Server System
The server system addresses the challenge of detecting and mitigating speed reduction propagation in traffic by estimating wave speeds and controlling vehicle parameters, thereby reducing collision risks.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- TOYOTA JIDOSHA KK
- Filing Date
- 2024-10-25
- Publication Date
- 2026-05-13
AI Technical Summary
Existing systems fail to effectively detect and mitigate the propagation of speed reduction phenomena in congested traffic conditions, which can lead to increased rear-end collision risks.
A server system that acquires traffic data, estimates the propagation speed of deceleration waves, and controls vehicle parameters to alert drivers or adjust driving assistance functions to prevent collisions.
The system detects the propagation of speed reduction phenomena and reduces the likelihood of rear-end collisions by providing timely alerts and adjusting vehicle controls.
Smart Images
Figure 2026077417000001_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of server systems.
Background Art
[0002] As this type of system, when a vehicle travels in an automatic driving mode in which the driving of the host vehicle is automatically controlled based on traffic information including the average speed, average headway time, average inter-vehicle distance, and traffic density of vehicles at points around the host vehicle, a system for setting driving control parameters including speed, inter-vehicle distance, and headway time has been proposed (see Patent Document 1).
Prior Art Documents
Patent Documents
[0003]
Patent Document 1
Summary of the Invention
Problems to be Solved by the Invention
[0004] For example, when the road is relatively congested, if a vehicle traveling in front of the host vehicle and at a relatively distant position from the host vehicle decelerates, the following vehicle traveling behind the one vehicle will also decelerate. Then, a speed reduction phenomenon will propagate from the one vehicle to the rear. As a result, there is a possibility that the speed reduction phenomenon will also propagate to the host vehicle. When such an event occurs, the possibility of a collision in a rear-end collision accident increases. In the technology described in Patent Document 1, it is difficult to detect the propagation of the speed reduction phenomenon as described above. In addition, a technology for measuring traffic volume from an image using AI (Artificial Intelligence) has been proposed.
[0005] The present invention has been made in view of the above circumstances, and an object thereof is to provide a server system capable of detecting the propagation of a speed reduction phenomenon.
Means for Solving the Problems
[0006] A server system according to one aspect of the present invention comprises: acquisition means for acquiring first information indicating traffic characteristics in a predetermined section on a road; estimation means for estimating the propagation speed of a wave that propagates deceleration in the predetermined section based on the first information; and control means for controlling a vehicle using second information based on the estimated propagation speed. [Brief explanation of the drawing]
[0007] [Figure 1] This is a block diagram showing the configuration of the server system according to the embodiment. [Figure 2] This figure shows an example of traffic characteristics expressed by traffic flow rate and density. [Figure 3] This figure shows an example of a vehicle's trajectory. [Modes for carrying out the invention]
[0008] Embodiments relating to the server system will be described with reference to Figures 1 to 3. In Figure 1, the server system 10 includes an information transmission / reception unit 101, a vehicle driving data reception processing unit 102, a sudden deceleration determination unit 104, a traffic situation estimation unit 106, a traffic characteristic estimation unit 108, a backward wave speed determination unit 110, a backward wave arrival vehicle determination unit 111, and a transmission information creation unit 112. Hereafter, the "backward wave speed determination unit 110" and the "backward wave arrival vehicle determination unit 111" will be referred to as "BW speed determination unit 110" and "BW arrival vehicle determination unit 111," respectively.
[0009] The information transmission / reception unit 101 is configured to communicate with the vehicle 20. The information transmission / reception unit 101 receives driving data from the vehicle 20. For example, the driving data may include at least one of the following: the position of the vehicle 20, the speed of the vehicle 20, the distance between the vehicle 20 and a vehicle traveling in front of the vehicle 20, information indicating that braking has been performed, and information on the operation of driver assistance functions. The driver assistance functions may include at least one of the following: pre-crash safety (PCS), adaptive cruise control (ACC), and anti-lock braking system (ABS).
[0010] The vehicle driving data receiving processing unit 102 performs predetermined processing on the driving data received by the information transmission / reception unit 101. For example, the vehicle driving data receiving processing unit 102 may perform processing to convert the driving data into a format suitable for the database as predetermined processing. The vehicle driving data receiving processing unit 102 registers the driving data in the database 103.
[0011] The sudden deceleration determination unit 104 determines whether or not a vehicle has decelerated suddenly based on the driving data registered in the database 103. For example, the sudden deceleration determination unit 104 may determine whether or not a vehicle has decelerated suddenly based on at least one of the following: changes in the vehicle's (e.g., vehicle 20) speed, whether or not brake operation was performed, and information on the operation of the driver assistance function. If it is determined that a vehicle has decelerated suddenly, the sudden deceleration determination unit 104 may identify the location where the sudden deceleration occurred based on the vehicle's position included in the driving data. The sudden deceleration determination unit 104 then registers location data indicating the location where the sudden deceleration occurred and the time when the sudden deceleration occurred in the database 105.
[0012] The traffic condition estimation unit 106 extracts driving data from the driving data registered in the database 103 relating to multiple vehicles that have traveled a predetermined section during a predetermined time period. Based on the extracted driving data, the traffic condition estimation unit 106 estimates the traffic conditions for a predetermined section during a predetermined time period. The traffic condition estimation unit 106 registers the traffic condition data showing the estimation results in the database 107. For example, the traffic condition estimation unit 106 may estimate density and traffic flow rate as traffic conditions. Here, density may be calculated as the reciprocal of the distance (in other words, length) occupied by one vehicle. The distance occupied by one vehicle may be the sum of the vehicle length and the distance between vehicles. Traffic flow rate may be calculated as the product of density and vehicle speed. The vehicle speed may be the average speed of multiple vehicles traveling in the predetermined section. At least one of the predetermined section and the predetermined time period may be specified in advance by the operator of the server system 10. The predetermined section may be a part of an expressway (e.g., a highway).
[0013] The traffic characteristics estimation unit 108 estimates the traffic characteristics of a predetermined section during a predetermined time period based on traffic condition data registered in the database 107. Here, the traffic characteristics can be represented by a kQ curve as shown in Figure 2. For example, the traffic characteristics estimation unit 108 may estimate the kQ curve as the above traffic characteristics based on traffic condition data. The traffic characteristics estimation unit 108 registers the traffic characteristics data showing the estimation result in the database 109. In the kQ curve, traffic flow when the density k is relatively small may be called "free flow". In the kQ curve, traffic flow when the density k is higher than the density of free flow and the traffic flow rate Q is higher than the traffic flow rate of free flow may be called "critical flow". In the kQ curve, traffic flow when the density k is higher than the density of critical flow may be called "congested flow".
[0014] The BW speed determination unit 110 may determine, based on the location data registered in the database 105, whether or not there is a location where sudden deceleration occurred within a predetermined time. If it is determined that there is a location where sudden deceleration occurred within a predetermined time, the BW speed determination unit 110 obtains traffic condition data and traffic characteristic data from databases 107 and 109 for the section including the location where sudden deceleration occurred, and for the time period including the time when the sudden deceleration occurred.
[0015] The BW speed determination unit 110 determines the propagation speed of backward waves based on traffic condition data and traffic characteristic data. Here, backward waves are a wave phenomenon that describes the phenomenon in which changes in the speed of a preceding vehicle are successively propagated to following vehicles when a following vehicle is traveling while following the movement of a preceding vehicle. For example, if a preceding vehicle decelerates suddenly, the speed reduction phenomenon is successively propagated to following vehicles. Backward waves may also be called shock waves.
[0016] For example, the BW speed determination unit 110 may identify the difference between the traffic conditions during the time period in which the sudden deceleration occurred and the traffic conditions during the time period immediately preceding it. When sudden deceleration occurs, the distance between vehicles decreases. Therefore, the density during the time period in which the sudden deceleration occurred is higher than the density during the time period immediately preceding it. For example, in the kQ curve shown in Figure 2, if the traffic conditions during the time period immediately preceding the sudden deceleration are those of point A, and the traffic conditions during the time period in which the sudden deceleration occurred are those of point B, the propagation speed of the backward wave can be determined from the slope θ of the line segment connecting points A and B. For example, the BW speed determination unit 110 may determine the propagation speed of the backward wave from the identified difference and the kQ curve.
[0017] For example, the BW speed determination unit 110 may identify the difference between the traffic conditions in the section where the sudden deceleration occurred and the traffic conditions in the section downstream of that section. Note that the section downstream of the section where the sudden deceleration occurred means the section ahead in the direction of travel of the vehicle that experienced the sudden deceleration, rather than the section where the vehicle that experienced the sudden deceleration was located. The traffic conditions in the section downstream of the section where the sudden deceleration occurred can be said to be the traffic conditions in the section where the sudden deceleration occurred before the sudden deceleration occurred. Therefore, the BW speed determination unit 110 may determine the propagation speed of the backward wave from the identified difference and the kQ curve.
[0018] For example, the BW speed determination unit 110 may determine the propagation speed of a backward wave in advance by aggregating sudden decelerations caused by the same backward wave from past statistical data for each section of the road, such as location data and traffic condition data. The BW speed determination unit 110 may then record in advance the relationship between a kQ curve, which is an example of traffic characteristic data, and the propagation speed of a backward wave. For example, the BW speed determination unit 110 may determine the propagation speed of a backward wave based on the traffic conditions in the section where the sudden deceleration occurred and the relationship recorded in advance.
[0019] Assuming that changes in the speed of a preceding vehicle propagate to subsequent vehicles, if one vehicle decelerates suddenly, the vehicles following that vehicle will also decelerate suddenly. For example, the BW speed determination unit 110 may extract one or more point data points from multiple point data points related to sudden deceleration caused by the same backward wave. The BW speed determination unit 110 may then determine the propagation speed of the backward wave based on the point and time at which the sudden deceleration occurred, as indicated by the extracted point data.
[0020] For example, the BW speed determination unit 110 may determine the propagation speed of backward waves using a trained model (in other words, AI). The trained model may be a trained model constructed by machine learning using data from each section of the road (e.g., location data, traffic condition data, and traffic characteristic data) as training data.
[0021] Based on the location data registered in the database 105 and the propagation speed of the backward wave determined by the BW speed determination unit 110, the BW arrival vehicle determination unit 111 identifies a vehicle that is estimated to have the backward wave propagate upstream of the point where the sudden deceleration occurred in the future. Then, the BW arrival vehicle determination unit 111 determines (or estimates) the position and time at which the identified vehicle encounters the backward wave. Here, upstream of the point where the sudden deceleration occurred means behind the traveling direction of the vehicle that performed the sudden deceleration.
[0022] Here, an explanation will be added by referring to the time-space diagram shown in FIG. 3. In FIG. 3, the white circles indicate the points where the sudden deceleration occurred. In FIG. 3, the slope of the dashed arrow indicating the backward wave changes according to the propagation speed of the backward wave. In FIG. 3, the black circle indicates the current position of vehicle A. The solid line extending from the black circle corresponds to the past travel trajectory of vehicle A, and the dashed line extending from the black circle corresponds to the future travel trajectory of vehicle A. In FIG. 3, the intersection point (time t, distance A) between the dashed line extending from the black circle indicating the current position of vehicle A and the dashed arrow indicating the backward wave corresponds to the position and time at which vehicle A encounters the backward wave determined by the BW arrival vehicle determination unit 111.
[0023] The transmission information creation unit 112 creates transmission information to be transmitted to the vehicle through which the backward wave will propagate in the future, identified by the BW arrival vehicle determination unit 111. For example, the transmission information may be at least one of information for prompting the driver of the vehicle to pay attention and information for changing parameters related to the driving support function. Examples of information for prompting the driver to pay attention include information for notifying the driver that the situation is likely to result in a collision. For example, examples of parameters related to the driving support function include parameters for accelerating the timing at which the collision damage mitigation brake issues a collision warning (specifically, parameters related to at least one of the inter-vehicle distance and relative speed at which the collision warning is issued), parameters for accelerating the start timing of control to increase the brake pressure in the collision damage mitigation brake, parameters for temporarily increasing the set inter-vehicle distance of the adaptive cruise control, and the like.
[0024] The information transmission / reception unit 101 transmits the transmission information created by the transmission information creation unit 112 to a vehicle (for example, vehicle 20).
[0025] Vehicle 20 includes an information transmission / reception unit 201, a vehicle information aggregation unit 202, a driving state determination unit 203, a backward wave arrival estimation unit 204, a PCS function change unit 205, a PCS function 206, an ACC function change unit 207, and an ACC function 208. Hereinafter, the "backward wave arrival estimation unit 204" will be described as the "BW arrival estimation unit 204" as appropriate. Note that the PCS function 206 may be referred to as a collision damage mitigation brake. Note that vehicle 20 may be a connected car.
[0026] The vehicle information aggregation unit 202 may acquire information from various sensors mounted on vehicle 20. The vehicle information aggregation unit 202 may transmit the acquired information as driving data to the server system 10 via the information transmission / reception unit 201 at each predetermined period. The driving state determination unit 203 may determine the driving state of vehicle 20 based on the information from various sensors acquired by the vehicle information aggregation unit 202.
[0027] The BW arrival estimation unit 204 may estimate the timing at which the backward wave will reach the vehicle 20 based on the transmission information received from the server system 10 via the information transmission / reception unit 201 (i.e., the transmission information created by the transmission information creation unit 112) and the driving state of the vehicle 20 determined by the driving state determination unit 203 (for example, the position and speed of the vehicle 20). If the transmission information is information that prompts the driver to pay attention, the BW arrival estimation unit 20 may issue a warning to the driver according to the estimated timing. If the transmission information is information for changing parameters related to the driving support function, the BW arrival estimation unit 20 may change the parameters related to the driving support function according to the estimated timing. If the parameters to be changed are parameters related to the pre-collision braking system (PCS), the BW arrival estimation unit 204 may control the PCS function change unit 205 to change the parameters related to the PCS function 206. If the parameter to be changed is a parameter related to adaptive cruise control, the BW arrival estimation unit 204 may control the ACC function modification unit 207 to change the parameter related to the ACC function 208.
[0028] Furthermore, the server system 10 may consist of a single server or multiple servers. The vehicles identified by the BW arrival vehicle determination unit 111 as vehicles on which backward waves are estimated to propagate are not limited to vehicles traveling in the section including the point where the sudden deceleration occurred, but may also be vehicles traveling in a section different from the section including the point where the sudden deceleration occurred.
[0029] (Technical effects) When a following vehicle is traveling in a situation where it is following the movement of a preceding vehicle, if the preceding vehicle slows down, the decrease in speed propagates to the following vehicles. It is known that in critical flow (i.e., the speed and density at which maximum traffic volume is achieved in a given road section), rear-end collisions are likely to occur due to the decrease in speed. Here, the propagation of deceleration that causes rear-end collisions (in other words, the propagation of the speed reduction phenomenon) differs depending on the traffic characteristics of the road section. For example, the propagation speed may differ depending on the traffic characteristics. Also, depending on the traffic characteristics, the sudden deceleration of one vehicle may not propagate to the following vehicles.
[0030] The server system 10 determines (or estimates) the propagation speed of the backward wave. The server system 10 then characterizes the vehicles on which the backward wave will propagate. The server system 10 transmits to the identified vehicles, for example, information to alert the driver of the vehicle, and information to change parameters related to the driving assistance function. As a result, the driver of the vehicle may be alerted, or parameters related to the driving assistance function may be changed. In this way, the server system 10 can detect the propagation of the speed reduction phenomenon and suppress the occurrence of rear-end collisions.
[0031] Various aspects of the invention derived from the embodiments described above are described below.
[0032] A server system according to one aspect of the invention includes: acquisition means for acquiring first information indicating traffic characteristics in a predetermined section on a road; estimation means for estimating the propagation speed of a wave propagating deceleration in the predetermined section based on the first information; and control means for controlling a vehicle using second information based on the estimated propagation speed. In the above embodiment, the "traffic characteristic estimation unit 108" corresponds to an example of the "acquisition means," the "BW speed determination unit 110" corresponds to an example of the "estimation means," and the "transmission information creation unit 112" corresponds to an example of the "control means."
[0033] In one example of the server system, the first information may include at least one of the vehicle density and traffic flow rate in the predetermined section.
[0034] In another example of the server system, the second information may be information indicating at least one of the location and time at which the wave propagating the deceleration reaches the vehicle.
[0035] In another example of the server system, the control means may control the vehicle by changing parameters related to the driving assistance functions provided by the vehicle.
[0036] In other examples of the server system, the estimation means may estimate the propagation speed using a trained model constructed by machine learning.
[0037] The present invention is not limited to the embodiments described above, and can be modified as appropriate without contradicting the gist or idea of the invention as can be read from the claims and specification as a whole. Server systems with such modifications are also included within the technical scope of the present invention. [Explanation of Symbols]
[0038] 10…Server system, 20…Vehicle, 101, 201…Information transmission / reception unit, 102…Vehicle driving data reception processing unit, 103, 105, 107, 109…Database, 104…Sudden deceleration determination unit, 106…Traffic situation estimation unit, 108…Traffic characteristics estimation unit, 110…BW speed determination unit, 111…BW arrival vehicle determination unit, 112…Transmission information creation unit
Claims
1. An acquisition means for acquiring first information indicating traffic characteristics in a predetermined section on a road, An estimation means for estimating the propagation speed of a wave in which deceleration propagates in the predetermined section based on the first information, A control means for controlling the vehicle using the second information based on the estimated propagation speed, A server system equipped with the following features.
2. The first information includes at least one of the vehicle density and traffic flow rate in the predetermined section. The server system according to claim 1.
3. The second information is information indicating at least one of the position and time at which the wave propagating the deceleration reaches the vehicle. The server system according to claim 1.
4. The control means controls the vehicle by changing parameters related to the driving assistance functions provided by the vehicle. The server system according to claim 1.
5. The estimation means estimates the propagation speed using a trained model constructed by machine learning. The server system according to claim 1.