to the traffic light ahead. If the traffic light ahead is different, the corresponding road speed can be different.

[0087] If the object is a regular vehicle, the client can display the recommended speed to the driver via voice or visuals to guide the driver to select the recommended speed so they can pass the traffic light ahead when the light is green. If the object is an intelligent driving object, the recommended speed can be pushed to the control system of the intelligent driving object so that the control system can control the intelligent driving object to drive at the recommended speed.

[0088] In an embodiment of the present disclosure, traffic light data on a target road is obtained, and the traffic light data includes the road speed on the target road, the queue dissipation characteristics in front of the light, the spatial topology characteristics of the traffic light, and the time characteristics of the traffic light signal; based on the traffic data mining, after the driving object reaches the target position in front of any traffic light on the target road, the green light time interval in which the driving object can directly pass the traffic light ahead under the green light state from the target position is determined. After the green light time interval is mined, it can be used in applications such as online navigation to recommend a driving speed for the driving object, thereby guiding the driving object to smoothly pass the traffic light ahead while driving at the recommended driving speed. The embodiment of the present disclosure guides the driving object to safely pass the traffic light ahead by mining the green light time interval in which the driving object can pass the traffic light on the target road in real time, and recommending the driving speed for the driving object to pass the traffic light in advance, thereby reducing the probability of the driving object waiting for the red light and improving the overall traffic efficiency of the intersection.

[0089] In an optional implementation of this embodiment, the traffic light spatial topology feature includes a spatial positional relationship between a plurality of traffic lights arranged consecutively on the target road; step S102, i.e., determining, based on the traffic light data, a green light time interval corresponding to a target position within a preset distance from the traffic light on the target road, further includes the following steps:

[0090] Based on the traffic light data, a green light time interval corresponding to a target position before a first one of the plurality of traffic lights and passing through one and / or a plurality of consecutive traffic lights is determined.

[0091] In this optional implementation, the spatial topological features of traffic lights include the spatial positional relationship of multiple traffic lights arranged consecutively on the target road. This spatial positional relationship may include, but is not limited to, the position of each traffic light and the relative positional relationship between two adjacent traffic lights. The preset distance range may be the preset distance range before the first traffic light among the multiple consecutive traffic lights. The first traffic light may be understood as the first traffic light encountered by the driving object when traveling on the target road. Based on the spatial position of the first traffic light and the current position of the driving object, it can be determined whether the driving object is within the preset distance range and the distance from the driving object to the first traffic light. Based on the relative positional relationships between the traffic lights and the distance from the driving object to the first traffic light, the distance from the driving object to other traffic lights can be determined.

[0092] In this embodiment, the green light time interval for a driving object to continuously pass through multiple traffic lights on the target road from a target position within a preset distance range can be determined based on traffic light data. That is, after the driving object reaches the target position within the green light time interval, the driving object can pass through the first traffic light in the green light state, and can continuously pass through the subsequent one or more traffic lights in the green light state without stopping.

[0093] It should be noted that, for each traffic light, the green light time interval that can be passed through each traffic light individually can also be determined. It can be understood that the green light time interval corresponding to multiple consecutive traffic lights is the intersection of the green light time intervals corresponding to each of the multiple consecutive traffic lights.

[0094] If there are three consecutive traffic lights on the target road, the green light time interval of the first traffic light is green1, the green light time interval of the second traffic light is green2, and the green light time interval of the third traffic light is green3. Then the green light time interval of continuously passing the green light signals of the first and second traffic lights is the intersection of green1 and green2, the green light time interval of continuously passing the green light signals of the first traffic light to the third traffic light is the intersection of green1, green2 and green3, and the green light time interval of continuously passing the green light signals of the second traffic light and the third traffic light is the intersection of green2 and green3.

[0095] In an optional implementation of this embodiment, the queue dissipation feature includes a corresponding relationship between the queue length at the traffic light and the time it takes for the tail of the queue to pass the traffic light under the green light state; the traffic light signal time feature includes a green light duration interval of the traffic light; step S102, i.e., determining, based on the traffic light data, a green light duration interval corresponding to a target position within a preset distance range from the traffic light on the target road, further includes the following steps:

[0096] determining an offset time for the moving object to travel from the target location to the traffic light at the road speed;

[0097] Determining the queue waiting time of the traveling object before passing the traffic light based on the correspondence between the queue length and time;

[0098] A green light passing time interval for a traveling object arriving at the target position to pass through the traffic light in a green light state is determined based on the green light duration interval, the offset time, and the queue waiting time.

[0099] In this optional implementation, a target location is defined as any location within a preset distance range. The offset time required for the vehicle to travel from the target location to the currently targeted traffic light at the road's normal speed is determined. The offset time can be calculated by dividing the distance from the target location to the traffic light by the road's normal speed. In some embodiments, the currently targeted traffic light can be the first traffic light on the target road.

[0100] The time it takes for a vehicle to travel from its target location to a traffic light depends not only on distance and speed, but also on whether there are other vehicles queuing at the traffic light ahead of the vehicle. Therefore, in the disclosed embodiments, the waiting time of a vehicle at a traffic light can also be determined based on the relationship between the number of vehicles in the queue and the waiting time.

[0101] In some embodiments, the process of calculating queue length can be pre-calculated on the server side or calculated in real time on the client side. When pre-calculating on the server side, the distance between the target location and the traffic light can be used as the actual queue length to determine the corresponding queue waiting time. The calculated queue waiting times for all actual queue lengths are then sent to the client side, allowing the client to calculate the queue waiting time corresponding to the actual queue length for the target road where the driving object is located during online application. Of course, it is understood that when implemented on the server side, the queue waiting time can also be calculated in real time for the driving object. The server side can pre-estimate the queue length of the driving object waiting for the current traffic light based on the vehicles on the target road, and then determine the queue waiting time based on this queue length and the aforementioned relationship between queue length and time. For example, the server side can calculate the queue length at the traffic light and the queue waiting time corresponding to this queue length on a minute-by-minute basis, and can update it every minute. In this way, when calculating the green light time interval for the driving object, the latest queue waiting time can be directly used.

[0102] Similarly, when performing real-time calculations on the client, the server can pre-send the correspondence between the queue length and time to the client. Furthermore, during online application, the server can also send the client the queue length at the traffic light ahead of the traveling object in real time. The client can then calculate the queue waiting time based on the queue length and the correspondence between the queue length and time. It is understood that the above is only one implementation method for calculating queue waiting time, and the embodiments of the present disclosure may also use other methods to calculate queue waiting time. Any method that can determine the queue waiting time of a traveling object at a traffic light based on the correspondence between the queue length and time is applicable to the embodiments of the present disclosure.

[0103] The green light passing time interval can be determined based on the offset time, queue waiting time and green light duration interval determined above. As described above, the green light passing time interval represents the maximum time offset and the time interval determined by the minimum time offset that a driving object can pass through without stopping when driving from the current position to the traffic light ahead. In the case of the maximum time offset, the driving object is exactly at the maximum boundary value of the green light duration interval when driving from the current position to the traffic light, that is, the moment before the end of the green light state corresponding to the green light duration interval, which means that the driving object passes through the traffic light at the last moment of the green light state after driving from the current position to the traffic light; and in the case of the minimum time offset, the driving object is exactly at the minimum boundary value of the green light duration interval when driving from the current position to the traffic light, that is, the moment when the green light state corresponding to the green light duration interval starts, which means that the driving object passes through the traffic light at the first moment of the green light state after driving from the current position to the traffic light.

[0104] Furthermore, it takes time for a vehicle to reach a traffic light, and depending on actual road conditions, it may encounter other vehicles waiting in line, so this waiting time must also be taken into account. Therefore, the green light duration interval corresponding to the vehicle's current location can be determined by factoring in the offset time it takes the vehicle to reach the traffic light and the waiting time in line, based on the maximum and minimum boundary values ​​of the green light duration interval. In other words, if the vehicle's arrival time at its current location falls within this green light duration interval, the vehicle can pass the traffic light under the green light condition.

[0105] In an optional implementation of this embodiment, the green light duration interval includes time intervals corresponding to multiple consecutive green light states of the same traffic light; and the step of determining, based on the green light duration interval, the offset time, and the queue waiting time, the green light passing time interval for a traveling object arriving at the target location to pass through the traffic light in the green light state further includes the following steps:

[0106] Determine the passing start time of each of the green light passing time intervals based on the green light start time, offset time and queue waiting time of each of the green light duration intervals corresponding to a plurality of consecutive green light states;

[0107] The passing end time of each of the green light passing time intervals is determined based on the green light end time and the offset time of each of the green light duration intervals corresponding to a plurality of consecutive green light states.

[0108] In this optional implementation, the green light duration interval may include multiple green light duration intervals corresponding to multiple consecutive green light states of the traffic light, and the traffic light is in the green light state during each green light duration interval. The green light passing time interval may also include multiple green light passing time intervals, each corresponding to each green light duration interval. The passing start time of each green light passing time interval is determined by the green light start time, offset time, and queue waiting time of the corresponding green light duration interval, and the passing end time of each green light passing time interval is determined by the green light end time and offset time of the corresponding green light duration interval.

[0109] Figures 2A-2B A schematic diagram showing the corresponding relationship between the green light time interval and the green light duration interval on the target road according to an embodiment of the present disclosure is shown. Assume that the target road includes three traffic lights set up in succession, such as Figure 2A As shown, the green light time interval corresponding to a single traffic light, i.e. the first traffic light, is shown as a group of short thick lines, while the green light time interval corresponding to two consecutive traffic lights, i.e. the first and second traffic lights, is shown as a group of short thin lines, and the green light time interval corresponding to three consecutive traffic lights, i.e. the first to third traffic lights, is shown as a group of long thin dotted lines. Figure 2A It can be seen that the green light time interval shown by each different line group can be understood as the bandwidth of a "green wave band", and the bandwidth of the "green wave band" shows the target position ( Figure 2A The correspondence between the distance from the first traffic light and the time interval represented by the "green wave band" indicates that when the driving object reaches the target position within the time interval, it can pass the corresponding traffic light under the green light state. Figure 2A The slope of these lines can be interpreted as the speed of the corresponding "green wave band," indicating that the vehicle can pass the corresponding traffic light under the green light state when traveling from the target location to the traffic light at this speed. This speed is determined based on the road driving speed.

[0110] like Figure 2BAs shown, at the target position within the preset distance range, the time offset 1 (time_offset1) between the driving object and the first traffic light is calculated based on the distance (offset) between the target position and the first traffic light divided by the road speed (kmph1) corresponding to the first traffic light, and the time offset 2 (time_offset2) between the driving object and the second traffic light is calculated based on the distance (dist12) between the first traffic light and the second traffic light divided by the road speed (kmph2) corresponding to the second traffic light, and then added with the time offset 1. The time offset 3 between the driving object and the third traffic light is calculated based on the distance (dist23) between the second traffic light and the third traffic light divided by the road speed (kmph3) corresponding to the third traffic light, and then added with the time offset 2.

[0111] Assume that the green light duration cycles of three traffic lights are as follows:

[0112] The green light period of the first traffic light is [t00, t01]∪[t02, t03]..., and the queue dissipation time of the first traffic light, that is, the time it takes for the tail of the queue to pass the light, is wait_time1.

[0113] The green light period of the second traffic light is [t10, t11]∪[t12, t13]..., and the queue dissipation time of the second traffic light, that is, the time it takes for the tail of the queue to pass the light, is wait_time2.

[0114] The green light period of the third traffic light is [t20, t21]∪[t22, t23]..., and the queue dissipation time of the third traffic light, that is, the time it takes for the tail of the queue to pass the light, is wait_time3.

[0115] Then the green light time interval for passing the first traffic light at the target location is:

[0116] green1=[t00-time_offset1+wait_time1,t01-time_offset1]

[0117] ∪[t02-time_offset1+wait_time1,t01-time_offset1]

[0118] ∪……

[0119] Then the green light time interval for passing the second traffic light at the target location is:

[0120] green2=[t10-time_offset2+wait_time2,t11-time_offset2]

[0121] ∪[t12-time_offset2+wait_time2,t13-time_offset2]

[0122] ∪……

[0123] Then the green light time interval for passing the third traffic light at the target location is:

[0124] green3=[t20-time_offset3+wait_time3,t21-time_offset3]

[0125] ∪[t22-time_offset3+wait_time3,t23-time_offset3]

[0126] ∪……

[0127] The time interval for the two green waves, i.e. the consecutive green light passing of the first and second traffic lights, is:

[0128] geen1∩green2

[0129] The green light interval of 3 traffic lights, that is, the green light interval from the first traffic light to the third traffic light, is:

[0130] green1∩green2∩green3.

[0131] By analogy, if there are n traffic lights on the target road, the theoretical time of the green wave of n lights can be calculated.

[0132] In an optional implementation of this embodiment, the method further includes the following steps:

[0133] The number of traffic lights that the traveling object can continuously pass through in a green light state from a target position is determined based on the green light time intervals corresponding to a plurality of consecutive traffic lights.

[0134] In this optional implementation, the corresponding green light time interval can be determined for each traffic light on the target road, for example, as follows: Figure 2B After determining the green light time interval for each traffic light, the intersection of the green light time intervals corresponding to multiple consecutive traffic lights can be calculated, and the maximum number of consecutive traffic lights whose intersection is not empty is determined as the number of traffic lights that the driving object can pass continuously from the target location under the green light state.

[0135] In an optional implementation of this embodiment, the method further includes the following steps:

[0136] Obtaining the current position of the moving object;

[0137] When the current position is within the preset distance range, determining the green light time interval corresponding to the target position matching the current position;

[0138] Based on the green light passing time interval, recommendation information that the driving object can pass the traffic light in the green light state is outputted to the driving object.

[0139] In this optional implementation, the server can determine the green light time interval corresponding to one and / or multiple consecutive traffic lights when the driving object is at each target position within a preset distance range. In online applications, such as online navigation, after detecting that the driving object has entered the preset distance range, the above-mentioned green light time interval corresponding to the target position matching the current position can be obtained. In other words, the green light time interval corresponding to each target position is determined in advance. After obtaining the current position, the green light time interval corresponding to the target position matching the current position (for example, the target position equal to the current position) is determined as the green light time interval corresponding to the current position. Based on the green light time interval, the recommended information that the driving object can pass the traffic light in the green light state at the current position is determined. The recommended information may include but is not limited to the maximum number of traffic lights that the driving object can pass without stopping, traffic light signs, and recommended driving speed. The recommended driving speed can be determined based on the road driving speed.

[0140] In some embodiments, when a driving object is determined to be at each target location within a preset distance range, the green light time interval corresponding to the traffic light can be executed on the client. After detecting that the driving object has entered the preset distance range, the client outputs the green light time interval at the current location, the recommended driving speed, etc. based on the determined green light time interval for the driving object. At the recommended driving speed, the driving object can pass through the recommended one or more traffic lights without stopping.

[0141] In some embodiments, the recommended driving speed may be equal to the road driving speed.

[0142] It should also be noted that, in other embodiments, the client may also determine the green light time intervals corresponding to one or more consecutive traffic lights when the traveling object is at a portion of the preset distance range. After detecting that the traveling object has reached a portion of the preset distance range, the client may output the aforementioned recommendation information to the traveling object.

[0143] In an optional implementation of this embodiment, the method further includes the following steps:

[0144] The preset distance range, the green light time interval corresponding to at least one target position within the preset distance range, and the road traffic speed are pushed to the client of the driving object, so that the client can output recommendation information to the driving object that it can pass the traffic light in the green light state based on the current position of the driving object.

[0145] In this optional implementation, when it is determined that the driving object is at each target position within the preset distance range, the green light time interval corresponding to the traffic light can be executed on the server side, and the server side pushes the preset distance range, the green light time interval corresponding to each target position, and the road speed and other information to the client of the driving object. After detecting that the driving object has entered the preset distance range, the client of the driving object can obtain the above-mentioned green light time interval corresponding to the target position that matches the current position. And based on the green light time interval, the recommended information of the driving object that can pass the traffic light in the green light state at the current position is determined. The recommended information may include but is not limited to the maximum number of traffic lights that the driving object can pass without stopping, traffic light signs, and recommended driving speed. The recommended driving speed can be determined based on the road driving speed. It should be noted that the above-mentioned recommendation information, that is, the green light time interval corresponding to any target location, the maximum number of traffic lights that the formal object at the target location can pass through within the green light time interval, the traffic light signs that can be passed, and the recommended driving speed have all been determined on the server side. The client only needs to push the matched recommendation information to the formal object after a successful match based on the current location.

[0146] In some embodiments, the recommended driving speed may be equal to the road driving speed.

[0147] It should also be noted that, in other embodiments, the server may also determine the green light time intervals corresponding to one or more consecutive traffic lights when the traveling object is at a portion of the preset distance range. After the client detects that the traveling object has reached a portion of the preset distance range, it outputs the above-mentioned recommendation information to the traveling object.

[0148] In an optional implementation of this embodiment, the method further includes the following steps:

[0149] Obtaining the current position of the moving object;

[0150] determining a current distance from the traveling object to a preceding traffic light based on the current position;

[0151] A recommended driving speed for the driving object to pass through a single traffic light ahead in a green light state is determined based on the current distance, the current time, the characteristics of the queue dissipation in front of the traffic light, and the green light duration interval.

[0152] In this optional implementation, for scenarios involving passing a single traffic light while the light is green, a different method than described above can be used to determine the green light time interval. For a single traffic light, a recommended speed for the driver to pass the preceding traffic light under the most recent green light can be output. This recommended speed may include, but is not limited to, a maximum speed and a minimum speed.

[0153] Based on the green light duration interval, the current distance between the driving object and the traffic light, the current time, the road driving speed and the queue dissipation characteristics in front of the light, it can be determined whether the driving object can catch up with the most recent green light state or the next green light state of the traffic light ahead, and then based on the green light duration interval of the corresponding green light state, the current distance between the driving object and the traffic light ahead and the road driving speed, the recommended driving speed of the driving object is determined. The recommended driving speed may include a maximum driving speed and a minimum driving speed. The maximum driving speed indicates the speed at which the light can be passed when the green light state is on, and the minimum driving speed is the speed that can ensure smooth passage through the traffic light ahead before the green light state ends.

[0154] In an optional implementation of this embodiment, the step of determining a recommended driving speed for the driving object to pass through a single traffic light ahead under a green light state based on the current distance, the current time, the characteristics of the queue dissipation before the traffic light, and the green light duration interval further includes the following steps:

[0155] When the current moment is within the green light duration interval of the traffic light, determining a lower limit of the recommended driving speed based on a first traffic light-passing speed, and setting an upper limit of the recommended driving speed to a first preset fixed value;

[0156] When the current moment is in the non-green light duration interval of the traffic light, the upper limit value of the recommended driving speed is determined based on the second green light speed, and the lower limit value of the recommended driving speed is set to a second preset fixed value; the first green light speed is lower than the second green light speed, and both are determined based on the current distance, the current moment, the queue dissipation characteristics in front of the light and the green light duration interval.

[0157] In this optional implementation, if the current moment is within the green light duration interval of the traffic light ahead, that is, the traffic light ahead is currently in a green state, a lower limit of the recommended driving speed can be determined based on the first speed required to pass the traffic light. This lower limit can be understood as the minimum recommended driving speed, while the upper limit of the recommended driving speed can be directly set to a first preset fixed value, such as 60. The reason why the lower limit of the recommended driving speed is determined in this scenario is that the traffic light ahead is already green. To pass the traffic light under this green light state, the vehicle must reach the traffic light before the green light state ends. Therefore, the driving speed cannot be too low. If it is too low, the green light state may end when the vehicle reaches the traffic light.

[0158] The first traffic light speed is determined based on the current distance between the driving object and the traffic light ahead, the current time, the queue dissipation characteristics corresponding to the traffic light ahead, and the green light duration interval of the current green light state of the traffic light ahead.

[0159] In some embodiments, the first traffic light speed can be determined based on the current distance between the driving object and the traffic light ahead divided by the time it takes the driving object to travel from the current position to the traffic light ahead, and the time can be obtained based on the difference between the current moment and the moment when the current green light state of the traffic light ahead ends.

[0160] If the current moment is within the non-green light duration interval of the traffic light ahead, that is, the traffic light ahead is currently in a red state (assuming only the red and green states of the traffic light ahead are considered), an upper limit of the recommended driving speed can be determined based on the second traffic light-passing speed. This upper limit can be understood as the maximum recommended driving speed, while the lower limit of the recommended driving speed can be directly set to a second preset fixed value, such as 25. The reason for determining the upper limit of the recommended driving speed in this scenario is that the traffic light ahead is currently in a non-green state. If the driving speed is too fast, the next green light state will not be on when the traffic light is reached, and the driver will need to stop and wait. Therefore, the driving speed cannot be too high.

[0161] The second traffic light speed is determined based on the current distance between the driving object and the traffic light ahead, the current time, the queue dissipation characteristics corresponding to the traffic light ahead, and the green light duration interval of the current green light state of the traffic light ahead.

[0162] In some embodiments, the second traffic light speed can be determined based on the current distance between the driving object and the traffic light ahead divided by the time it takes for the driving object to travel from the current position to the traffic light ahead, and the time can be obtained based on the difference between the current moment and the start time of the next green light state of the traffic light ahead.

[0163] In some embodiments, the first preset fixed value and the second preset fixed value are the upper and lower speed limits that can be used by a vehicle traveling on a target road, respectively. The first preset fixed value is greater than the second preset fixed value, and these two values ​​can be predetermined. The main reason for setting these two values ​​is that different roads have speed limit characteristics, and the two preset fixed values ​​need to be set based on these speed limit characteristics.

[0164] The following example illustrates one implementation of the traffic light speed recommendation process for a single traffic light:

[0165] Figure 3 Schematic diagram of a single light over light effect according to an embodiment of the present disclosure is shown. Figure 3 As shown, t0-t1 is the red light duration interval of the traffic light ahead, and t1-t3 is the next green light duration interval. Assuming that the current time of the driving object is between t0-t1, that is, the traffic light ahead is in the non-green light duration interval at the current time, time t2 is the time when all vehicles ahead of the driving object pass the traffic light ahead under the next green light state.

[0166] Assuming that the current moment is within the green light duration interval [t1, t3], the recommended driving speed range for the driving object is: [max(first possible speed to pass the light, 25), 60], that is, the lower limit of the recommended driving speed is the maximum value between the first possible speed to pass the light and 25, and the upper limit is a fixed value of 60.

[0167] Assuming that the current moment is within the red light duration interval [t0, t1], the recommended driving speed range for the driving object is: [max(first possible speed for passing the red light, 30), min(second possible speed for passing the red light, 50)], that is, the upper limit of the recommended driving speed is the minimum of the second possible speed for passing the red light and 50, and the lower limit is a fixed value of 30.

[0168] First light-passing speed = distance from the vehicle to the light / (|user time - upper limit of light-passing time|);

[0169] Maximum speed for passing the light = distance between the user and the light / (|user time - minimum time limit for passing the light|);

[0170] Time to pass the light = [time when the queue disappears (t2), time when the green light turns red (t3)];

[0171] To make the recommended speed easier for users to understand, you can use multiples of 5 for the recommended speed:

[0172] First, the speed of passing the light: take a multiple of 5, if the calculated value is 42, take 45;

[0173] The second way to calculate the speed of passing the light is to take a multiple of 5. If the result is 42, take 40.

[0174] Figure 4 FIG. 1 is a flow chart showing a navigation method according to an embodiment of the present disclosure. Figure 4 As shown, the navigation method includes the following steps:

[0175] In step S401, a planned path from the navigation starting point to the navigation destination is obtained;

[0176] In step S402, the green light time interval corresponding to the target road on the planned path is determined using the above-mentioned traffic light time determination method;

[0177] In step S403, the relevant information of passing the traffic light ahead is output to the guided object based on the current position of the guided object and the green light passing time interval.

[0178] In this embodiment, the navigation method can be executed on the server and / or the client. The planned path from the navigation starting point to the navigation destination can be planned by the navigation system. After obtaining the planned path from the navigation system, the roads involved in the planned path can be used as target roads, and the corresponding green light time intervals can be determined respectively using the traffic light time determination method mentioned above. The target road can be a road with a "green wave belt" to be excavated. In some embodiments, the target road can be a straight road, and one or more traffic lights can be set on the target road.

[0179] Traffic light data on the target road may include road traffic speed, queue dissipation characteristics in front of the light, traffic light spatial topological characteristics, and traffic light signal time characteristics.

[0180] In some embodiments, the road speed may be the speed at which the navigated object travels on the target road. The road speeds at different traffic lights on different roads may be different. In some embodiments, the navigated object may be a vehicle, an intelligent driving object, or the like. In some embodiments, the road speed may be obtained by aggregating the historical speeds of historical vehicles on the target road, and the road speed may reflect the traffic capacity on the target road. In addition, after obtaining the speed by aggregating the historical speeds of historical vehicles traveling on the target road, the speed limit characteristics of the target road may be used to perform speed correction to ensure that the corrected road speed is no higher than the speed limit of the target road. In addition, the corrected road speed may be multiplied by 5 so that the road speed is an integer multiple of 5. The road speed is multiplied by 5 so that when the road speed is recommended to the user, the user can more intuitively understand the size of the speed value.

[0181] In some embodiments, the queue dissipation feature can be a correspondence between the queue length of navigated objects waiting for a green light at a traffic light on a target road and the time it takes to pass that light. For example, if the time it takes for vehicles queuing 100 meters (the queue length) to pass the green light is 10 seconds, then the queue length is 100 meters, and the corresponding queue waiting time is 10 seconds. In some embodiments, the queue waiting time corresponding to any queue length within a certain distance from the traffic light can be pre-calculated to form the queue dissipation feature.

[0182] In some embodiments, the aforementioned queue dissipation feature can be constructed by capturing the trajectory data of floating vehicles within the influence range of traffic lights, inferring the parking positions of floating vehicles at intersections and the time it takes to pass through the intersection. During the construction process, abnormal samples can be first filtered out, and then the parking positions and time it takes for individual vehicles to pass through the intersection are calculated. Then, all vehicles within a certain period of time are counted, and the features of the vehicles at the intersection are aggregated. Finally, a minute-dimensional queue dissipation feature is calculated, which is the corresponding relationship between the length of the queue at the corresponding traffic light and the time it takes the vehicle at the end of the queue to pass through the traffic light for each minute of the day. In other words, the queue dissipation feature includes the corresponding relationship between the queue length at the traffic light and the queue dissipation time. In some embodiments, to improve the real-time performance of the data, the functional relationship between the queue length at the traffic light and the queue dissipation time is also captured, so that the client can calculate the queue dissipation time of the navigated object based on this functional relationship during the real-time guidance of the navigated object. In some embodiments, the queue dissipation feature corresponding to different traffic lights can be different.

[0183] In some embodiments, the spatial topological relationship of traffic lights may include but is not limited to the spatial position of traffic lights on the target road, and in the case of multiple traffic lights, the relative positional relationship between the multiple traffic lights.

[0184] In some embodiments, traffic light signal temporal features may include, but are not limited to, a sequence of duration intervals for the red, yellow, and green signal states of a traffic light, each of which includes the start and end times of the corresponding signal state. For example, the sequence of duration intervals for the green light state of traffic light A on a target road can be represented as: [t0, t1][t2, t3]…[tn-1, tn]; where [t0, t1] is assumed to be the green light duration interval for the first green light state, [t2, t3] is the green light duration interval for the second green light state, and so on.

[0185] The traffic light signal time characteristics can be calculated based on the actual changing conditions of the traffic lights on the target road. For details, please refer to the existing technology and no specific limitations are given here. Of course, the traffic light signal time characteristics can also be provided by relevant departments.

[0186] After acquiring the aforementioned traffic light data, the green light passing time interval within which the navigated object can pass the traffic light on the target road, after reaching a target location before the traffic light, can be determined based on the traffic light data. In some embodiments, considering that in online applications, it is necessary to provide the navigated object with a recommended driving speed in advance for passing the preceding traffic light on a green light, a preset distance range can be set. After the navigated object enters the preset distance range, a prediction is made as to whether the navigated object can pass the preceding traffic light on a green light, and the recommended driving speed in such a case.

[0187] To achieve the above objective, multiple locations within a preset distance range can be selected, and a corresponding green light time interval can be determined for each selected location. The target location can be one of the selected locations. The green light time interval can be for a single traffic light or for multiple consecutive traffic lights. The green light time interval for a single traffic light represents the target time for the guided object to reach the target location within the green light time interval. If the guided object travels at the recommended speed during the green light time interval, the guided object can pass the single traffic light ahead with a green light. The green light time interval for multiple consecutive traffic lights represents the target time for the guided object to reach the target location within the green light time interval. If the guided object travels at the recommended speed during the green light time interval, the guided object can pass the multiple consecutive traffic lights ahead with a green light. The green light time intervals corresponding to the multiple consecutive target locations within a distance range are equivalent to the bandwidth of the "green wave band" mentioned above. During the time interval corresponding to the "green wave band," a vehicle traveling at a certain speed from the target location can pass the single or multiple traffic lights ahead with a green light.

[0188] In some embodiments, a preset distance range can be predefined based on actual application requirements. The preset distance range can be a preset distance range before any traffic light on the target road, for example, a distance range of 200-250 meters before the traffic light. In some embodiments, when there are multiple consecutive traffic lights on the target road, the preset distance range can be the distance range before the first traffic light. Of course, in other embodiments, when there are multiple consecutive traffic lights on the target road, the preset distance range can be set for one or more of the traffic lights. Multiple preset distance ranges can be set, and the green light time interval of the traffic light can be determined for each location within the preset distance range.

[0189] In some embodiments, the green light transition time interval may correspond to a green light duration interval of a traffic light. The green light duration interval can be a sequence of time intervals corresponding to continuous cycles of the green light state, that is, the green light duration interval of the traffic light is a series of green light duration intervals, and each green light passing time interval corresponds to one of the series of green light duration intervals. The upper and lower boundary values ​​of the green light passing time interval are related to the upper and lower boundary values ​​of the corresponding green light duration interval. For example, the upper boundary value of the green light passing time interval (the earlier boundary value) is the value obtained after considering the driving time and queue waiting time of the current distance from the target position to the traffic light on the basis of the upper boundary value (the earlier boundary value) of the corresponding green light duration interval, and the lower boundary value of the green light passing time interval (the later boundary value) is the value obtained after considering the driving time of the current distance from the target position to the traffic light on the basis of the lower boundary value (the later boundary value) of the corresponding green light duration interval. That is to say, there is a linear relationship between the upper boundary value of the green light passing time interval and the upper boundary value of the corresponding green light duration interval, and there is a linear relationship between the lower boundary value of the green light passing time interval and the lower boundary value of the corresponding green light duration interval.

[0190] In some embodiments, the green light time interval of the traffic light may be the green light time interval of one of the traffic lights on the target road. In other embodiments, the green light time interval of the traffic light may also be the green light time interval of multiple consecutive traffic lights on the target road. When the navigated object travels at a certain speed at the target position corresponding to the green light time interval, it can pass through multiple traffic lights in a green light state. In other embodiments, the green light time interval may also be the green light time interval of some of the multiple consecutive traffic lights on the target road. For example, if there are three traffic lights on the target road, the green light time interval corresponding to any one of the three traffic lights, the green light time interval corresponding to two consecutive traffic lights, and / or the green light time interval corresponding to three consecutive traffic lights, etc. may be determined separately. It can be understood that the green light time interval is associated with the traffic light and the position in front of the traffic light, which means that when the navigated object reaches the position associated with the green light time interval in front of one or more consecutive traffic lights at any time within the green light time interval, the navigated object can drive through the one or more consecutive traffic lights at a certain speed in the green light state.

[0191] In some embodiments, the target location may be any location within a preset distance range, and a corresponding green light passing time interval may be calculated in advance for each location within the preset distance range.

[0192] In some embodiments, the green light time interval can be predetermined by the server, and the server sends the green light time interval and other relevant data to the client. In other embodiments, the green light time interval can also be determined directly in real time by the client.

[0193] Through the above method, the green light time interval corresponding to each position within a preset distance range in front of the traffic light can be mined for the target road, thereby forming the bandwidth of the "green wave band".

[0194] This green light time interval can be applied in location-based online services. For example, during online navigation, the navigation system can determine whether the navigated object can pass the traffic light ahead and the maximum number of traffic lights that can be passed based on the current location and current time of the navigated object. It can also determine the recommended driving speed for passing the traffic light ahead and output the above information to the navigated object.

[0195] In some embodiments, before the navigated object arrives at the target road on the planned route, the server may pre-determine the green light time intervals corresponding to all or part of the locations within a preset distance range before the first traffic light encountered on the target road, and push the green light time intervals to the navigated object's client. The navigated object's client may obtain the navigated object's current location in real time, and after the current location is within the preset distance range, determine the green light time interval corresponding to the current location, and determine whether the current time is within the green light time interval. If the current time is within the green light time interval, it can be assumed that the navigated object can pass the traffic light ahead at a certain speed under the green light condition. Therefore, relevant information regarding passing the traffic light ahead can be output to the navigated object. This relevant information may include, but is not limited to, information on the ability to pass the traffic light ahead without stopping, the maximum number of traffic lights that can be passed, and a corresponding recommended driving speed. The recommended driving speed may be the road speed corresponding to the traffic light ahead; different traffic lights ahead may have different corresponding road speeds. If the current time is not within the green light passing time interval, it can be considered that the navigated object cannot pass the traffic light ahead directly without stopping. At this time, the relevant information about passing the traffic light ahead can be not output to the driving object, or a prompt message indicating that the traffic light ahead cannot be passed directly can be output.

[0196] When the guided object is a regular vehicle, the client can display the recommended speed to the driver of the guided object via voice or visuals to guide the driver to select the recommended speed so that they can pass the traffic light ahead in a green state. When the guided object is an intelligent driving object, the recommended speed can be pushed to the control system of the intelligent driving object so that the control system can control the intelligent driving object to drive at the recommended speed.

[0197] In an embodiment of the present disclosure, a planned path from a navigation starting point to a navigation destination is obtained, and based on the traffic light time determination method described above, a green light time interval corresponding to a target road involved in the planned path is determined, and then navigation services are provided to the navigated object based on the current location of the navigated object and the green light time interval. By mining the green light time intervals that allow the navigated object to pass traffic lights on the target road in real time and recommending relevant information about the traffic light ahead, such as driving speed, to the navigated object in advance, the present disclosure guides the navigated object to safely pass the traffic light ahead, reduces the probability of the navigated object waiting for a red light, and improves traffic efficiency at the intersection overall.

[0198] The following are embodiments of the apparatus disclosed herein, which can be used to implement the embodiments of the apparatus disclosed herein.

[0199] Figure 5 The block diagram of the time interval determination device according to one embodiment of the present disclosure is shown. The device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. Figure 5 As shown, the time interval determining device includes:

[0200] The first acquisition module 501 is configured to acquire traffic light data on a target road; the traffic light data includes road traffic speed, queue dissipation characteristics before the light, traffic light spatial topology characteristics, and traffic light signal time characteristics;

[0201] The first determination module 502 is configured to determine the green light time interval corresponding to the target position within a preset distance range in front of the traffic light on the target road based on the traffic light data; wherein, the green light time interval indicates that when the target time for the driving object to reach the target position is within the green light time interval, the driving object can pass the traffic light under the green light state.

[0202] In this embodiment, the time interval determination device can be executed on the server and / or the client. The target road can be a road where the "green wave belt" is to be excavated. In some embodiments, the target road can be a straight road, and one or more traffic lights can be set on the target road.

[0203] Traffic light data on the target road may include road traffic speed, queue dissipation characteristics in front of the light, traffic light spatial topological characteristics, and traffic light signal time characteristics.

[0204] In some embodiments, the road speed may be the speed of a driving object on a target road. The road speeds at different traffic lights on different roads may be different. In some embodiments, the driving object may be a vehicle, an intelligent driving object, or the like. In some embodiments, the road speed may be obtained by aggregating the historical speeds of historical vehicles on the target road. The road speed may reflect the traffic capacity of the target road. In addition, after obtaining the speed by aggregating the historical speeds of historical vehicles traveling on the target road, the speed limit characteristics of the target road may be used to perform speed correction to ensure that the corrected road speed is no higher than the speed limit of the target road. In addition, the corrected road speed may be multiplied by 5 so that the road speed is an integer multiple of 5. The road speed is multiplied by 5 so that when the road speed is recommended to the user, the user can more intuitively understand the magnitude of the speed value.

[0205] In some embodiments, the queue dissipation feature can be the corresponding relationship between the queue length of vehicles waiting to pass the green light at a traffic light on a target road and the time it takes to pass the green light. For example, if the time it takes for vehicles queuing 100 meters (queue length) at a traffic light to pass the green light is 10 seconds, then the queue length is 100 meters and the corresponding queue waiting time is 10 seconds. In some embodiments, the queue waiting time corresponding to any queue length within a certain distance from the traffic light can be pre-calculated to form the above-mentioned queue dissipation feature.

[0206] In some embodiments, the aforementioned queue dissipation feature can be constructed by capturing the trajectory data of floating vehicles within the influence range of traffic lights, inferring the parking position of floating vehicles at the intersection and the time it takes to pass through the intersection. During the construction process, abnormal samples can be first filtered out, and then the parking position and time it takes for a single vehicle to pass through the intersection can be calculated. Then, all vehicles within a certain period of time are counted, and the features of the vehicles at the intersection are aggregated. Finally, the minute-dimensional queue dissipation feature is calculated, which is the corresponding relationship between the length of the queue at the corresponding traffic light and the time it takes the vehicle at the end of the queue to pass through the traffic light for each minute of the day. In other words, the queue dissipation feature includes the corresponding relationship between the queue length at the traffic light and the queue dissipation time. In some embodiments, to improve the real-time performance of the data, the functional relationship between the queue length at the traffic light and the queue dissipation time is also captured, so that the client can calculate the queue dissipation time of the traveling object based on this functional relationship during the real-time guidance of the traveling object. In some embodiments, the queue dissipation feature corresponding to different traffic lights can be different.

[0207] In some embodiments, the spatial topological relationship of traffic lights may include but is not limited to the spatial position of traffic lights on the target road, and in the case of multiple traffic lights, the relative positional relationship between the multiple traffic lights.

[0208] In some embodiments, traffic light signal temporal features may include, but are not limited to, a sequence of duration intervals for the red, yellow, and green signal states of a traffic light, each of which includes the start and end times of the corresponding signal state. For example, the sequence of duration intervals for the green light state of traffic light A on a target road can be represented as: [t0, t1][t2, t3]…[tn-1, tn]; where [t0, t1] is assumed to be the green light duration interval for the first green light state, [t2, t3] is the green light duration interval for the second green light state, and so on.

[0209] The traffic light signal time characteristics can be calculated based on the actual changing conditions of the traffic lights on the target road. For details, please refer to the existing technology and no specific limitations are given here. Of course, the traffic light signal time characteristics can also be provided by relevant departments.

[0210] After obtaining the aforementioned traffic light data, the green light passing time interval within which a driving object can pass the traffic light under a green light condition after reaching a target location before a traffic light on a target road can be determined based on the traffic light data. In some embodiments, considering that in online applications, it is necessary to provide the driving object with a recommended driving speed in advance for passing the preceding traffic light under a green light condition, a preset distance range can be set. After the driving object enters the preset distance range, a prediction is made as to whether the driving object can pass the preceding traffic light under a green light condition, and the recommended driving speed in such a case is also predicted.

[0211] To achieve the above objective, multiple locations within a preset distance range can be selected, and a corresponding green light time interval can be determined for each selected location. The target location can be one of the selected locations. The green light time interval can be for a single traffic light or for multiple consecutive traffic lights. The green light time interval for a single traffic light represents the target time for a vehicle to reach the target location. During this green light time interval, the vehicle can pass the single traffic light ahead with a green light if traveling at the recommended speed. The green light time interval for multiple consecutive traffic lights represents the target time for a vehicle to reach the target location. During this green light time interval, the vehicle can pass the multiple consecutive traffic lights ahead with a green light if traveling at the recommended speed. The green light time intervals corresponding to the multiple consecutive target locations within a distance range are equivalent to the bandwidth of the "green wave band" mentioned above. During the time interval corresponding to this "green wave band," a vehicle traveling at a certain speed from the target location can pass the single or multiple traffic lights ahead with a green light.

[0212] In some embodiments, a preset distance range can be predefined based on actual application requirements. The preset distance range can be a preset distance range before any traffic light on the target road, for example, a distance range of 200-250 meters before the traffic light. In some embodiments, when there are multiple consecutive traffic lights on the target road, the preset distance range can be the distance range before the first traffic light. Of course, in other embodiments, when there are multiple consecutive traffic lights on the target road, the preset distance range can be set for one or more of the traffic lights. Multiple preset distance ranges can be set, and the green light time interval of the traffic light can be determined for each location within the preset distance range.

[0213] In some embodiments, the green light transition time interval may correspond to a green light duration interval of a traffic light. The green light duration interval can be a sequence of time intervals corresponding to continuous cycles of the green light state, that is, the green light duration interval of the traffic light is a series of green light duration intervals, and each green light passing time interval corresponds to one of the series of green light duration intervals. The upper and lower boundary values ​​of the green light passing time interval are related to the upper and lower boundary values ​​of the corresponding green light duration interval. For example, the upper boundary value of the green light passing time interval (the earlier boundary value) is the value obtained after considering the driving time and queue waiting time of the current distance from the target position to the traffic light on the basis of the upper boundary value (the earlier boundary value) of the corresponding green light duration interval, and the lower boundary value of the green light passing time interval (the later boundary value) is the value obtained after considering the driving time of the current distance from the target position to the traffic light on the basis of the lower boundary value (the later boundary value) of the corresponding green light duration interval. That is to say, there is a linear relationship between the upper boundary value of the green light passing time interval and the upper boundary value of the corresponding green light duration interval, and there is a linear relationship between the lower boundary value of the green light passing time interval and the lower boundary value of the corresponding green light duration interval.

[0214] In some embodiments, the green light time interval of the traffic light may be the green light time interval of one of the traffic lights on the target road. In other embodiments, the green light time interval of the traffic light may also be the green light time interval of multiple consecutive traffic lights on the target road. When the driving object travels at a certain speed at the target position corresponding to the green light time interval, it can pass through multiple traffic lights continuously under the green light state. In other embodiments, the green light time interval may also be the green light time interval of some of the multiple consecutive traffic lights on the target road. For example, if there are three traffic lights on the target road, the green light time interval corresponding to any one of the three traffic lights, the green light time interval corresponding to two consecutive traffic lights, and / or the green light time interval corresponding to three consecutive traffic lights, etc. may be determined separately. It can be understood that the green light time interval is associated with the traffic light and the position in front of the traffic light, which means that when the driving object reaches the position in front of one or more consecutive traffic lights associated with the green light time interval at any time within the green light time interval, the driving object can drive through the one or more consecutive traffic lights at a certain speed in the green light state.

[0215] In some embodiments, the target location may be any location within a preset distance range, and a corresponding green light passing time interval may be calculated in advance for each location within the preset distance range.

[0216] In some embodiments, the green light time interval can be predetermined by the server, and the server sends the green light time interval and other relevant data to the client. In other embodiments, the green light time interval can also be determined directly in real time by the client.

[0217] Through the above method, the green light time interval corresponding to each position within a preset distance range in front of the traffic light can be mined for the target road, thereby forming the bandwidth of the "green wave band".

[0218] This green light time interval can be applied in location-based online services. For example, during online navigation, the navigation system can determine whether the driving object can pass the traffic light ahead and the maximum number of traffic lights that can be passed based on the current location of the driving object and the current time. It can also determine the recommended driving speed for passing the traffic light ahead and output the above information to the driving object.

[0219] In some embodiments, after determining the green light time intervals corresponding to all or part of the locations within a preset distance range, a driving speed can be recommended in real time for the driving object. The client of the driving object can obtain the current location of the driving object in real time, and when the current location is within the preset distance range, determine the green light time interval corresponding to the current location, and determine whether the current time is within the green light time interval. If the current time is within the green light time interval, it can be considered that the driving object can pass the traffic light ahead at a certain driving speed under the green light state, and therefore a recommended driving speed can be pushed to the driving object. The recommended driving speed can be the road speed corresponding to the traffic light ahead. If the traffic light ahead is different, the corresponding road speed can be different.

[0220] If the object is a regular vehicle, the client can display the recommended speed to the driver via voice or visuals to guide the driver to select the recommended speed so they can pass the traffic light ahead when the light is green. If the object is an intelligent driving object, the recommended speed can be pushed to the control system of the intelligent driving object so that the control system can control the intelligent driving object to drive at the recommended speed.

[0221] In an embodiment of the present disclosure, traffic light data on a target road is obtained, and the traffic light data includes the road speed on the target road, the queue dissipation characteristics in front of the light, the spatial topology characteristics of the traffic light, and the time characteristics of the traffic light signal; based on the traffic data mining, after the driving object reaches the target position in front of any traffic light on the target road, the green light time interval in which the driving object can directly pass the traffic light ahead under the green light state from the target position is determined. After the green light time interval is mined, it can be used in applications such as online navigation to recommend a driving speed for the driving object, thereby guiding the driving object to smoothly pass the traffic light ahead while driving at the recommended driving speed. The embodiment of the present disclosure guides the driving object to safely pass the traffic light ahead by mining the green light time interval in which the driving object can pass the traffic light on the target road in real time, and recommending the driving speed for the driving object to pass the traffic light in advance, thereby reducing the probability of the driving object waiting for the red light and improving the overall traffic efficiency of the intersection.

[0222] In an optional implementation of this embodiment, the traffic light spatial topology feature includes a spatial positional relationship between a plurality of traffic lights arranged consecutively on the target road; and the first determining module includes:

[0223] The first determining submodule is configured to determine, based on the traffic light data, a green light passing time interval corresponding to a target position before a first one of the plurality of traffic lights and passing through one and / or a plurality of consecutive traffic lights.

[0224] In an optional implementation of this embodiment, the queue dissipation feature includes a corresponding relationship between the queue length at the traffic light and the time it takes for the tail of the queue to pass through the traffic light in the green light state; the traffic light signal time feature includes the green light duration interval of the traffic light; and the first determination module includes:

[0225] A second determining submodule is configured to determine an offset time for the traveling object to travel from the target position to the traffic light at the road speed;

[0226] A third determining submodule is configured to determine the queue waiting time of the traveling object before passing the traffic light based on the correspondence between the queue length and time;

[0227] The fourth determining submodule is configured to determine a green light passing time interval for a moving object arriving at the target position to pass through the traffic light under the green light state based on the green light duration interval, the offset time and the queue waiting time.

[0228] In an optional implementation of this embodiment, the green light duration interval includes time intervals corresponding to multiple consecutive green light states of the same traffic light; and the fourth determining submodule includes:

[0229] A fifth determining submodule is configured to determine a passing start time of each of the green light passing time intervals based on the green light start time, the offset time and the queue waiting time of each of the green light duration intervals corresponding to a plurality of consecutive green light states;

[0230] The sixth determining submodule is configured to determine the passing end time of each of the green light passing time intervals based on the green light end time and the offset time of each of the green light duration intervals corresponding to a plurality of consecutive green light states.

[0231] In an optional implementation of this embodiment, the apparatus further includes:

[0232] The second determining module is configured to determine the number of traffic lights that the traveling object can pass through continuously in the green light state from the target position based on the green light time intervals corresponding to multiple consecutive traffic lights.

[0233] In an optional implementation of this embodiment, the apparatus further includes:

[0234] A second acquisition module is configured to acquire the current position of the moving object;

[0235] a third determining module configured to determine, when the current position is within the preset distance range, the green light time interval corresponding to the target position matching the current position;

[0236] The first output module is configured to output recommendation information that the driving object can pass the traffic light in a green light state based on the green light passing time interval.

[0237] In an optional implementation of this embodiment, the apparatus further includes:

[0238] The push module is configured to push the preset distance range, the green light time interval corresponding to at least one target position within the preset distance range, and the road traffic speed to the client of the driving object, so that the client can output recommendation information to the driving object that it can pass the traffic light in the green light state based on the current position of the driving object.

[0239] In an optional implementation of this embodiment, the apparatus further includes:

[0240] a third acquisition module, configured to acquire the current position of the traveling object;

[0241] a fourth determining module, configured to determine a current distance from the traveling object to a traffic light ahead based on the current position;

[0242] The fifth determination module is configured to determine a recommended driving speed for the driving object to pass through a single traffic light ahead in a green light state based on the current distance, the current time, the queue dissipation characteristics before the traffic light, and the green light duration interval.

[0243] In an optional implementation of this embodiment, the fifth determining module includes:

[0244] a seventh determining submodule configured to, when the current moment is within the green light duration interval of the traffic light, determine a lower limit of the recommended driving speed based on the first traffic light-passing speed, and set an upper limit of the recommended driving speed to a first preset fixed value;

[0245] The eighth determination submodule is configured to determine the upper limit of the recommended driving speed based on the second traffic light-passing speed and set the lower limit of the recommended driving speed to a second preset fixed value when the current moment is in the non-green light duration interval of the traffic light; the first traffic light-passing speed is lower than the second traffic light-passing speed, and both are determined based on the current distance, the current moment, the queue dissipation characteristics in front of the light and the green light duration interval.

[0246] The time interval determination device in this embodiment corresponds to the time interval determination method described above. For specific details, please refer to the description of the time interval determination method described above, which will not be repeated here.

[0247] Figure 6 FIG1 shows a structural block diagram of a navigation device according to an embodiment of the present disclosure. The device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. Figure 6 As shown, the navigation device includes:

[0248] The third acquisition module 601 is configured to acquire a planned path from the navigation start point to the navigation destination;

[0249] The sixth determining module 602 is configured to determine the green light time interval corresponding to the target road on the planned path using the time interval determining device;

[0250] The second output module 603 is configured to output relevant information of passing the traffic light ahead to the navigated object based on the current position of the navigated object and the green light passing time interval.

[0251] The navigation device in this embodiment corresponds to the navigation method described above. For specific details, please refer to the description of the navigation method described above, which will not be repeated here.

[0252] Figure 7It is a structural diagram of an electronic device suitable for implementing the time interval determination method and / or navigation method according to an embodiment of the present disclosure.

[0253] like Figure 7 As shown, the electronic device 700 includes a processing unit 701, which can be implemented as a processing unit such as a CPU, a GPU, an FPGA, an NPU, etc. The processing unit 701 can perform various processes in the embodiment of any of the above methods of the present disclosure according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device 700 are also stored. The processing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0254] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, and the like; an output section 707 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 708 including a hard disk; and a communication section 709 including a network interface card such as a LAN card or a modem. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 710 as needed, so that computer programs read therefrom can be installed into the storage section 708 as needed.

[0255] In particular, according to embodiments of the present disclosure, any of the methods described above with reference to the embodiments of the present disclosure may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for executing any of the methods described in the embodiments of the present disclosure. In such embodiments, the computer program may be downloaded and installed from a network via the communication portion 709 and / or installed from a removable medium 711.

[0256] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0257] The units or modules described in the embodiments of the present disclosure may be implemented in software or hardware. The units or modules described may also be provided in a processor, and the names of these units or modules do not, in certain circumstances, limit the units or modules themselves.

[0258] As another aspect, the present disclosure further provides a computer-readable storage medium. This computer-readable storage medium may be included in the apparatus described in the above embodiments, or may be a standalone computer-readable storage medium not incorporated into the apparatus. The computer-readable storage medium stores one or more programs, which are used by one or more processors to execute the methods described in the present disclosure.

[0259] The above description is merely a preferred embodiment of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention herein is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.

Claims

1. A method for determining a time interval, wherein: include: Obtaining traffic light data on a target road; the traffic light data includes road traffic speed, queue dissipation characteristics in front of the light, traffic light spatial topology characteristics, and traffic light signal time characteristics; The traffic light queue dissipation feature includes the corresponding relationship between the queue length in front of the traffic light and the time it takes for the tail of the queue to pass through the traffic light in the green light state; the traffic light signal time feature includes the green light duration interval of the traffic light; determining an offset time for a moving object to travel from a target position to the traffic light at the road speed; Determining the queue waiting time of the traveling object before passing the traffic light based on the correspondence between the queue length and time; Determine a green light passing time interval for a traveling object arriving at the target location to pass through the traffic light under a green light state based on the green light duration interval, the offset time, and the queue waiting time; The green light passing time interval indicates that when the target time for the moving object to arrive at the target position is within the green light passing time interval, the moving object can pass the traffic light under the green light state.

2. The method according to claim 1, wherein The green light duration interval includes time intervals corresponding to multiple consecutive green light states of the same traffic light; and determining the green light passing time interval for a traveling object arriving at the target location to pass through the traffic light in the green light state based on the green light duration interval, the offset time, and the queue waiting time includes: Determine the passing start time of each of the green light passing time intervals based on the green light start time, offset time and queue waiting time of each of the green light duration intervals corresponding to a plurality of consecutive green light states; The passing end time of each of the green light passing time intervals is determined based on the green light end time and the offset time of each of the green light duration intervals corresponding to a plurality of consecutive green light states.

3. The method according to claim 2, wherein: The method further comprises: The number of traffic lights that the traveling object can continuously pass through in a green light state from a target position is determined based on the green light time intervals corresponding to a plurality of consecutive traffic lights.

4. The method according to claim 2 or 3, wherein: The method further comprises: Obtaining the current position of the moving object; When the current position is within a preset distance range, determining the green light time interval corresponding to the target position matching the current position; Based on the green light passing time interval, recommendation information that the driving object can pass the traffic light in the green light state is outputted to the driving object.

5. The method according to claim 4, wherein The method further comprises: The preset distance range, the green light time interval corresponding to at least one target position within the preset distance range, and the road traffic speed are pushed to the client of the driving object, so that the client can output recommendation information to the driving object that it can pass the traffic light in the green light state based on the current position of the driving object.

6. The method according to claim 2 or 3, wherein: The method further comprises: Obtaining the current position of the moving object; determining a current distance from the traveling object to a preceding traffic light based on the current position; A recommended driving speed for the driving object to pass through a single traffic light ahead in a green light state is determined based on the current distance, the current time, the characteristics of the queue dissipation in front of the traffic light, and the green light duration interval.

7. The method according to claim 6, wherein: Determining a recommended driving speed for the driving object to pass through a single traffic light ahead in a green light state based on the current distance, the current time, the queue dissipation characteristic before the traffic light, and the green light duration interval includes: When the current moment is within the green light duration interval of the traffic light, determining a lower limit of the recommended driving speed based on a first traffic light-passing speed, and setting an upper limit of the recommended driving speed to a first preset fixed value; When the current moment is in the non-green light duration interval of the traffic light, the upper limit value of the recommended driving speed is determined based on the second green light speed, and the lower limit value of the recommended driving speed is set to a second preset fixed value; the first green light speed is lower than the second green light speed, and both are determined based on the current distance, the current moment, the queue dissipation characteristics in front of the light and the green light duration interval.

8. A navigation method, wherein: include: Get the planned path from the navigation starting point to the navigation destination; Determine the green light time interval corresponding to the target road on the planned path using the method described in any one of claims 1 to 7; Based on the current position of the navigated object and the green light passing time interval, relevant information about passing the traffic light ahead is outputted to the navigated object.

9. A time interval determination device, wherein: include: A first acquisition module is configured to acquire traffic light data on a target road; the traffic light data includes road traffic speed, queue dissipation characteristics before the traffic light, traffic light spatial topology characteristics, and traffic light signal time characteristics; wherein the queue dissipation characteristics before the traffic light include a correspondence between the length of the queue before the traffic light and the time the tail of the queue passes the traffic light under the green light state and the length of time; the traffic light signal time characteristics include the green light duration interval of the traffic light; The first determination module is configured to determine the offset time for the driving object to travel from the target position to the traffic light at the road traffic speed; determine the queue waiting time before the driving object passes the traffic light based on the correspondence between the queue length and time; determine the green light passing time interval for the driving object arriving at the target position to pass the traffic light under the green light state based on the green light duration interval, the offset time and the queue waiting time; wherein, the green light passing time interval indicates that when the target time for the driving object to arrive at the target position is within the green light passing time interval, the driving object can pass the traffic light under the green light state.

10. A navigation device, wherein: include: A third acquisition module is configured to acquire a planned path from the navigation start point to the navigation destination; a sixth determining module, configured to determine a green light time interval corresponding to a target road on the planned path using the apparatus according to claim 9; The second output module is configured to output relevant information of passing the traffic light ahead to the navigated object based on the current position of the navigated object and the green light passing time interval.

11. An electronic device, wherein: The method comprises a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 8.

12. A computer program product comprising computer instructions, wherein: When the computer instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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