System and method for traffic insight

Abstract

A method of providing traffic insight to a vehicle supporting vehicle-to-everything (V2X) using basic safety messages (BSMs) includes one or more of the following steps: sending a BSM by a road vehicle; forwarding a V2X message including the BSM to a multi-access edge computing (MEC) server; extracting data samples from the V2X message including the BSM; generating statistics from the extracted data samples; and visualizing the statistics for a driver of the vehicle.

Description

Technical Field

[0001] This disclosure relates to a system and method for providing traffic condition insights to vehicle drivers. More specifically, this disclosure relates to a system and method for providing traffic condition insights to drivers of vehicles supporting vehicle-to-everything (V2X) communication. Background Technology

[0002] As vehicles continue to evolve, an increasing number of vehicles are equipped with systems that allow them to communicate with other vehicles (e.g., via vehicle-to-vehicle (V2V) systems). These systems allow drivers to modify their vehicle's behavior based on information they receive about the behavior of surrounding vehicles.

[0003] While current vehicle communication systems have achieved their intended purpose, a new and improved system and approach is still needed for vehicles to communicate with each other outside of surrounding vehicles. Summary of the Invention

[0004] According to several aspects, a method for providing traffic condition insights to vehicles supporting Vehicle-to-Everything (V2X) using Basic Safety Messages (BSMs) includes one or more of the following steps: sending the BSM by a road vehicle; forwarding the BSM and other V2X messages to a Multi-Access Edge Computing (MEC) server; extracting data samples from the BSM and other V2X messages; generating statistical results based on the extracted data samples; and visualizing the statistical results for vehicle drivers. In some deployments, other types of cloud computing servers are used instead of MEC servers; for simplicity, the term "MEC" refers to any capable cloud computing server.

[0005] In another aspect of this disclosure, the roadside sensor transmits the sensing data to the roadside unit (RSU).

[0006] In another aspect of this disclosure, the RSU forwards the information to the MEC.

[0007] In another aspect of this disclosure, MEC analysis examines the sample distribution of potentially useful data elements over a spatial-temporal scope.

[0008] In another aspect of this disclosure, the method also includes sending the sample distribution to the RSU.

[0009] In another aspect of this disclosure, the sample distribution indicates traffic conditions with a predetermined confidence level.

[0010] In another aspect of this disclosure, the method also includes sending the sample distribution to a cellular network.

[0011] In another aspect of this disclosure, the cellular network forwards the statistical results from the MEC to other vehicles.

[0012] In another aspect of this disclosure, the RSU forwards the statistical results from the MEC to other vehicles.

[0013] According to several aspects, a method for providing traffic condition insights to vehicles supporting Vehicle-to-Everything (V2X) using Basic Safety Messages (BSMs) includes one or more of the following steps: sending the BSM by a road vehicle; sending perception data from a Roadside Unit (RSU) as a V2X message; forwarding the BSM and other V2X messages to a Multi-Access Edge Computing (MEC) server; extracting data samples from the BSM and other V2X messages; generating statistical results based on the extracted data samples; and visualizing the statistical results for vehicle drivers.

[0014] In another aspect of this disclosure, the roadside sensor sends the sensing data to the RSU.

[0015] In another aspect of this disclosure, MEC analysis examines the sample distribution of potentially useful data elements over a spatial-temporal scope.

[0016] In another aspect of this disclosure, the method also includes sending the sample distribution to the RSU.

[0017] In another aspect of this disclosure, the sample distribution indicates traffic conditions with a predetermined confidence level.

[0018] In another aspect of this disclosure, the method also includes sending the sample distribution to a cellular network.

[0019] In another aspect of this disclosure, the cellular network forwards the statistical results from the MEC to other vehicles.

[0020] In another aspect of this disclosure, the RSU forwards the statistical results from the MEC to other vehicles.

[0021] According to several aspects, a method for providing traffic condition insights to vehicles supporting Vehicle-to-Everything (V2X) using Basic Safety Messages (BSMs) includes one or more of the following steps: sending the BSM by a roadside vehicle; sending perception data from a Roadside Unit (RSU) as a V2X message; forwarding the BSM and other V2X messages to a Multi-Access Edge Computing (MEC) server; extracting data samples from the BSM and other V2X messages; generating statistical results based on the extracted data samples; and visualizing the statistical results for vehicle drivers. The MEC server or other type of cloud computing server analyzes the sample distribution of potentially useful data elements over a spatial-temporal range.

[0022] In another aspect of this disclosure, the method also includes sending the sample distribution to an RSU or a cellular network.

[0023] In another aspect of this disclosure, the statistical results were sent to other vehicles.

[0024] Further applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0025] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure in any way.

[0026] Figure 1 This is a block diagram of a vehicle supporting vehicle-to-everything (V2X) according to an exemplary embodiment;

[0027] Figure 2 This is an overview diagram of a V2X-enabled vehicle encountering temporary road conditions according to an exemplary embodiment;

[0028] Figure 3 This is an operational flowchart of a V2X-enabled vehicle according to an exemplary embodiment;

[0029] Figure 4 A visualization provided to a driver in a V2X-enabled vehicle, according to an exemplary embodiment, is shown; and

[0030] Figure 5A and Figure 5B An alternative visualization provided to a driver in a V2X-enabled vehicle, according to an exemplary embodiment, is shown. Detailed Implementation

[0031] The following description is exemplary in nature and is not intended to limit this disclosure, application, or use.

[0032] refer to Figure 1The illustration shows a vehicle 300 equipped with Vehicle-to-Everything (V2X) technology, capable of providing traffic condition insights using Basic Safety Messages (BSM). Vehicle 300 in various arrangements is a non-motorized or motorized vehicle, including, but not limited to, bicycles, motorcycles, buses, trucks, boats, aircraft, and automobiles. Vehicle 300 includes an Electronic Control Unit (ECU) 302 communicating with a receiver 304. Further, vehicle 300 includes a set of sensors 308 for acquiring information about the condition of vehicle 300 and a transmitter 306 for transmitting information about vehicle 300. In various embodiments, the vehicle uses receiver 304 to receive BSMs from other vehicles and roadside units (RSUs). In various embodiments, vehicle 300 communicates with a Multiple Access Edge Computing (MEC) server to relay information about vehicle 300 and to receive information about the vehicle 300's environment. Note that other types of cloud computing servers may be used instead of the MEC server, and for simplicity, the term "MEC" refers to any capable cloud computing server in this disclosure.

[0033] ECU 302 is a non-general-purpose electronic control device with a pre-programmed digital computer or processor having memory or non-transitory computer-readable medium for storing data, such as control logic, software applications, instructions, computer code, data, lookup tables, etc., and a transceiver. Computer-readable medium includes any type of media that can be accessed by a computer, such as read-only memory (ROM), random access memory (RAM), hard disk drive, optical disc (CD), digital video disc (DVD), or any other type of memory. "Non-transitory" computer-readable medium does not include wired communication links, wireless communication links, optical communication links, or other communication links that transmit transient electrical signals or other signals. Non-transitory computer-readable medium includes media capable of permanently storing data and media capable of storing data and subsequently being rewritten, such as rewritable optical discs or erasable storage devices. Computer code includes any type of program code, including source code, object code, and executable code. ECU 302 is configured to execute code or instructions. Furthermore, receiver 304 and transmitter 306 are configured to conduct wireless communication using the Wi-Fi protocol under IEEE 802.11x.

[0034] ECU 302 also includes one or more application programs. An application program is a software program configured to perform a specific function or a set of functions. In various applications, the application includes one or more computer programs, software components, instruction sets, processes, functions, objects, classes, instances, associated data, or portions thereof suitable for implementation in suitable computer-readable program code. In some implementations, these application programs are stored in memory or in additional or separate memory.

[0035] Vehicle 300 utilizes BSMs (Balanced Messages) sent by road vehicles and other V2X messages from the vehicle to gather inferential traffic conditions about some intermediate distance ahead. The vehicle is supported by RSUs (Roadside Units) and MEC (Multi-access Edge Computing) servers that receive forwarded V2X messages from associated RSUs. Typically, based on the extraction of relevant data elements (e.g., vehicle speed and steering angle), the MEC server performs statistical analysis and identifies sample distributions that may suggest certain temporary traffic conditions are at a sufficient level of confidence. The MEC server transmits these statistics to potentially affected vehicles via V2X messages. Upon receiving the messages, the statistics are visualized according to the minimum confidence level and visualization format required by the driver. Thus, insights into the traffic conditions are presented to each driver with a preferred level of certainty and visual type.

[0036] refer to Figure 2 The diagram shows a group of vehicles (vehicle A) 12, (vehicle B) 14, (vehicle C) 16, and (vehicle D) 18, all equipped with the ability to receive BSM and communicate with the MEC server. Figure 2 In the example shown, vehicle A encounters a temporary road condition 20, such as a puddle appearing during heavy rain. Next, at 22, vehicles A and B take action based on road condition 20. Simultaneously at 24, vehicle C (and possibly vehicles A and B) broadcasts what vehicle C perceives and / or acts upon via the BSM. Finally, at 26, vehicle D, at a certain distance behind vehicles A, B, and C, becomes aware of road condition 20, inferred by the MEC server based on the time-space-related BSM received by vehicle D.

[0037] When a sufficient number of vehicles (e.g., vehicles A, B, and C) pass through a specific location, the MEC server obtains a sufficient number of raw data samples (data elements such as vehicle speed and steering angle), which are extracted from the vehicle's BSM. Based on the statistical analysis performed by the MEC server, the MEC server determines the distribution of indicators of temporary road conditions (e.g., puddles caused by heavy rain) with a sufficiently high confidence level (e.g., >= 0.6).

[0038] The MEC server transmits a sample distribution with sufficiently high confidence, indicating temporary road conditions, to potentially affected vehicles. Potentially affected vehicles at a mid-distance from the current road conditions (e.g., vehicle D) receive statistical results from the MEC (which may be updated over a specific period) and visualize these results. Figure 4 , Figure 5A and Figure 5BThe result is given to the driver of vehicle D, provided that the confidence level of the result is not lower than the threshold configured by the driver. The driver of vehicle D is aware of the predicted traffic conditions and is able to prepare appropriate maneuvers based on intuitive visualizations without knowing the exact type of event occurring some distance ahead.

[0039] Further reference Figure 3 The diagram 100 illustrates the operation of a V2X vehicle 102 communicating with an MEC server 106 via a proxy and auxiliary message source 104. In step 108, vehicle 102 sends a BSM (Balanced Message Signal), while roadside sensors send sensing data to the RSU (Roadside Unit) in step 114. In step 116, the RSU forwards the received V2X message to the MEC server 106. In step 120, the MEC server 106 extracts data samples of potentially useful data elements from the V2X message. In step 122, the MEC server analyzes the sample distribution of potentially useful data elements within an appropriate spatial-temporal range. In step 124, the MEC server 106 sends the sample distribution with sufficiently high confidence and indicative of traffic conditions to the RSU or the cellular network.

[0040] In step 118, the RSU or cellular network forwards the statistical results provided by the MEC to each vehicle. In step 110, V2X enables vehicle 102 to receive the statistical results provided by the MEC. In step 112, the statistical results are processed so that the driver can visually view the results.

[0041] Now for reference Figure 4 This diagram illustrates a visualization of the statistical results provided by the MEC to the drivers of vehicles 200 traveling along road 202. Changes in vehicle speed are illustrated by the gradient of grayscale (or color) of arrows 202 and 206. Darker grayscale represents lower speeds, and lighter grayscale represents higher speeds. Lane-changing behavior is inferred based on a sample distribution of steering wheel angles and is indicated by the bifurcation of arrow 202.

[0042] Figure 5A and Figure 5B Alternative types of visualizations are shown. For example, Figure 5A A rectangular block 208 is shown, followed by two alternative paths 210 and 212; and Figure 5B An arrow 214 is shown, followed by two alternative paths 216 and 218. Therefore, other indications of traffic flow are incorporated into the graphical properties of the visualization, such as the cross-sectional width of a shape representing the road vehicle density.

[0043] This disclosure offers several advantages for V2X-enabled vehicles. These include the use of BSM (and other relevant V2X messages) in spatial-temporal ensembles and statistical methods to provide insights into traffic conditions ahead of the vehicle. This provides an important complement to vehicle-to-vehicle (V2V) information services. Furthermore, visualizations of inferred traffic conditions are provided in an intuitive and interpretable manner, based on the driver's configuration at the lowest confidence level and visualization format. Visualization can be performed without explicitly inferring event types (i.e., neither the MEC server nor the vehicle-side system needs to tell the driver the exact type of the expected event ahead), thus ensuring that statistical results provide optimal benefit to the driver without misleading or causing unnecessary commotion.

[0044] The description in this disclosure is exemplary in nature only, and any changes that do not depart from the spirit and scope of this disclosure are intended to fall within its scope. Such changes should not be considered as departing from the spirit and scope of this disclosure.

Claims

1. A method for providing traffic condition insights to vehicles supporting vehicle-to-everything V2X using Basic Safety Messages (BSM), the method comprising: BSM is sent by road vehicles; Forward V2X messages, including BSM, to multi-access edge computing (MEC) servers or other types of cloud computing servers; Extract data samples from V2X messages, including BSM; Statistical results are generated based on the extracted data samples, wherein the statistical results define one or more distributions, which indicate temporary road conditions within the spatial-temporal range of vehicles supporting V2X; as well as The statistical results are visualized for the driver of the V2X-enabled vehicle, wherein the statistical results are displayed such that changes in vehicle speed are indicated by a color gradient within one or more directional arrows, wherein darker colors within the one or more directional arrows represent lower vehicle speeds, and lighter colors lighter than the darker colors represent higher vehicle speeds, wherein lane-changing behavior is based on the distribution of steering wheel angles and is indicated by the bifurcation of the one or more directional arrows, and wherein the cross-sectional width of the one or more directional arrows represents the density of road vehicles.

2. The method according to claim 1, wherein, The roadside sensors send the sensed data to the roadside unit (RSU).

3. The method according to claim 2, wherein, The RSU forwards the information to the MEC.

4. The method according to claim 3, wherein, The MEC analysis measures the sample distribution of potentially useful data elements over a spatial-temporal range.

5. The method of claim 4, further comprising sending the sample distribution to the RSU.

6. The method according to claim 4, wherein, The sample distribution indicates traffic conditions with a predetermined confidence level.

7. The method of claim 4, further comprising transmitting the sample distribution to a cellular network.

8. The method according to claim 7, wherein, The cellular network forwards the statistical results from the MEC to other vehicles.

9. The method according to claim 2, wherein, The RSU forwards the statistical results from the MEC statistics to other vehicles.

10. A method for providing traffic condition insights to vehicles supporting vehicle-to-everything V2X using Basic Safety Messages (BSM), the method comprising: BSM is sent by road vehicles; Sensing data from roadside units (RSUs) is sent as V2X messages; The V2X messages, including BSM, are forwarded to multi-access edge computing (MEC) servers or other types of cloud computing servers. Extract data samples from the V2X messages, including BSM; Statistical results are generated based on the extracted data samples, wherein the statistical results define one or more distributions, which indicate temporary road conditions within the spatial-temporal range of vehicles supporting V2X; as well as The statistical results are visualized for the driver of the V2X-enabled vehicle, wherein the statistical results are displayed such that changes in vehicle speed are indicated by a color gradient within one or more directional arrows, wherein darker colors within the one or more directional arrows represent lower vehicle speeds, and lighter colors lighter than the darker colors represent higher vehicle speeds, wherein lane-changing behavior is based on the distribution of steering wheel angles and is indicated by the bifurcation of the one or more directional arrows, and wherein the cross-sectional width of the one or more directional arrows represents the density of road vehicles.

Images