A method, device and readable medium for determining road travel time

Abstract

The embodiment of the specification discloses a kind of determination method, device and readable medium of road traffic length. Scheme can include: obtaining the first vehicle average speed of target section;The first vehicle average speed is the average value of the instantaneous speed of vehicle of the target section at the first sampling time;Obtain the number of vehicles existing in the target section at the first sampling time collected by road side perception device;Based on the vehicle quantity and the size information of the target section, the vehicle density coefficient of the target section is obtained;Based on the first vehicle average speed and the vehicle density coefficient, the first traffic length of the target section is determined based on pre-design formula, wherein at least the first calculation term and the second calculation term are included in the pre-design formula, the first calculation term is positively correlated with the vehicle density coefficient of the target section, and the second calculation term is negatively correlated with the vehicle density coefficient of the target section.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving, in particular to a method and device for determining road passing time and a readable medium. BACKGROUND

[0002] In the field of automatic driving, it is often necessary to calculate the passing time by relying on the speed of vehicles in a road section. The current road passing time is often the average of the speeds of all vehicles on the road, and the passing time is determined according to the average speed of the vehicles. However, when there are few vehicles on the road and the speed of the vehicles is low, the average speed calculated will be low, and the current road section will be determined as a congested road section, which does not match the actual situation.

[0003] Therefore, there is an urgent need for a method for determining road passing time to improve the accuracy of road passing time calculation. SUMMARY

[0004] The embodiments of the present specification provide a method and device for determining road passing time and a readable medium to improve the accuracy of road passing time prediction.

[0005] To solve the above technical problems, the embodiments of the present specification are implemented as follows:

[0006] The method for determining road passing time provided by the embodiments of the present specification comprises:

[0007] obtaining a first vehicle average speed of a target road section; the first vehicle average speed is an average of the instantaneous speeds of vehicles on the target road section at a first sampling time;

[0008] obtaining the number of vehicles existing on the target road section at the first sampling time collected by a roadside perception device;

[0009] obtaining a vehicle density coefficient of the target road section based on the number of vehicles and size information of the target road section;

[0010] determining a first passing time of the target road section based on a pre-designed calculation formula, the first vehicle average speed, and the vehicle density coefficient, wherein the pre-designed calculation formula at least includes a first calculation term and a second calculation term, the first calculation term is positively correlated with the vehicle density coefficient of the target road section, and the second calculation term is negatively correlated with the vehicle density coefficient of the target road section.

[0011] Optionally, the method for determining road passing time comprises:

[0012] obtaining a set of average speeds in a preset sampling time period; the preset sampling time period is a predetermined number of sampling time lengths before the first sampling time;

[0013] determining the first vehicle average speed of the target road section at the first sampling time based on the average speed set.

[0014] Optionally, the vehicle density coefficient of the target road section is obtained based on the vehicle number and size information of the target road section, and specifically includes:

[0015] obtaining length information and lane number of the target road section;

[0016] determining an area of the target road section based on the length information and lane information of the target road section;

[0017] determining a vehicle density coefficient reference value according to the area of the target road section;

[0018] the vehicle density coefficient of the target road section is the minimum value between the vehicle density coefficient reference value and 1.

[0019] Optionally, the pre-designed formula is:

[0020]

[0021]

[0022]

[0023] wherein, T1 represents the first passing time, L is the length of the target road section, w is the lane number of the target road section, N is the vehicle number of the target road section, v is the first vehicle average speed of the target road section, v max is the maximum passing speed of the target road section, F is the vehicle density coefficient, k is the vehicle density, and a is the calibration coefficient.

[0024] Optionally, the method further includes:

[0025] determining a second passing time based on a scene event in which the target road section is located; the scene event is used to describe the road attribute of the target road section;

[0026] determining the predicted passing time of the target road section based on the first passing time and the second passing time; the predicted passing time of the target road section is the maximum value of the first passing time and the second passing time.

[0027] Optionally, the second passing time is determined based on the scene event in which the target road section is located, and specifically includes:

[0028] obtaining traffic data of the target road section collected by the roadside perception device;

[0029] determine a scenario event of the target road section based on the traffic data of the target road section;

[0030] determine a second vehicle average speed corresponding to the scenario event based on the scenario event;

[0031] determine the second passing time length based on a length of the target road section and the second vehicle average speed.

[0032] Optionally, when the scenario event of the target road section is multiple, a minimum value of the second vehicle average speeds corresponding to the scenario events is the second vehicle average speed of the target road section.

[0033] Optionally, the determining the scenario event of the target road section based on the traffic data of the target road section specifically includes:

[0034] obtaining an event ID in the traffic data of the target road section;

[0035] determining the scenario event of the target road section according to the event ID.

[0036] The embodiments of the present specification further provide a road passing time length determination device, comprising:

[0037] a first obtaining module configured to obtain a first vehicle average speed of a target road section; the first vehicle average speed is an average value of vehicle instantaneous speeds on the target road section at a first sampling time;

[0038] a second obtaining module configured to obtain a number of vehicles existing on the target road section at a current sampling time collected by a roadside sensing device;

[0039] a vehicle density coefficient determining module configured to obtain a vehicle density coefficient of the target road section based on the number of vehicles and size information of the target road section;

[0040] a first passing time length determining module configured to determine a first passing time length of the target road section based on a preset calculation formula, the first vehicle average speed and the vehicle density coefficient, wherein the preset calculation formula at least includes a first calculation term and a second calculation term, the first calculation term is positively correlated with the vehicle density coefficient of the target road section, and the second calculation term is negatively correlated with the vehicle density coefficient of the target road section.

[0041] The embodiments of the present specification further provide a computer readable medium, and the computer readable instructions can be executed by a processor to implement the road passing time length determination method described above.

[0042] One embodiment of the present specification can at least achieve the following beneficial effects:

[0043] The average value of the instantaneous speed of the vehicle on the target road section is collected, and the average value of the instantaneous speed of the vehicle, the vehicle density coefficient, and a pre-designed calculation formula are used to determine the first passing time of the target road section. Since the instantaneous speed of the vehicle and the vehicle density in the target road section are considered in the calculation of the first passing time, the determination method of the passing time provided in the embodiments of the present specification can more truly reflect the actual driving state of the vehicle on the road, and the accuracy of the passing time prediction is improved. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present specification or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present specification, and other drawings can be obtained by those skilled in the art without creative labor.

[0045] Figure 1 A flowchart of a road passing time determination method provided by an embodiment of the present specification;

[0046] Figure 2 A structural diagram of a road passing time determination device provided by an embodiment of the present specification;

[0047] Figure 3 A structural diagram of a road passing time determination device provided by an embodiment of the present specification. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of one or more embodiments of the present specification more clear, the technical solutions of one or more embodiments of the present specification will be described clearly and completely in combination with the specific embodiments of the present specification and the corresponding drawings. Obviously, the described embodiments are only some embodiments of the present specification, not all embodiments. Based on the embodiments in the present specification, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of one or more embodiments of the present specification.

[0049] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other.

[0050] The technical solutions provided by the embodiments of the present specification will be described in detail below in combination with the drawings.

[0051] Figure 1A flowchart of a method for determining a road travel time according to an embodiment of the present disclosure is shown. From a program perspective, the execution subject of the flowchart can be a program loaded on an application server or an application terminal.

[0052] As shown in Figure 1 the flowchart can include the following steps:

[0053] Step 102: Obtain a first vehicle average speed of a target road section; the first vehicle average speed is an average value of vehicle instantaneous speeds of the target road section at a first sampling time.

[0054] The target road section can be a road with a preset length to be predicted for a travel time, and the preset length can be determined according to the length of the road in an actual situation. The first vehicle is a vehicle traveling on the target road section, and the traffic data of the vehicle is collected by a roadside device to calculate the average speed of the first vehicle.

[0055] Step 104: Obtain a number of vehicles existing on the target road section at the first sampling time collected by a roadside perception device.

[0056] Step 106: Obtain a vehicle density coefficient of the target road section based on the number of vehicles and size information of the target road section.

[0057] The size information of the target road section can include length information of the target road section and a number of lanes of the target road section.

[0058] The obtaining of the vehicle density coefficient of the target road section based on the number of vehicles and the size information of the target road section can specifically include:

[0059] Obtaining length information and a number of lanes of the target road section;

[0060] Determining an area of the target road section based on the length information and the lane information of the target road section;

[0061] Determining a vehicle density coefficient reference value according to the area of the target road section;

[0062] The vehicle density coefficient of the target road section is a minimum value between the vehicle density coefficient reference value and 1.

[0063] In actual implementation, the vehicle density coefficient can be determined by the following formula:

[0064]

[0065]

[0066] wherein k is a vehicle density, a is a calibration parameter, L is a length value of the target road section, and w is a number of lanes of the target road section. is a preset value, which can be determined according to the vehicle density of an actual road, for example, can be set to 30.

[0067] The min function can return the minimum value in the given parameters, that is, the minimum value between the vehicle density coefficient reference value and 1 can be determined through the min function, and the minimum value is taken as the vehicle density coefficient of the target road section.

[0068] The road area of the target road section can be determined based on the size information of the target road section, and the vehicle density coefficient of the target road section is further determined based on the road area of the target road section.

[0069] Step 108: determining the first passing time length of the target road section based on the preset calculation formula, the first vehicle average speed and the vehicle density coefficient, wherein the preset calculation formula at least includes a first calculation item and a second calculation item, the first calculation item is positively correlated with the vehicle density coefficient of the target road section, and the second calculation item is negatively correlated with the vehicle density coefficient of the target road section.

[0070] It should be noted that the first calculation item and the second calculation item can be calculation items related to the vehicle density coefficient, the first calculation item is positively correlated with the vehicle density coefficient of the target road section, which can be understood as that when the vehicle density coefficient becomes larger, the value of the first calculation item also increases; the second calculation item is negatively correlated with the vehicle density coefficient of the target road section, which can be understood as that when the vehicle density coefficient decreases, the value of the second calculation item also decreases.

[0071] Figure 1 The method provided in the method avoids the problem that the running state of the target road section is incorrectly estimated due to directly using the vehicle average speed, by obtaining the average value of the instantaneous speed of the first vehicle of the target road section as the vehicle average speed at the first sampling time; the vehicle density coefficient of the target road section is determined based on the number of vehicles of the target road section and the size information of the target road section, and the first passing time length is determined based on the first vehicle average speed, the vehicle density coefficient and the preset calculation formula. Since the vehicle density coefficient of the target road section and the instantaneous speed of the vehicle are considered, the accuracy of the passing time is improved.

[0072] Based on the method of Figure 1 The embodiments of the present specification also provide some specific implementations of the method, which are described below.

[0073] In order to more accurately describe the first vehicle average speed, in the method for determining road passing time provided by the embodiments of the present specification, the first vehicle average speed of the target road section is obtained, which can specifically include:

[0074] acquire a set of average speeds in a preset sampling time period; the preset sampling time period is a predetermined number of sampling time lengths before the first sampling time;

[0075] determine the first vehicle average speed at the first sampling time based on the set of average speeds.

[0076] In practical applications, the first vehicle average speed can be calculated by the following formula:

[0077]

[0078] wherein, is the average speed at the first sampling time, is the instantaneous speed of the jth vehicle, is the nth vehicle on the target section, : the average vehicle speed collected by the roadside device on the target section, is the sampling time. It can be set in advance. For example, the sampling frequency of the roadside device is 1 Hz, which can be 5, i.e. the instantaneous speed of the vehicle in the previous 5 sampling time lengths at the current sampling time is calculated as the first vehicle average speed. By the above method, the instantaneous speed of the vehicle in multiple sampling times is taken as the first vehicle average speed of the target section, which more truly reflects the driving speed of the vehicle on the target section and improves the accuracy of the calculation of the passing time.

[0079] Optionally, the preset calculation formula can be:

[0080]

[0081]

[0082]

[0083] wherein, T1 represents the first passing time, L is the length of the target section, w is the number of lanes of the target section, N is the number of vehicles on the target section, v is the first vehicle average speed of the target section, v max is the maximum passing speed of the target section, F is the vehicle density coefficient, k is the vehicle density, and a is the calibration coefficient.

[0084] For example, the length of a certain target section is 1 km, there are 40 vehicles in the length of the target section, the number of lanes is 2, the first vehicle average speed of the 40 vehicles is 40 km / h, and the speed limit of the road is 50 km / h. The preset calculation formula can be calculated as follows:

[0085]

[0086] The calculation result is 83.0679 seconds, indicating that the first travel time is 83.0679 seconds.

[0087] In actual application, the target road section can be in various scene events, which can include: accident-prone road section, road danger information, road construction, traffic accident, traffic congestion, etc., wherein the road danger information can specifically include: water accumulation, road icing, snow accumulation, road collapse, bridge collapse, etc. The roadside device can also determine the accident-prone road section by comparing the number or characteristics of traffic accidents in the current road section within a preset time with other positions, and obviously highlighting the road section.

[0088] The roadside device can infer the danger information of the target road section, such as water accumulation, snow accumulation, road icing, etc., by collecting the road surface image of the target road section.

[0089] In order to more accurately describe the travel time of the target road section, the method for determining the road travel time provided by the embodiments of the present specification can further include:

[0090] determining a second travel time based on a scene event in which the target road section is located; the scene event is used to describe the road attribute of the target road section;

[0091] determining a predicted travel time of the target road section based on the first travel time and the second travel time; the predicted travel time of the target road section is the maximum value of the first travel time and the second travel time.

[0092] Optionally, the determining of the second travel time based on the scene event in which the target road section is located specifically includes:

[0093] acquiring traffic data of the target road section collected by the roadside perception device;

[0094] determining the scene event of the target road section based on the traffic data of the target road section;

[0095] determining a second vehicle average speed corresponding to the scene event based on the scene event;

[0096] determining the second travel time based on the length of the target road section and the second vehicle average speed.

[0097] In actual application, the roadside device can collect vehicle traffic data of the target road section, such as vehicle speed information and vehicle latitude and longitude information. The actual position of the target road section can be determined by using the latitude and longitude information of the vehicle, and the scene event of the target road section can be further determined by using the actual position of the target road section.

[0098] Optionally, determining the scenario events of the target road segment based on the traffic data of the target road segment specifically includes:

[0099] Obtain the event ID from the traffic data of the target road segment;

[0100] Based on the event ID, determine the scene event of the target road segment.

[0101] It should be noted that the server can pre-store event IDs corresponding to scene events, as well as a data table of the average speed of the second vehicle corresponding to each event ID. Once the event ID of the target road segment is obtained, the average speed of the second vehicle corresponding to the target road segment can be determined. The event ID can be any combination of letters and numbers.

[0102] For example: when the target road segment is an accident-prone section, the average speed of the second vehicle can be 20 km / h; when the target road segment is a waterlogged section, the average speed of the second vehicle can be 15 km / h; when the target road segment is an icy section, the average speed of the second vehicle can be 5 km / h; when the target road segment is a snow-covered section, the average speed of the second vehicle can be 5 km / h; when the target road segment is a road construction section, the average speed of the second vehicle can be 0 km / h.

[0103] In practical applications, when there are multiple scene events in the target road segment, the minimum value of the second average vehicle speed of the scene event corresponding to the scene event is determined to be the second average vehicle speed of the target road segment.

[0104] For example, when the scene event at the target road segment is both an accident-prone road segment and a snow-covered road segment, since the average speed of the second vehicle corresponding to the snow-covered road segment is less than the average speed of the second vehicle corresponding to the accident-prone road segment, the average speed of the second vehicle at the target road segment is the same as the average speed of the second vehicle corresponding to the snow-covered road segment.

[0105] Based on the same idea, embodiments of this specification also provide apparatus corresponding to the above methods. Figure 2 This is a schematic diagram of a device for measuring road travel time, provided as an embodiment of this specification. Figure 2 As shown, the device may include:

[0106] The first acquisition module 202 is used to acquire the first average vehicle speed of the target road segment; the first average vehicle speed is the average value of the instantaneous speeds of vehicles on the target road segment at the first sampling time;

[0107] The second acquisition module 204 is used to acquire the number of vehicles existing in the target road segment at the current sampling time, as collected by the roadside sensing device.

[0108] The vehicle density coefficient determination module 206 is configured to obtain a vehicle density coefficient of the target road section based on the number of vehicles and size information of the target road section.

[0109] The first passing time determination module 208 is configured to determine a first passing time of the target road section based on a preset calculation formula, the first vehicle average speed, and the vehicle density coefficient, wherein the preset calculation formula comprises at least a first calculation term and a second calculation term, the first calculation term is positively correlated with the vehicle density coefficient of the target road section, and the second calculation term is negatively correlated with the vehicle density coefficient of the target road section.

[0110] It can be understood that each of the above modules refers to a computer program or program segment, and is configured to perform one or more specific functions. In addition, the division of each of the above modules does not mean that the actual program code must also be separated.

[0111] Based on the same idea, the embodiments of the present specification also provide a device corresponding to the above method.

[0112] Figure 3 A structural schematic diagram of a road passing time determination device provided by the embodiments of the present specification is shown in FIG. 3. As shown in FIG. 3, the device 300 can include: Figure 3

[0113] at least one processor 310; and

[0114] a memory 330 in communication connection with the at least one processor; wherein

[0115] the memory 330 stores instructions 320 executable by the at least one processor 310, and the instructions are executed by the at least one processor 310 to enable the at least one processor 310 to:

[0116] obtain a first vehicle average speed of a target road section; the first vehicle average speed is an average value of vehicle instantaneous speeds of the target road section at a first sampling time;

[0117] obtain a number of vehicles existing on the target road section at the first sampling time collected by a roadside perception device;

[0118] obtain a vehicle density coefficient of the target road section based on the number of vehicles and size information of the target road section;

[0119] ​determine a first travel time of the target road section based on a pre-designed formula, the first vehicle average speed and the vehicle density coefficient, wherein the pre-designed formula at least includes a first calculation term and a second calculation term, the first calculation term is positively correlated with the vehicle density coefficient of the target road section, and the second calculation term is negatively correlated with the vehicle density coefficient of the target road section.

[0120] Based on the same idea, the present specification also provides a computer readable medium corresponding to the above method. The computer readable medium stores computer readable instructions, and the computer readable instructions can be executed by a processor to perform the above method for determining the road travel time.

[0121] The above describes specific embodiments of the present specification, and in some cases, the actions or steps recorded in the claims can be executed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0122] Each of the embodiments in the present specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other.

[0123] The device, equipment and method provided by the embodiments of the present specification are corresponding, therefore, the device and equipment also have similar beneficial technical effects as the corresponding method, since the beneficial technical effects of the method have been described in detail above, therefore, the beneficial technical effects of the corresponding device and equipment will not be described here.

[0124] In the 1990s, it was possible to distinguish whether an improvement in a technology was a hardware improvement (e.g., an improvement in the circuit structure of a diode, transistor, switch, etc.) or a software improvement (an improvement in a method flow). However, as technology has advanced, many improvements in method flows today can be considered as direct improvements in hardware circuit structures. Designers almost always obtain a corresponding hardware circuit structure by programming an improved method flow into a hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (e.g., a field programmable gate array (FPGA)) is an integrated circuit whose logic function is determined by user programming of the device. A designer programs a digital system "integrated" on a PLD by himself / herself, without having to ask a chip manufacturer to design and manufacture a special integrated circuit chip. Furthermore, instead of manually manufacturing an integrated circuit chip, this programming is now mostly implemented using "logic compiler" software, which is similar to a software compiler used when developing a program, and the original code before compilation is also written in a specific programming language, which is called a hardware description language (HDL), and there are many types of HDL, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., and the most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also be aware that it is only necessary to logically program a method flow using the above-mentioned hardware description languages and program it into an integrated circuit to easily obtain a hardware circuit that implements the logical method flow.

[0125] The controller can be implemented in any suitable way, for example, the controller can take the form of a microprocessor or processor and a computer readable medium storing computer readable program code, such as software or firmware, executable by the (micro)processor, logic gates, switches, an application specific integrated circuit (ASIC), a programmable logic controller and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320, the memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also know that, in addition to implementing the controller in pure computer readable program code, it is also possible to implement the controller in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers and embedded microcontrollers, etc. to perform the same functions by logically programming the method steps. Such a controller can therefore be considered as a hardware component, and the means included therein for performing various functions can also be considered as structures within the hardware component. Alternatively, the means for performing various functions can even be considered as both a software module implementing the method and a structure within the hardware component.

[0126] The systems, apparatuses, modules or units illustrated by the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0127] For the sake of description, the above apparatuses are described in various units by functions respectively. Of course, the functions of each unit can be implemented in the same or multiple software and / or hardware in implementing the present application.

[0128] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0129] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0130] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0131] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0132] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0133] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory. The memory is an example of computer-readable media.

[0134] Computer-readable media includes permanent and non-permanent, movable and non-movable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0135] It should also be noted that the terms "comprising", "comprising" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0136] Those skilled in the art will appreciate that embodiments of the present application can be provided as a method, system or computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] The present application can be described in the general context of computer-executable instructions, such as program modules, executed by computers. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The present application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices that are connected through a communication network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including storage devices.

[0138] The above merely provides an example of the present application, but is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application should be included in the scope of claims of the present application.

Claims

1. A method for determining road travel time, characterized in that, include: Obtain the average speed of the first vehicle on the target road segment; The first average vehicle speed is the average of the instantaneous vehicle speeds on the target road segment at the first sampling time; The number of vehicles present on the target road segment at the first sampling time is obtained from the data collected by the roadside sensing device; Based on the number of vehicles and the size information of the target road segment, the vehicle density coefficient of the target road segment is obtained; Based on a preset calculation formula, the first average vehicle speed, and the vehicle density coefficient, the first travel time of the target road segment is determined. The preset calculation formula includes at least a first calculation term and a second calculation term. The first calculation term is positively correlated with the vehicle density coefficient of the target road segment, and the second calculation term is negatively correlated with the vehicle density coefficient of the target road segment. The method further includes: A second travel duration is determined based on the scene events in which the target road segment is located; the scene events are used to describe the road attributes of the target road segment. Based on the first travel duration and the second travel duration, the estimated travel duration of the target road segment is determined; the estimated travel duration of the target road segment is the maximum value of the first travel duration and the second travel duration.

2. The method for determining road travel time according to claim 1, characterized in that, The acquisition of the first average vehicle speed of the target road segment specifically includes: Obtain the set of average velocities within a preset sampling time period; the preset sampling time period is a predetermined number of sampling durations prior to the first sampling moment. Based on the set of average speeds, the average speed of the first vehicle at the first sampling time is determined.

3. The method for determining road travel time according to claim 1, characterized in that, The process of obtaining the vehicle density coefficient of the target road segment based on the number of vehicles and the size information of the target road segment specifically includes: Obtain the length and number of lanes of the target road segment; Based on the length and lane information of the target road segment, the area of ​​the target road segment is determined; Based on the area of ​​the target road segment, determine the reference value for the vehicle density coefficient; The vehicle density coefficient of the target road segment is the minimum value between the reference value of the vehicle density coefficient and 1.

4. The method for determining road travel time according to claim 1, characterized in that, The preset calculation formula is: Where T1 represents the first travel time, L is the length of the target road segment, w is the number of lanes in the target road segment, N is the number of vehicles in the target road segment, and v is the first average vehicle speed in the target road segment. max The maximum traffic speed of the target road segment is denoted as F, where F is the vehicle density coefficient, k is the vehicle density, and α is the calibration coefficient.

5. The method for determining road travel time according to claim 1, characterized in that, The determination of the second travel duration based on the scene events of the target road segment specifically includes: Acquire traffic data of the target road segment collected by the roadside sensing device; Based on the traffic data of the target road segment, determine the scene events of the target road segment; Based on the scene event, determine the average speed of the second vehicle corresponding to the scene event; The second travel time is determined based on the length of the target road segment and the average speed of the second vehicle.

6. The method for determining road travel time according to claim 5, characterized in that, When there are multiple scene events in the target road segment, the minimum value of the second average vehicle speed of the scene event corresponding to the scene event is determined to be the second average vehicle speed of the target road segment.

7. The method for determining road travel time according to claim 5, characterized in that, The determination of the scenario events for the target road segment based on the traffic data of the target road segment specifically includes: Obtain the event ID from the traffic data of the target road segment; Based on the event ID, determine the scene event of the target road segment.

8. A device for determining road travel time, characterized in that, include: The first acquisition module is used to acquire the first average vehicle speed of the target road segment; the first average vehicle speed is the average of the instantaneous speeds of vehicles on the target road segment at the first sampling time; The second acquisition module is used to acquire the number of vehicles existing in the target road segment at the current sampling time, as collected by the roadside sensing device. The vehicle density coefficient determination module is used to obtain the vehicle density coefficient of the target road segment based on the number of vehicles and the size information of the target road segment; The first travel duration determination module is used to determine the first travel duration of the target road segment based on a preset calculation formula, the first average vehicle speed, and the vehicle density coefficient. The preset calculation formula includes at least a first calculation term and a second calculation term. The first calculation term is positively correlated with the vehicle density coefficient of the target road segment, and the second calculation term is negatively correlated with the vehicle density coefficient of the target road segment. The device is also used for: A second travel duration is determined based on the scene events in which the target road segment is located; the scene events are used to describe the road attributes of the target road segment. Based on the first travel duration and the second travel duration, the estimated travel duration of the target road segment is determined; The estimated travel time for the target road segment is the maximum of the first travel time and the second travel time.

9. A computer-readable medium having computer-readable instructions stored thereon, characterized in that, The computer-readable instructions can be executed by a processor to implement the method for determining road travel time as described in any one of claims 1 to 7.

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