Understanding Road Signs

Abstract

A device, service, system and method for estimating traffic instructions at a first area (220), the method comprising the following steps: (S1) detecting the position and / or movement of at least one vehicle (201) and / or vehicle user (301) in the first area (220) or in a second area (221) associated with a corresponding traffic instruction of the first area (220); (S2) determining a behavior pattern based on the detected position and / or movement of the at least one vehicle (201) and / or vehicle user (301); and, (S3) estimating the traffic instructions of the first area (220) based on the determined behavior pattern.

Description

Technical Field

[0001] The present disclosure generally relates to the field of road signs indicating traffic instructions at an area. More specifically, the present disclosure relates to predicting or estimating traffic instructions at an area. Background Art

[0002] The purpose of a road sign may generally be to inform or inform vehicle users of traffic rules or traffic instructions in an area. A road sign is generally a picture describing the instructions valid for that area, and vehicle users learn the meaning of road signs when obtaining a driver's license, etc.

[0003] Understanding the traffic instructions of foreign road signs can be difficult, and this is even more difficult if the road signs include text in a foreign language that the user does not understand. In some cases, understanding the instructions of a combination of road signs can also be difficult. Prior art traffic sign assistance systems focus on translating the text recognized on the road signs and translating the meaning of the text on the road signs. Even the most advanced traffic sign assistance systems have problems interpreting the instructions of road signs unless the user or the system understands the language in which the text is written.

[0004] Understanding traffic instructions in combination with road signs is even more difficult.

[0005] Therefore, in areas where vehicle drivers are not familiar with given road signs and instructions, an alternative approach is needed to assist drivers in understanding traffic rules or instructions by predicting or estimating traffic instructions from road signs. Summary of the invention

[0006] It should be emphasized that when used in this specification, the term "comprising / including..." is used to indicate the presence of the described features, integral bodies, steps, or components, but does not exclude the presence or addition of one or more other features, integral bodies, steps, components, or combinations thereof. As used herein, the singular forms "a", "an", and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0007] Generally speaking, the apparatus mentioned in this article should be understood as a physical product, such as a device. The physical product may include one or more components, such as a control circuit in the form of one or more processors, one or more controllers, etc.

[0008] Some embodiments aim to provide an alternative to traffic directives / regulations in effect for an area.

[0009] Some embodiments aim to provide an alternative way to understand instructions on road signs to understand traffic instructions / regulations in force for an area.

[0010] According to a first aspect, this object is achieved by a method for estimating a traffic directive at a first area.

[0011] The method comprises detecting the position and / or movement of at least one vehicle and / or vehicle user in a first area or in a second area associated with a corresponding traffic directive for the first area.

[0012] The method further comprises determining a behavior pattern based on the detected position and / or movement of at least one vehicle and / or a vehicle user.

[0013] The method also includes estimating a traffic directive for the first area based on the determined behavior pattern.

[0014] An advantage of some embodiments is that an alternative way of understanding traffic instructions for a first area is provided.

[0015] An advantage of some embodiments is that traffic instructions derived from crowd information can be used to estimate traffic instructions from different areas (i.e., the first area and the second area) with the same traffic instructions. The advantage of this is that if there is another area with a corresponding traffic instruction, then a traffic instruction for an area with a small amount / number of moving vehicles and / or vehicle users can be estimated.

[0016] Another advantage of some embodiments is that the estimation of traffic instructions for the area is based on how actual vehicles and people move in the first area and / or the second area, rather than an interpretation or translation of road signs.

[0017] Yet another advantage of some embodiments is that an estimate of traffic instructions is provided even for environments with road signs that do not give any meaning even if the text itself is interpreted or translated into an understandable language.Some road signs are difficult to understand because they are local signs.

[0018] Yet another advantage of some embodiments is that a method is provided that does not depend on translating the text of road signs.

[0019] Corresponding traffic instructions refer to similar or identical traffic instructions that are valid for different areas (ie, the first area and the second area). The relationship between the first area and the second area is that they have corresponding traffic instructions (even if the actual meaning of the traffic instructions is actually unknown).

[0020] According to one aspect, the method includes the step of receiving estimated traffic instructions for the first area in another vehicle entering the first area. The advantage of this is that the vehicle user entering the first area obtains information related to the traffic instructions for the first area without having to understand the road signs at the first area.

[0021] According to one aspect, the detecting step comprises scanning the first area and / or the second area by means of one or more sensors.

[0022] According to one aspect, the scanning step further comprises scanning the first area by onboard sensors of the vehicle and / or another vehicle and / or sensors installed at the first area and / or the second area. An advantage of this aspect is that sensors of the vehicle or another vehicle (such as LIDAR and other sensors) that continuously scan the vehicle's surroundings are used to collect scanning information at the first area and / or the second area. Another advantage of this aspect is that sensors (such as cameras) located at intersections or parking places can be used to collect scanning information at the first area and / or the second area. According to one aspect, the onboard sensors of the vehicle and / or another vehicle are connected to the cloud via the vehicle's connection device, that is, the onboard sensors are cloud-connected sensors.

[0023] According to one aspect, the first area and / or the second area is one or more of a parking area, an intersection, a road section, a city or a part of a city. According to one aspect, the area is an area corresponding to an area where road signs are used to define traffic instructions.

[0024] According to one aspect, the determination step comprises analyzing in the cloud a detected position and / or movement of at least one vehicle and / or a vehicle user.

[0025] According to one aspect, the step of estimating traffic instructions for the first area comprises a step of analyzing the determined behavior patterns in the cloud.

[0026] The advantage of determining and analyzing information in the cloud is the ability to process large amounts of information without having to do the processing on board each vehicle.

[0027] According to one aspect, the method further comprises detecting one or more of road signs, roads, traffic lanes, markings on the roads, and the step S3 of estimating the traffic instruction is also based on the detected one or more road signs, roads, traffic lanes on the roads and / or signs. An advantage of this aspect is that this information provides more data for identifying the pattern of the area. Another advantage is that this estimation can focus on a specific type of traffic instruction, that is, if the type of stop sign is detected, a stop instruction can be estimated, and if a traffic lane or sign with an arrow is detected on the road, a direction instruction can be estimated. By focusing on the specific type of traffic instruction, the traffic instruction can be estimated based on fewer inputs of a determined behavior pattern, and the estimated traffic instruction is still reliable.

[0028] According to one aspect, the detected movement includes information related to one or more of the time, date, speed of the vehicle and / or vehicle user, location of the vehicle and / or vehicle user, number of vehicles, type of vehicle, and direction of the vehicle and / or vehicle user. An advantage of this aspect is that this information provides more data for identifying the pattern of the area. By detecting the type of vehicle and vehicle user, more features can be identified and more traffic instructions can be estimated.

[0029] According to one aspect, the method further comprises the step of displaying in another vehicle the estimated traffic instructions for the first area. An advantage of some aspects is that in this way, the driving of the vehicle can be adjusted according to the estimated traffic instructions for the area without requiring the understanding of any road signs.

[0030] According to one aspect, the method further comprises the step of receiving, in an autonomous driving system of another vehicle, an estimated traffic directive for the first area.

[0031] According to one aspect, the estimated traffic instructions for the first area include one or more instructions of recommended speed, driving direction, parking instructions, non-driving direction, maximum height, allowed tire type, maximum weight, bridge tunnel, pedestrian street, bus lane, carpool lane, no-passing zone, toll, speed camera, and specific rules for specific lanes to assist the user of the other vehicle or the autonomous driving system to comply with the traffic instructions for the first area.

[0032] According to one aspect, the method further comprises the step of identifying a first indication or indicator of traffic instructions associated with the first area. According to one aspect, the first indication or indicator of traffic instructions associated with the first area is one or more of a road sign and / or a sign on and / or at the road at the first area. The first indicator refers to something that the driver can see when driving the vehicle, such as a sign or text, in order to obtain traffic instructions for the area. According to one aspect, the first indicator is a combination of a road sign and / or a sign on and / or at the road at the first area.

[0033] According to one aspect, the method further comprises the step of identifying a second indication or indicator of the traffic directive associated with the second area. According to one aspect, the method further comprises comparing the first indication or indicator of the traffic directive associated with the first area with the second indication or indicator of the traffic directive associated with the second area to determine that the first area and the second area have corresponding traffic directives.

[0034] According to one aspect, the method further comprises the step of identifying the second area by comparing a first indication or indicator of a traffic directive associated with the first area with a second indication or indicator of a traffic directive associated with the second area.

[0035] According to one aspect, the step of identifying the first indication comprises identifying one or more road signs and / or signs on and / or at the road at the first area.

[0036] According to one aspect, the method further includes comparing the first indication with a second indication of a traffic directive associated with the second area to determine whether the first indication and the second indication indicate corresponding traffic directives.

[0037] According to one aspect, the scanning of the area includes scanning one or more of parked vehicles, roads, traffic lanes, pedestrian traffic, and traffic flows in the first area and / or the second area. An advantage of this aspect is that this information provides data for training the modeling of traffic conditions and competing traffic flows in the process of identifying behavioral patterns to estimate the significance of many different types of traffic instructions at the first area and / or the second area.

[0038] According to one aspect, the detection and / or scanning includes any one of detecting and / or scanning when the vehicle approaches or enters the first area and / or the second area, when the vehicle passes through the first area and / or the second area, and when the vehicle has passed through the first area and / or the second area.

[0039] An advantage of some embodiments is that detection and / or scanning provides data at different points in time and at different locations in the first area and / or the second area for further training of modeling of traffic instructions, traffic conditions and competing traffic flows, and identifying (multiple) behavioral patterns.

[0040] According to one aspect, the method further comprises sending a continuous stream of detected and / or scanned information to the cloud in response to the detection and / or scanning of the first area and / or the second area.

[0041] An advantage in some aspects is that this continuous information provides an uninterrupted data stream for more accurately training traffic instructions at the first area, as well as modeling / estimation of traffic conditions and competing traffic flows at the first area and / or the second area.

[0042] According to one aspect, the estimated traffic instructions for the first area include one or more instructions of recommended speed, driving direction, parking instructions, non-driving direction, maximum height, maximum weight, bridge tunnel, pedestrian street, bus lane, carpool lane, no-passing zone, toll, speed camera, and specific rules for specific lanes to assist vehicle users in complying with the traffic instructions for the first area.

[0043] An advantage in some aspects is that the driving of the other vehicle can be adapted to the traffic instructions of the first area and thus comply with the traffic instructions in the first area.

[0044] According to one aspect, the method comprises analyzing road sign information in the cloud, and wherein the step of estimating a traffic directive for the first area is also based on analyzing the road sign information. An advantage of some aspects is that the estimate of the traffic directive may be a combination of data from detection and / or scanning and road signs to even further improve the accuracy of the estimate of the traffic directive for the area.

[0045] A second aspect is a computer program product comprising a non-transitory computer readable medium having a computer program comprising program instructions on the non-transitory computer readable medium. The computer program can be loaded into a data processing unit and is configured to cause the method according to the first aspect to be performed when the computer program is run by the data processing unit.

[0046] A third aspect is an apparatus for estimating traffic instructions at the area.

[0047] The device includes a memory having executable instructions, and one or more processors configured to communicate with the memory.

[0048] The one or more processors are configured to cause the device to detect the location and / or movement of at least one vehicle and / or vehicle user in the first area or in the second area associated with a corresponding traffic directive for the first area.

[0049] The one or more processors are further configured to cause the device to determine a behavior pattern based on the detected location and / or movement of at least one vehicle and / or vehicle user, and to estimate traffic instructions for the first area based on the determined behavior pattern.

[0050] An advantage of some embodiments and aspects is that an alternative way of understanding traffic instructions in a first area is provided.

[0051] Another advantage of some embodiments is that the estimation of the traffic directive for the first area is based on how actual vehicles and people move in the first area and / or the second area.

[0052] Yet another advantage of some embodiments is that estimated traffic instructions are provided even for first areas with road signs that do not give any meaning even if the text itself is translated into an understandable language.Some road signs are difficult to understand because they are local signs.

[0053] Yet another advantage of some embodiments is that a method is provided that does not rely on textual translation of road signs.

[0054] According to one aspect, the one or more processors are also configured to enable the device to further receive recommended speeds, driving directions, parking instructions, non-driving directions, maximum heights, maximum weights, bridge tunnels, pedestrian streets, bus lanes, carpool lanes, no-passing zones, tolls, speed cameras, and specific rules for specific lanes to assist vehicle users in complying with traffic instructions in the first area.

[0055] A fourth aspect is a vehicle comprising the apparatus of the third aspect.

[0056] An advantage of some embodiments is that alternative ways of understanding traffic instructions at an area are provided.

[0057] A fifth aspect is a cloud service for estimating traffic instructions at the area.

[0058] The cloud service includes: a control circuit configured to receive a detected position and / or movement of at least one vehicle and / or vehicle user in a first area and / or a second area associated with a corresponding traffic directive for the first area; determine a behavior pattern based on the detected position and / or movement of at least one vehicle and / or vehicle user; and estimate the traffic directive for the first area based on the determined behavior pattern. An advantage of some embodiments is that an alternative way of understanding traffic directives for an area is provided.

[0059] Another advantage of some embodiments is that the estimation of traffic instructions for the area is based on how actual vehicles and people move in the area, rather than on interpretations of road signs.

[0060] Yet another advantage of some embodiments is that estimated traffic instructions are provided even for first areas with road signs that do not give any meaning even if the text itself is translated into an understandable language.Some road signs are difficult to understand because they are local signs.

[0061] Yet another advantage of some embodiments is that a method is provided that does not rely on textual translation of road signs.

[0062] According to one aspect, the control circuit of the cloud service is also configured to provide recommended speeds, driving directions, parking instructions, non-driving directions, maximum heights, maximum weights, bridge tunnels, pedestrian streets, bus lanes, carpool lanes, no-passing zones, tolls, speeding cameras, and specific rules for specific lanes to the user of the vehicle or the autonomous vehicle to assist in complying with traffic instructions in the first area.

[0063] A sixth aspect is a system for estimating a traffic directive for a first area.

[0064] The system includes: a scanning module configured to scan a first area and / or a second area; a transmitting module configured to send a continuous stream of scanning information; an analyzing module configured to analyze the scanning information; an estimating module configured to predict traffic instructions at the first area based on the analysis of the scanning information; a receiving module configured to receive estimated instructions for the first area; and a display module configured to display the estimated traffic instructions for the first area.

[0065] An advantage of some embodiments is that an alternative way of understanding first area traffic instructions is provided.

[0066] Another advantage of some embodiments is that the estimation of the traffic directive for the first area is based on how actual vehicles and people move in the first area and / or the second area.

[0067] Yet another advantage of some embodiments is that estimated traffic instructions are provided even for first areas with road signs that do not give any meaning even if the text itself is translated into an understandable language.Some road signs are difficult to understand because they are local signs.

[0068] Yet another advantage of some embodiments is that a method is provided that does not rely on textual translation of road signs.

[0069] According to one aspect, the receiving module is further configured to receive one or more of a recommended speed, a driving direction, a parking instruction, and a non-driving direction to assist a user of the vehicle in complying with traffic regulations.

[0070] In some embodiments, any of the above aspects may also have features that are the same as or corresponding to any of the various features described above for any of the other aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] More objects, features and advantages will become apparent from the following detailed description of embodiments with reference to the accompanying drawings, which are not necessarily drawn to scale, emphasis instead being placed on depicting exemplary embodiments.

[0072] Figure 1 is a flow chart illustrating exemplary method steps according to some embodiments and aspects.

[0073] Figure 2 is a schematic overview diagram illustrating an exemplary system according to one aspect;

[0074] Figure 3a is a schematic diagram showing an example of a first region and a second region according to one aspect;

[0075] Figure 3b is a schematic diagram showing an example of a first region and a second region according to one aspect;

[0076] Figure 4 is a schematic block diagram illustrating an exemplary arrangement according to one aspect; and

[0077] Figure 5 is a schematic diagram illustrating an exemplary computer-readable medium according to one aspect;

[0078] Figure 6 is a flow chart illustrating exemplary steps of a cloud service according to some embodiments and aspects. DETAILED DESCRIPTION

[0079] As mentioned above, it should be emphasized that when used in this specification, the term "comprising / including..." is used to indicate the presence of the described features, integrals, steps, or components, but does not exclude the presence or addition of one or more other features, integrals, steps, components, or combinations thereof. As used herein, the singular forms "a", "an", and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0080] Embodiments and aspects of the present disclosure will be described and exemplified more fully below with reference to the accompanying drawings. However, the solutions disclosed herein may be implemented in many different forms and should not be construed as being limited to the embodiments set forth herein.

[0081] Hereinafter, embodiments and aspects will be described that provide alternative ways to interpret, predict or estimate traffic directives for an area. In addition, some embodiments and aspects will be described in which, in alternative ways, traffic directives for an area are interpreted, predicted or estimated based on analyzing the movement of vehicles and personnel in the area or in areas with the same or similar traffic directives.

[0082] Figure 1 1 is a flow chart showing exemplary method steps according to one aspect. Method 100 is a method for estimating a traffic instruction at a first area 220. Thus, for example, Figure 2 Method 100 is performed by a system 200 for estimating a traffic directive for a first area 220. Estimation refers to determining, predicting, understanding (i.e., attempting to understand) a rule or traffic directive for the area. According to one aspect, the first area is one or more of a parking area, an intersection, a road section, a city, or a portion of a city. According to one aspect, the area is a first area corresponding to an area for which road signs are used to define traffic directives. According to one aspect, the first area is an area corresponding to an area for which a particular traffic directive is valid.

[0083] The method 100 for estimating instructions for the area 220 includes the following steps.

[0084] S1 detects the position and / or movement of at least one vehicle 201 and / or vehicle user 301 in the first area 220 or in the second area 221 associated with the corresponding traffic instruction of the first area 220. According to one aspect, the position refers to the location or position of at least one vehicle 201 within the first area 220 or the second area 221, and / or the time when the vehicle has been at the position. According to one aspect, the position refers to the place or location of at least one vehicle user 301 within the first area 220 or the second area 221, and / or the time when the user has been located at the position. The vehicle user 301 refers to a person who is associated with the vehicle in some way, which can be a driver or a passenger. According to one aspect, the movement refers to the direction, speed and / or distance that at least one vehicle 201 moves within the first area 220 or the second area 221. According to one aspect, S1 detection includes detecting the type of vehicle.

[0085] The first area 220 is an area whose traffic directive should be estimated. The second area 221 is another area having the same / similar / corresponding traffic directive as the first area 220. The second area 221 may be located at a certain distance from the first area 221 and may be far away from the first area 221. According to one aspect, the first area 220 or the second area 221 is a parking area, a block, a strip with a certain radius, a street, a part of a city, or a city. According to one aspect, the first area 220 or the second area 221 is different for different traffic directives.

[0086] According to one aspect, the step of detecting S1 includes: S11 scanning the first area 220 and / or the second area 221 by one or more sensors 230. According to one aspect, the scanning S11 also includes scanning S11 the first area 220 by a vehicle-mounted sensor 230 of the vehicle 201 and / or a sensor 230 installed at the first area 220 and / or the second area 221.

[0087] According to one aspect, vehicle 201 is capable of vehicle-to-cloud (V2C) communications. V2C technology enables information of the vehicle and another vehicle 202 or information obtained by vehicle 201 to be exchanged with a cloud system or cloud service 401. This allows another vehicle 202 to utilize information from vehicle 201, which is also capable of V2C communications, through a public cloud system or cloud service.

[0088] The onboard sensors 230 may include detectors, cameras, 360-degree radars, LIDARs, ultrasonic sensors, or any other vehicle-compatible sensors for obtaining information about the environment near the vehicle 201 .

[0089] Additionally, vehicle 201 and / or another vehicle 202 may include an Internet connection, an advanced driver assistance system, and / or high definition maps for more accurate object detection and positioning.

[0090] According to one aspect, the sensor 230 is a sensor 230 installed at the first area 220 and / or the second area 221. According to one aspect, the sensor 230 is a cloud-connected sensor 230. According to one aspect, the sensor 230 is a camera fixedly connected at the first area 220 and / or the second area 221. According to one aspect, the sensor 230 is a camera located at the first area 220 and / or the second area 221, which is an intersection and / or a parking area. For example, the sensor 230 may be a surveillance camera at a parking area or a sensor at a building in the area 220. The sensor 230 at the first area and / or the second area may include a detector, a camera, a 360-degree radar, an ultrasonic sensor, or any other sensor for obtaining information about the environment near the first area and / or the second area.

[0091] According to one aspect, the detected movement includes information related to one or more of time, date, speed of vehicles and / or vehicle users, location of vehicles and / or vehicle users, number of vehicles, type of vehicles, and direction of vehicles and / or vehicle users.

[0092] According to one aspect, the detected movement includes information regarding one or more of a width, a height, a type, a make, and a tire type of the vehicle.

[0093] In step S2 , a behavior pattern is determined S2 based on the detected position and / or movement of at least one vehicle 201 and / or vehicle user 301 .

[0094] According to one aspect, the determining step S2 can be performed by big data analysis. Generally, big data analysis is a complex process of examining large and diverse data sets (i.e., big data) to discover information containing hidden patterns, unknown correlations, trends, and preferences to make informed decisions or predictions. According to one aspect, such big data analysis is performed in a scalable cloud system or cloud service.

[0095] In one aspect, the step S2 of determining a behavior pattern based on the detected position and / or movement of at least one vehicle 201 and / or vehicle user 301 is determined by a software analysis pattern in software engineering, which is a conceptual model that embodies an abstract concept of a situation often encountered in modeling. A behavior pattern can be represented as a set of related generic objects (e.g., metaclasses) that have typical attributes (e.g., data definitions), behaviors (e.g., method signatures), and expected interactions defined in a domain-neutral manner. By determining and analyzing the behavior pattern in the detected information, the pattern can be identified and traffic instructions can be estimated based on the identified pattern.

[0096] According to one aspect, the position of the vehicle refers to the relative position between the vehicles 201. According to one aspect, the position of the vehicle refers to the position of the vehicle on the road. According to one aspect, the position of the vehicle refers to the position of the vehicle at a parking spot or parking area. According to one aspect, the type of the vehicle is the size of the vehicle. By knowing the size of the vehicle, the type of the vehicle can be identified as a bicycle, motorcycle, car, bus, moped, snowmobile and / or truck. According to one aspect, the type of the vehicle is a vehicle function such as a taxi, ambulance, police car, postal vehicle or freight vehicle. The second area 221 is used to detect more movements for traffic instructions so that more data can be used for the determination step S2. By having more available data, the determination S2 of the behavior data can be more accurate, and the behavior data can also be determined for areas (i.e., the first area 220) where sufficient data has not yet been detected to determine the behavior pattern.

[0097] In step S3 , traffic instructions for first area 220 are estimated based on the determined behavior pattern determined in step S2 .

[0098] In step S4, the estimated traffic instructions of the first area 220 are received in the other vehicle 202. According to one aspect, the reception can be performed by a receiving circuit configured for a V2C included in the other vehicle. According to one aspect, when the other vehicle 202 enters or approaches the first area 220, the other vehicle 202 receives the traffic instructions of the first area 220, so that the autonomous driving system or the driver of the other vehicle 202 obtains / receives the information of the estimated traffic instructions and can comply with them. According to one aspect, the vehicle 201 is located in the first area 220 or the second area 221 and detects a moving vehicle. According to one aspect, the other vehicle 202 is a vehicle that should use the estimated traffic instructions. According to one aspect, the other vehicle 202 is the vehicle 201.

[0099] In some embodiments and aspects, the method 100 of instructions for estimating a region further includes the following steps.

[0100] According to one aspect, the determining step S2 comprises: S21 analyzing the detected position and / or movement of at least one vehicle 201 and / or vehicle user 301 in the cloud 401. By analyzing the information in the cloud 401, the information can be collected and analyzed in an efficient manner, and each vehicle does not need to have data capabilities to perform the analysis.

[0101] According to one aspect, the step S3 of estimating traffic directives for the first area 220 comprises a step S31 of analyzing the determined behavior patterns in the cloud 401. By analyzing the information in the cloud 401, the information may be collected and analyzed in an efficient manner and each vehicle does not need to have data capabilities to perform the analysis.

[0102] According to one aspect, the vehicle 201 is a vehicle that is positioned in the first area 220 or the second area 221 and detects movement. According to one aspect, the other vehicle 202 is a vehicle that should use the estimated traffic directive.

[0103] In some embodiments and aspects, the method 100 of instructions for estimating a region further includes the following steps.

[0104] Detect S5 one or more of road signs, roads, traffic lanes, markings on the road, and the step S3 of estimating traffic instructions is also based on the detected one or more road signs, roads, traffic lanes on the road and / or signs. When estimating S3 traffic instructions, the detected additional information is used as further input. This can reduce the time or required data capacity for estimation. For example, if road signs are identified as something related to parking instructions, then the estimation S3 can focus this estimation on vehicles stationary in the first area and / or the second area and vehicle users going to or leaving their vehicles. In another example, if road signs are identified as being related to instructions on how a vehicle can move, then the estimation S3 can focus on the behavior patterns of moving vehicles.

[0105] The information of the road sign can be used as an input in the analysis of the instructions at the area. If the road sign is identified as traffic information related to the parking information of the area, the estimation step S3 can start and focus on when the vehicle is parked in the area and how long it is parked, and spend less analysis capabilities on the speed and direction of the vehicle in the area. However, if the road sign is identified as traffic information related to the speed and direction of the vehicle allowed to travel, the estimation S3 can start and focus on the speed and direction of the vehicle in the first area 220 and / or the second area 221, and spend less analysis capabilities on the vehicles parked in the first area 220 and / or the second area 221. This can make the estimation S3 more efficient. This can also be used in area 220, where for area 220, the cloud 401 has not received enough information to fully analyze the first area 220 and / or the second area 221.

[0106] According to one aspect, the method 100 comprises a further step S6 of displaying the estimated traffic directive for the first area 220 in the further vehicle 202 .

[0107] According to one aspect, the method 100 comprises a further step S7 of receiving, in the autonomous driving system of the further vehicle 202 , estimated traffic directives for the first area 220 .

[0108] According to one aspect, the estimated traffic instructions for the first area 220 include one or more instructions of recommended speed, driving direction, parking instructions, non-driving direction, allowed tire type, maximum height, maximum weight, bridge tunnel, pedestrian street, lane for autonomous driving vehicles, bus lane, carpool lane, no-passing zone, toll, speed camera, and specific rules for specific lanes to assist vehicle users or autonomous driving systems to comply with the traffic instructions of the first area 220.

[0109] According to one aspect, the method 100 comprises a further step S8 of identifying a first indication / indicator of a traffic directive associated with the first area 220. According to one aspect, the step S8 of identifying the first indication comprises identifying one or more road signs and / or signs on and / or at the road at the first area 220.

[0110] According to one aspect, the method 100 comprises a further step S9 of comparing the first indication with a second indication of a traffic directive associated with the second area 221 to determine S10 whether the first indication and the second indication indicate corresponding traffic directives. According to one aspect, the first indication is one or more road signs and / or signs on and / or at the road at the first area 220. According to one aspect, the second indication is one or more road signs and / or signs on and / or at the road at the second area 221.

[0111] According to one aspect, in response to step S2 of detecting an area, a continuous stream of detected positions and / or movements of at least one vehicle 201 and / or vehicle user 301 is sent to the cloud 401. The continuous stream of detected information may form part of big data to be analyzed by the cloud service.

[0112] According to one aspect, the displaying step S6 is accomplished by displaying the traffic instructions on a dashboard, a head-up display, or a human-machine interface in the vehicle.

[0113] According to one aspect, the detection S1 of the movement and / or position of the vehicle user includes detecting information of a pedestrian flow in the first area 220 and / or the second area 221 .

[0114] In one aspect, step S11 of scanning the first area 220 by the on-board sensor 230 of the vehicle 201 and / or another vehicle 202 passing through the area 220 includes any one of scanning when the vehicle 201 and / or another vehicle approaches or enters the first area 220, when the vehicle travels through the first area 220, and when the vehicle leaves the first area 220.

[0115] According to one aspect, an example of a traffic instruction may be: parking on the road is allowed from 8:00 to 20:00 on weekdays and there is a parking fee. Another example of a traffic instruction is: the speed limit is 80 km / h and parking is not allowed on weekends.

[0116] According to one aspect, the behavior pattern of the first area 220 and / or the second area 221 of the road is that the average speed of vehicles on the road is 83 km / h, and an estimate based on this may be that the traffic instruction for the road (the traffic instruction for the first area 220 and / or the second area 221) is that the speed limit in the first area 220 is 80 km / h.

[0117] According to one aspect, the behavior pattern of the first area 220 of parking spaces is that the average time from parking to locking of vehicles in the area is more than 3 minutes, and almost no vehicles are stationary for more than 2 hours. The estimation of the traffic instructions for parking spaces in the area 220 is based on this pattern and may be: the parking time allowed is 2 hours and there is a parking fee.

[0118] According to one aspect, a behavior pattern is that almost only taxis travel in the first area 220 and / or the second area 221 on weekends. An estimation of the traffic instructions for the first area 220 or the second area 221 based on the behavior pattern may be that only taxis are allowed on the road on weekends.

[0119] According to one aspect, an estimated traffic instruction is any instruction disclosed or likely to be disclosed on road sign 305 .

[0120] Figure 2 2 is a schematic overview diagram illustrating an exemplary system according to some aspects and embodiments. The system 200 is used to estimate traffic instructions at a first area 220. Thus, the system 200 can be used, for example, to Figure 3a The first area 220 of the environment 300a and / or Figure 3b The first area 220 of the environment 300b.

[0121] The vehicle 201 includes an apparatus for estimating a traffic directive for a first area 220. The apparatus includes a memory having executable instructions, wherein one or more processors are configured to communicate with the memory.

[0122] The one or more processors are configured to cause the device to: S1 detect a position and / or movement of at least one vehicle 201 and / or vehicle user 301 in the first area 220 or in the second area 221 associated with a corresponding traffic directive of the first area 220 .

[0123] The one or more processors are further configured to cause the device: S2 to determine a behavior pattern based on the detected position and / or movement of at least one vehicle 201 and / or vehicle user 301 .

[0124] The one or more processors are further configured to cause the device to: S3 estimate a traffic instruction for the first area 220 based on the determined behavior pattern.

[0125] Vehicle 201 uses onboard sensors to scan (i.e., detect) the environment near vehicle 201, such as lane markings, other lanes or other vehicles in the same lane, pedestrians, cyclists, road signs 305, intersections, traffic lights and their current status. The onboard sensors may include, for example, detectors, cameras, 360-degree radars, LIDARs, ultrasonic sensors, or any other vehicle-compatible sensors that are used to obtain information about the environment near the vehicle.

[0126] According to one aspect, vehicle 201 includes cloud or internet connectivity, advanced driver assistance systems, and high-definition maps for more accurate object detection and localization.

[0127] According to one aspect, as described above, the vehicle 201 sends a continuous stream of detected positions and / or movements of at least one vehicle 201 and / or vehicle user 301 in the first area 220 or the second area 221 obtained by onboard sensors to the cloud 401 for determination and estimation.

[0128] The sensor 230 installed at the area scans (i.e., detects) the environment near the first area 220 and / or the second area 221, such as lane markings, vehicles in different lanes, pedestrians, cyclists, road signs 305, intersections, traffic lights, and their current states. The sensor 230 may include, for example, a detector, a camera, a 360-degree radar, an ultrasonic sensor, or any other compatible sensor for obtaining information about the environment near the area.

[0129] The sensors 230 at the first area 220 and / or the second area 221 may send a continuous stream of information obtained by the sensors as described above to the cloud 401 for determination and estimation.

[0130] According to one aspect, cloud 401 includes at least one cloud database 404 and / or at least one server database 403, which are typically databases running on a cloud computing platform and access to which is provided as a service. Database services can provide scalability and high availability of databases. Cloud 401 can be included in a single cloud service 401 or multiple associated cloud services 401.

[0131] In the cloud 401, a machine learning algorithm creates a model capable of estimating traffic instructions (e.g., instructions) for the area based on input parameters, namely, the location and / or movement of at least one vehicle 201 and / or vehicle user 301 detected in the first area 220 or the second area 221, such as where and how many other vehicles are detected relative to the vehicle 201, which vehicles are currently traveling and at what speed and direction, road signs, vehicle type, time between parking and locking, time of day, pedestrians at the crosswalk (waiting or walking) and how many pedestrians there are, etc.

[0132] Then, the cloud 401 may provide the estimated traffic instructions of the first area 220 to the vehicle 201 or another vehicle 202 approaching or entering the first area 220, so that the other vehicle 202 can adjust to comply with the traffic instructions of the first area 220. According to one aspect, the traffic instructions may be any traffic instructions disclosed by road signs. According to one aspect, the instructions are one or more of speed limits, driving directions, parking instructions, non-driving directions, maximum heights, maximum weights, bridge tunnels, maximum parking times, environmental zones, permitted tire types, pedestrian streets, bus lanes, carpool lanes, no-passing areas, tolls, speed cameras, and specific rules for specific lanes to assist vehicle users in complying with traffic regulations. According to one aspect, the instructions may be any instructions that are valid for the first area 220 and can be identified by analyzing the position and / or movement of at least one vehicle 201 and / or vehicle user 301 in the first area 220 or the second area 221.

[0133] The cloud 401 receives a continuous stream of information 206 of the detected environment (eg, the first area 220 and / or the second area 221 ) obtained from onboard sensors of the vehicle 201 and / or from sensors 230 at the first area 220 and / or the second area 221 .

[0134] In response to receiving the detected position and / or movement information stream, the cloud 401 analyzes the scan information. The cloud 401 predicts / estimates the traffic instructions for the first area 220 based on the determined behavior patterns of the detected information in the first area 220 and / or the second area 221. The cloud 401 can predict the traffic instructions for the first area 220 based on the scan information obtained from the vehicle 201 and the scan information obtained from the scan information obtained by other vehicles, wherein the scan information can be included in the databases 403, 404. The cloud 401 can predict the traffic instructions for the area 220 based on the scan information obtained from one or more sensors 230 that detect the information. The cloud 401 can estimate the traffic instructions for the first area 220 based on the detected information obtained from the vehicle 201 and the detected information obtained from the scan information obtained by other vehicles and sensors 230 installed at the area, wherein the scan information can be included in the databases 403, 404. According to one aspect, as in Figure 3a and 3b As disclosed in , the cloud 401 sends an information stream including estimated traffic instructions for the area 220 to the other vehicle 202 .

[0135] More specifically, according to one aspect, the determination of information is performed by a machine learning algorithm that creates a model of the first region 220 and the second region 221 that is continuously improved, ie, trained, whenever new information is available.

[0136] Before the model is fully trained, a more preliminary model may be used. An example of this may be that the method is able to estimate traffic instructions based on a combination of identifying known road signs and input from the vehicle 201 and / or cloud-connected sensors 230 installed at the first area 220 and / or the second area 221. In this example, the preliminary model is to only assume that parking is allowed in areas with stop signs, although this may lead to errors if there is other information on the sign that cannot be predicted. For example, this information can be used to roughly estimate recommended vehicle speeds for other cloud-connected vehicles, where to park the vehicle, etc. However, because the model is based on information from the second area 221 in addition to information from the first area 220, the time to fully train the model for the first area 220 is reduced.

[0137] The method provides estimated traffic instructions for the first area 220 to another vehicle 202 when the other vehicle 202 is approaching or entering the first area 220 .

[0138] In some embodiments, the other vehicle 202 may also receive recommended speeds, driving directions, parking instructions, non-driving directions, maximum heights, maximum weights, bridge tunnels, pedestrian streets, bus lanes, HOV (carpool) lanes, no-passing zones, tolls, speeding cameras, and specific rules for specific lanes to assist the user of the other vehicle 202 or to assist the autonomous driving system of the other vehicle 202 in complying with traffic rules.

[0139] In some embodiments, the other vehicle 202 may also display predicted instructions to assist the other vehicle 202 in complying with traffic regulations at the first area having the one or more road signs 305 .

[0140] Figure 3a is a schematic diagram showing an exemplary environment according to some embodiments. For example, Figure 2 The road sign instruction prediction system 200 shown in FIG. Figure 3a environment 300a.

[0141] Figure 3a Two environments (i.e., first area 220 or second area 221) are shown, which include multiple vehicles 201 traveling on a road toward the first area 220 or the second area 221, the first area 220 or the second area 221 having sensors 230 and road signs 305. In this example, the two environments each include a road passing through a parking area. The first area 220 or the second area 221 need not be exactly the same, however, some of the traffic instructions of the first area 220 should be the same as some of the traffic instructions of the second area 221. Figure 3aIn the two environments, the traffic instructions related to how and when parking is allowed in the parking lot in the first area 220 and the traffic instructions related to how and when parking is allowed in the parking lot in the second area 221 are the same. According to one aspect, the corresponding traffic instructions related to parking can be identified by the same parking sign 305.

[0142] Another vehicle 202 approaching or entering the first area 220 receives or obtains an estimate of traffic instructions for the first area 220. According to one aspect, the instructions are estimated traffic instructions for where parking is allowed and where parking is not allowed. According to one aspect, this can be estimated based on where different vehicles are parked and how long they are parked.

[0143] According to one aspect, the estimated instructions include instructions whether there are any parking fees, so that the other vehicle 202 does not violate the parking rules of the first area. According to one aspect, this can be predicted based on the time it takes for the vehicle to be locked from stopping, that is, the time it takes for the user of the vehicle to walk to the parking meter, pay the fee and walk back. According to one aspect, this can be estimated based on whether the vehicle uses a parking fee application.

[0144] According to one aspect, the estimated instructions include instructions for how long parking is allowed in the parking area / lot (i.e., in the first area 220). According to one aspect, the estimated instructions include instructions on which days of the week parking is allowed. According to one aspect, this can be estimated based on when different vehicles are stationary parked, how long they are stationary parked, and whether there are differences in patterns between different days of the week and month.

[0145] According to one aspect, the estimated instructions include instructions on whether special stickers or information are needed in the car to meet the regulations. The other vehicle 202 is also configured to display the received estimated instructions so that the user of the other vehicle 202 can see the traffic instructions.

[0146] According to one aspect, the other vehicle 202 is further configured to input the received estimated command into a driving assistance system of the other vehicle 202 .

[0147] Depending on the traffic instructions for the first area and the road signs present at the first area, the estimated instructions for one or more road signs may also include a mix of stop instructions and traffic instructions.

[0148] Figure 3b is a schematic diagram showing an exemplary environment according to some embodiments. For example, Figure 2 The road sign instruction estimation system 200 shown in FIG. Figure 3b environment 300b.

[0149] Figure 3b Two environments (i.e., the first area 220 or the second area 221) are shown, which include multiple vehicles 201 traveling toward / through / out of the environment (i.e., the first area 220 or the second area 221), with one or more road signs 305 along different directions. In this example, the first area 220 or the second area 221 includes an intersection of two roads. The first area 220 does not need to be exactly the same as the second area 221, but some of the traffic instructions of the first area 220 should be the same as some of the traffic instructions of the second area 221. In the environment shown, the traffic instructions related to how to allow turns at intersections are the same in the first area 220 and the second area 221. According to one aspect, the corresponding traffic instructions can be identified by the same road signs 305 being located at the intersection and / or the same markings 305 being located on the road. Information from the first area 220 or the second area 221 related to traffic instructions that are not the same in both areas 220, 221 can be used as input when estimating traffic instructions in other areas with the same traffic instructions. The first area 220 or the second area 221 includes two sensors 230 installed at the first area 220 or the second area 221. The sensors 230 may be installed on lamp posts, parking meters, road signs, or buildings at the area.

[0150] As vehicle 201 approaches a first area 220 or a second area 221 including an intersection, vehicle 201 scans (i.e., monitors) the status of traffic lights in all directions, senses or approximately calculates the number of other vehicles in the vicinity relative to the intersection, senses the speed and direction of the vehicle, senses the type of vehicle, and senses any pedestrians beside or crossing the road, including their locations.

[0151] The sensor(s) 230 at the first area 220 or the second area 221 of the intersection also scan (i.e., monitor) their respective areas 220, 221, the status of traffic lights in each direction, sense or approximate the number of other vehicles in the vicinity relative to the intersection, sense the speed and direction of the vehicle, sense the type of vehicle, and sense any pedestrians beside or crossing the road, including their locations.

[0152] Additionally, vehicles 201 and / or sensors 230 installed in the area may sense images and / or text on the road or on road signs 305 indicating, for example, lane directions, or may sense any other relevant signs at one or more road signs for modeling traffic patterns in the area, such as yield signs (such as turns allowed on red).

[0153] According to one aspect, the vehicle 201 continuously sends the detected information to the cloud 401. The vehicle 201 may alternatively send the scan information to the cloud 401 at a specific determined time point or at regular time intervals (eg, every 5 seconds).

[0154] According to one aspect, cloud-connected sensor 230 continuously sends scan information to cloud 401. Sensor 230 may alternatively send scan information to cloud 401 at specifically determined points in time or at regular time intervals (eg, every 5 seconds).

[0155] When the vehicle 201 arrives at an intersection with a road sign 305, and when traveling through the first area 220 or the second area 221, the vehicle 201 continuously senses or approximately calculates the number of other vehicles and their positions at the intersection and other vehicles traveling through the area (including their positions, directions, and vehicle speeds). At the same time, all visible road signs 305 and traffic lights around the vehicle 201 are sensed.

[0156] In addition, the vehicle 201 identifies pedestrians beside the road or crossing the road (including their locations).

[0157] When vehicle 201 leaves the area, vehicle 201 senses the number of approaching vehicles (ie, vehicles about to enter the area), senses the traffic flow behind the vehicle (eg, using a rear-facing vision sensor).

[0158] According to one aspect, the vehicle 201 continues to send scan information to the cloud 401 until, for example, 200 meters after an intersection or until the end of the line of sight.

[0159] Another vehicle 202 that is approaching or entering the first area 220 receives or obtains an estimated traffic instruction of the first area 220, for example, from the cloud 401, and the other vehicle 202 follows the estimated traffic instruction so that the other vehicle 202 obeys the traffic rules in the first area 220. According to one aspect, the other vehicle 202 is configured to display the received estimated traffic instruction in the other vehicle so that the user of the other vehicle 202 can obtain the traffic rules in the first area 220 and can obey the traffic rules. According to one aspect, the other vehicle 221 is also configured to use the received estimated traffic instruction as an input to the autonomous driving system or navigation system of the other vehicle 202, so that the other vehicle 202 obeys the traffic rules in the first area 220.

[0160] According to one aspect, the estimated traffic directives include speed limits on major roads and intersections. According to one aspect, this can be estimated based on the speeds of different vehicles.

[0161] According to one aspect, the estimated instructions include information about which roads in the intersection are allowed to be driven in. For example, this can be predicted or estimated based on traffic flow and whether the vehicle enters different roads.

[0162] According to one aspect, the estimated instructions include information on when and where a stop is permitted and for how long the stop is permitted.

[0163] According to one aspect, the estimated instruction includes information that the lane is a taxi lane or a lane for a specific type of vehicle. According to one aspect, this is based on a pattern that only specific types of vehicles travel on specific lanes.

[0164] According to one aspect, different instructions for an intersection area are based on the pattern of vehicles that have passed through the intersection.

[0165] According to one aspect, the first area 220 is a continuous first area 220. According to one aspect, the first area 220 is a continuous first area 220 surrounding the further vehicle 202.

[0166] Figure 4 2 is a schematic block diagram of an exemplary device according to some aspects. The exemplary device is a pattern detection device 410 for detecting a pattern of traffic flow behavior in the first area 220 or the second area 221 to estimate a traffic instruction for the first area 220 .

[0167] The pattern detection device 410 includes a control circuit CNTR 400, which in turn may include: a scanning device SCAN 406 (e.g., a scanning circuit) configured to scan or monitor the first area 220 or the second area 221, an analyzing device ANLS402 (e.g., an analyzing circuit) configured to analyze the scanning information, an estimating device PRED403 (e.g., an estimating circuit) configured to estimate instructions for the area, a receiving device REC 404 (e.g., a receiving circuit) configured to receive estimated instructions on the area, and a display device DSPL 405 (e.g., a display circuit) configured to display the received estimated instructions.

[0168] The mode detection device 410 may be included in combination with Figure 2 The described mode detection system 200, and / or the mode detection device 410 may be configured to perform a combination of Figure 1 The method steps of any of the described methods.

[0169] Figure 5is a schematic diagram illustrating an exemplary computer-readable medium according to some aspects. A computer program product includes a non-transitory computer-readable medium 500 having a computer program 510 containing program instructions thereon, wherein the computer program can be loaded into a data processing unit and is configured to cause execution in conjunction with Figure 1 The method steps of any of the described methods.

[0170] According to some embodiments, the computer program product comprises a computer readable medium, such as for example a Universal Serial Bus (USB), a memory, a plug-in card, an embedded drive or a Read Only Memory (ROM). Figure 5 An exemplary computer readable medium in the form of a compact disc (CD) ROM 500 is shown. The computer readable medium has stored thereon a computer program including program instructions. The computer program can be loaded into a data processor (PROC) 520, which may be included in the device or vehicle 201, 202, for example. When the computer program is loaded into a data processing unit, the computer program may be stored in a memory (MEM) 530 associated with the data processing unit or in a memory (MEM) 530 included in the data processing unit. According to one aspect, when the computer program is loaded into the data processing unit and executed by it, it causes execution according to the instructions in the data processing unit. Figure 1 The invention further comprises method steps of any of the methods shown in or otherwise described herein.

[0171] According to one aspect, and as Figure 6 The disclosed cloud service 401 for estimating a traffic directive for a first area 220 includes a control circuit, which is configured to: S100 receive the position and / or movement of at least one vehicle 201 and / or vehicle user 301 detected S1 in the first area 220 and / or the second area 221 associated with the traffic directive corresponding to the first area 220; S2 determine a behavior pattern based on the detected position and / or movement of at least one vehicle 201 and / or vehicle user 301; and S3 estimate the traffic directive for the first area 220 based on the determined behavior pattern. According to one aspect, the control circuit of the cloud service is further configured to: S101 provide a recommended speed, driving direction, parking instruction, non-driving direction, maximum height, maximum weight, bridge tunnel, pedestrian street, bus lane, carpool lane, no-passing zone, toll, speed camera, and specific rules of a specific lane to the user of the vehicle or the autonomous vehicle to assist in complying with the traffic directive for the first area 220.

[0172] Generally speaking, the device mentioned in this article should be understood as a physical product, such as a device. The physical product may include one or more components, such as a control circuit in the form of one or more processors, one or more controllers, etc.

[0173] The described embodiments and aspects and their equivalents may be implemented in software, hardware, or a combination thereof. The embodiments may be performed by general-purpose circuits. Examples of general-purpose circuits include digital signal processors (DSPs), central processing units (CPUs), coprocessor units, field programmable gate arrays (FPGAs), and other programmable hardware. Alternatively or additionally, the embodiments may also be performed by dedicated circuits, such as application-specific integrated circuits (ASICs). For example, general-purpose circuits and / or dedicated circuits may be associated with, or included in, devices such as vehicles.

[0174] Embodiments and aspects may be implemented in an electronic device (associated with or included in a vehicle) that includes a device, circuit, and / or logic according to any of the embodiments described herein. Alternatively or additionally, the electronic device (associated with or included in a vehicle) may be configured to perform a method according to any of the embodiments described herein.

[0175] Generally speaking, all terms used herein may be interpreted according to their ordinary meanings in the relevant technical fields, unless a different meaning is clearly given and / or implied in the context in which the terms are used.

[0176] Reference is made herein to various embodiments. However, one skilled in the art will recognize many variations of the described embodiments that still fall within the scope of the claims.

[0177] For example, the method embodiments described herein disclose exemplary methods by performing multiple steps in a certain order. However, it should be appreciated that the order of these events may occur in another order without departing from the scope of the claims. Moreover, some method steps may be performed in parallel, even if they have been described as being performed sequentially. Therefore, the steps of any method disclosed herein do not necessarily have to be performed in the exact order disclosed, unless a step is explicitly described as being performed after or before another step, and / or it is implied that a step must be performed after or before another step.

[0178] In the same way, it should be noted that in the description of the embodiments and aspects, the division of functional blocks into specific units is not intended to represent a limitation. On the contrary, these divisions are exemplary only. The functional blocks described as a unit herein may be divided into two or more units. Moreover, the functional blocks described as implemented as two or more units herein may be merged into fewer (e.g., single) units.

[0179] Where appropriate, any feature of any one of the embodiments disclosed herein may be applicable to any other embodiment. Likewise, any advantage of any one of the embodiments may be applicable to any other embodiment, and vice versa.

[0180] Therefore, it should be understood that the details of the described embodiments are merely examples set forth for purposes of illustration and that all variations coming within the scope of the claims are intended to be embraced therein.

Claims

1. A method (100) for estimating a traffic order at a first area (220), wherein: The first area (220) is a parking area, and the method comprises the following steps: - (S1) detecting the position and / or movement of at least one vehicle (201) in the first area (220) or in a second area (221), wherein the second area (221) is a parking area and the traffic instructions in the second area (221) and the first area (220) are the same in terms of parking; -(S2) determining a behavior pattern based on the detected position and / or movement of the at least one vehicle (201), wherein the behavior pattern is estimated based on when and for how long the at least one vehicle (201) is stationary in the first area (220) or the second area (221); and - (S3) estimating a parking instruction for the first area (220) based on the determined behavior pattern.

2. The method (100) according to claim 1, wherein: The method further comprises the following steps: (S4) Receiving an estimated traffic instruction of the first area (220) in another vehicle (202) entering the first area (220).

3. The method (100) according to claim 2, wherein: The detection step (S1) comprises: (S11) Scanning the first area (220) and / or the second area (221) by one or more sensors (230).

4. The method (100) according to claim 3, wherein: The scanning (S11) further includes: The first area (220) is scanned (S11) by a sensor (230) mounted on the vehicle (201) and / or the other vehicle (202) and / or a sensor (230) installed at the first area (220) and / or the second area (221).

5. The method (100) of claim 1, wherein: The determining step (S2) comprises: (S21) Analyzing the detected position and / or movement of the at least one vehicle (201) in the cloud (401).

6. The method (100) of claim 1, wherein: The step (S3) of estimating traffic instructions for said first area (220) comprises a step (S31) of analyzing the determined behavior pattern in the cloud (401).

7. The method (100) of claim 1, wherein: The method further comprises: (S5) detecting one or more of a road sign, a road, a traffic lane, a marking on the road; and The step (S3) of estimating said traffic directive is further based on detected one or more road signs, roads, traffic lanes and / or signs on said roads.

8. The method (100) of claim 1, wherein: The detected movement includes information regarding one or more of time, date, speed of vehicles and / or vehicle users, location of vehicles and / or vehicle users, number of vehicles, type of vehicles, and direction of vehicles and / or vehicle users.

9. The method (100) of claim 2, wherein: The method further comprises the following steps: (S6) displaying estimated traffic instructions for the first area (220) in the other vehicle (202).

10. The method (100) according to claim 2, wherein: The method further comprises the following steps: (S7) Receiving estimated traffic instructions for the first area (220) in the autonomous driving system of the other vehicle (202).

11. The method (100) of claim 1, wherein: The estimated traffic instructions for the first area (220) include one or more instructions of recommended speed, driving direction, parking instructions, non-driving direction, maximum height, allowed tire type, maximum weight, bridge tunnel, pedestrian street, bus lane, carpool lane, no-driving zone, toll, speed camera, and specific rules for specific lanes to assist the vehicle user or the vehicle's autonomous driving system to comply with the traffic instructions for the first area (220).

12. The method (100) according to any one of the preceding claims, wherein: The method further comprises the following steps: (S8) Identifying a first indication / indicator of a traffic directive associated with the first area (220).

13. The method (100) according to claim 12, wherein: The step of identifying the first indication (S8) comprises: One or more road signs and / or signs on and / or at the road at the first area (220) are identified.

14. The method (100) of claim 12, wherein: The method further comprises the following steps: (S9) comparing the first indication with a second indication of a traffic directive associated with the second area (221) to determine whether the first indication and the second indication are indications corresponding to the traffic directive.

15. A computer program product, comprising a non-transitory computer-readable medium (500), on which is a computer program (510) comprising program instructions, wherein the computer program can be loaded into a data processing unit and is configured to execute the method according to any one of claims 1 to 14 when the computer program is run by the data processing unit.

16. An apparatus for estimating a traffic order at a first area (220), wherein: The first area (220) is a parking area, and the device comprises: A memory including executable instructions and one or more processors configured to communicate with the memory, wherein the one or more processors are configured to cause the device to: - (S1) detecting the position and / or movement of at least one vehicle (201) in the first area (220) or in a second area (221), wherein the second area (221) is a parking area and the traffic instructions in the second area (221) and the first area (220) are the same in terms of parking, -(S2) determining a behavior pattern based on the detected position and / or movement of the at least one vehicle (201), wherein the behavior pattern is estimated based on when and for how long the at least one vehicle (201) is stationary in the first area (220) or the second area (221), and - (S3) estimating a parking instruction for the first area (220) based on the determined behavior pattern.

17. The device according to claim 16, wherein: The one or more processors are also configured to enable the device to further receive (S4) recommended speeds, driving directions, parking instructions, non-driving directions, maximum heights, maximum weights, bridge tunnels, pedestrian streets, bus lanes, carpool lanes, no-driving zones, tolls, speed cameras, and specific rules for specific lanes to assist the user of another vehicle in complying with traffic instructions for the first area (220).

18. A vehicle (201, 202) comprising an apparatus according to claim 16 or 17.

19. A cloud service (401) for estimating traffic instructions for a first area, wherein: The first area (220) is a parking area, wherein the cloud service comprises a control circuit, and the control circuit is configured to: - (S100) receiving a detected (S1) position and / or movement of at least one vehicle (201) in the first area (220) or in a second area (221), wherein the second area (221) is a parking area and the traffic instructions in the second area (221) and the first area (220) are the same in terms of parking, -(S2) determining a behavior pattern based on the detected position and / or movement of the at least one vehicle (201), wherein the behavior pattern is estimated based on when and for how long the at least one vehicle (201) is stationary in the first area (220) or the second area (221), and - (S3) estimating a parking instruction for the first area (220) based on the determined behavior pattern.

20. The cloud service (401) according to claim 19, characterized in that: The control circuit of the cloud service is further configured to: (S101) Recommended speed, driving direction, parking instructions, non-driving direction, maximum height, maximum weight, bridge tunnels, pedestrian streets, bus lanes, carpool lanes, no-driving zones, tolls, speed cameras, and specific rules for specific lanes are provided to vehicle users or autonomous vehicles to assist in complying with traffic instructions in the first area (220).

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