Fault detection system

Abstract

We provide an obstacle detection system that can reliably determine whether or not there are road obstructions. [Solution] An obstacle detection system for detecting road obstacles that obstruct vehicle traffic performs the following processes based on time-series behavioral data relating to the behavior of multiple vehicles traveling in a predetermined section of road, to determine whether multiple vehicles have successively shown evasive behavior to avoid an obstacle on the road; if multiple vehicles have shown evasive behavior, to extract behavioral data of the multiple vehicles traveling in the road section; to calculate the travel trajectories of each of the multiple vehicles based on the behavioral data; and to determine that an obstacle exists in a space if the size of the space on the road in the road section where the travel trajectories of multiple vehicles do not exist is greater than or equal to a threshold.

Description

Technical Field

[0001] The present disclosure relates to a fault detection system.

Background Art

[0002] Patent Document 1 discloses a technology related to an obstacle detection system that detects obstacles on a road from sensor information of a plurality of vehicles. The system of this technology determines, for each vehicle, whether or not the vehicle has shown an avoidance behavior to avoid an obstacle on the road based on time-series behavior data regarding the behavior of each motor vehicle traveling on the road, and when a plurality of motor vehicles show an avoidance behavior within a predetermined time, it is determined that there is an obstacle on the road.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the technology of Patent Document 1, the presence or absence of the avoidance behavior of a motor vehicle is determined based on behavior data such as yaw rate, lighting information of a direction indicator, and vehicle speed. However, even if it is determined that a plurality of motor vehicles have shown an avoidance behavior, an obstacle on the road may not actually be found, and an incorrect report may be sent to a road operator or the like. Therefore, there remains room for improvement in the technology of Patent Document 1 in terms of more reliably determining the presence or absence of a traffic obstacle on the road.

[0005] The present disclosure has been made in view of the above problems, and an object thereof is to provide a fault detection system capable of reliably determining the presence or absence of a traffic obstacle on the road.

Means for Solving the Problems

[0006] This disclosure provides an obstacle detection system for detecting road obstacles that obstruct vehicle traffic, in order to solve the above problems, comprising at least one storage device storing at least one program, and at least one processor coupled to the at least one storage device. The at least one processor is configured to perform, by executing at least one program, a process to determine whether multiple vehicles have successively shown evasive behavior to avoid an obstacle on the road, based on time-series behavior data relating to the behavior of multiple vehicles that have traveled a predetermined road section on the road; a process to retrieve behavior data of multiple vehicles traveling in the road section if multiple vehicles have shown evasive behavior; a process to calculate the travel trajectories of each of the multiple vehicles based on the behavior data; and a process to determine that an obstacle exists in a space if the size of the space on the road section where the travel trajectories of multiple vehicles do not exist is greater than or equal to a threshold. [Effects of the Invention]

[0007] The obstruction detection system described herein makes it possible to reliably determine road obstructions. [Brief explanation of the drawing]

[0008] [Figure 1] This flowchart shows an example of a routine executed by the information server of the fault detection system in this embodiment. [Figure 2] This figure shows an example of a space where no vehicle trajectories exist. [Modes for carrying out the invention]

[0009] Embodiments of this disclosure will be described below. However, when the number of elements, quantities, amounts, ranges, etc., are mentioned in the embodiments described below, this disclosure is not limited to the number mentioned unless it is specifically stated or clearly defined in principle. Furthermore, structures, steps, etc., described in the embodiments described below are not necessarily essential to this disclosure unless they are specifically stated or clearly defined in principle.

[0010] Embodiment. 1. Configuration of the fault detection system according to the embodiment

[0011] The obstacle detection system of this embodiment is a system for reliably determining whether there are obstacles causing traffic obstruction on roads such as expressways. Obstacles here include obstacles that hinder vehicle traffic on the road, road collapses, steps, and cracks. The obstacle detection system comprises multiple vehicles, an information server, and an information terminal device.

[0012] Each vehicle is equipped with a power source for driving, such as an engine or motor, various sensors for detecting the vehicle's status, a navigation system, turn signals, and an electronic control unit (hereinafter referred to as "ECU").

[0013] The navigation system sets a planned route from the vehicle's current location to the destination based on stored map information, the vehicle's current location, and the destination set by the user, and provides route guidance by displaying the set planned route on a non-illustrated display. Turn signals are mounted on the left and right sides of the front and rear of the vehicle and are activated by the driver to indicate the direction of turns or lane changes to those around the vehicle.

[0014] The ECU receives vehicle sensor data, including signals from various sensors, via its input ports. Examples of vehicle sensor data input to the ECU include position data from a position sensor that detects the vehicle's current position, vehicle speed data from a vehicle speed sensor that detects vehicle speed, turn signal illumination data, and yaw rate data from a yaw rate sensor that detects the vehicle's yaw rate. The ECU outputs various control signals via its output ports. The ECU exchanges various data with an information server via wireless communication through a DCM (Data Communication Module).

[0015] Information servers are typically located within a data center. Typically, an information server is a microcomputer comprising at least one processor, at least one memory device, and at least one input / output interface.

[0016] The processor includes a CPU (Central Processing Unit). The processor is coupled with a memory device and an input / output interface. Various types of information are stored in the memory device. Examples of memory devices include volatile memory, non-volatile memory, and HDDs (Hard Disk Drives). For example, the memory device stores coordinate information (latitude and longitude information) for each distance marker (kilometer post). The input / output interface is an interface for exchanging various types of information with each vehicle via wireless communication and with information terminal devices via wired or wireless communication.

[0017] Furthermore, the memory device stores at least one program related to the road obstacle detection operation. The processor reads and executes the program stored in the memory device, thereby realizing various functions of the information server. For example, by reading and executing the program stored in the memory device, the processor performs the process of storing time-series behavioral data for each vehicle. Here, behavioral data refers to data about the behavior of the vehicles while they are driving. Typically, in the process of storing behavioral data, the processor sets road sections as segments of the road divided into predetermined distances based on the stored coordinate information, and for each road section, inputs vehicle sensor data from each vehicle traveling in that road section via wireless communication at predetermined intervals, and stores it in the memory device as time-series behavioral data. The driving trajectory of each vehicle can also be calculated from the behavioral data.

[0018] Information terminal devices are installed, for example, within the facilities of road operators. These information terminal devices are configured as standard computers. They receive various types of information from each vehicle and information servers via wired or wireless communication.

[0019] 2. Operation of the fault detection system of the embodiment Figure 1 is a flowchart showing an example of a routine executed by the information server of the fault detection system in this embodiment. This routine is repeatedly executed for each road section and at predetermined intervals by the information server's processor executing a program stored in the memory.

[0020] In step 100 of the routine shown in FIG. 1, it is determined whether each vehicle has an avoidance behavior. Here, the same processing as that from S100 to S160 of the obstacle detection routine shown in FIG. 2 in the prior art document described in Patent Document 1 is executed. Briefly, the CPU of the information server inputs the behavior data of the vehicles in the road section, and based on the input behavior data, determines whether there is an avoidance behavior in the vehicles traveling in the road section. The determination of the avoidance behavior is made based on, for example, determination of whether the vehicle has made a sharp turn, determination of the operation of the vehicle's direction indicator, and determination of the acceleration and deceleration operations of the vehicle. The determination of the sharp turn operation is made based on the time change of the yaw rate data included in the behavior data. The determination of the operation of the direction indicator is made based on the lighting data of the direction indicator included in the behavior data. And the determination of the acceleration and deceleration operations of the vehicle is made based on the vehicle speed data included in the behavior data. When the processing of step 100 is completed, the processing proceeds to step 102.

[0021] In step 102, based on the determination result of step 100, it is determined whether the avoidance behaviors of the plurality of vehicles are continuous in the road section. As a result, if the determination is established, the processing proceeds to step 104. On the other hand, if the determination is not established, it is determined that there is no traffic obstacle on the road, and the processing of this routine is terminated.

[0022] In step 104, the behavior data of each vehicle for a predetermined time in the road section is respectively retrieved from the storage device of the vehicle information server. The behavior data here includes position data, vehicle speed data, and yaw rate data as vehicle sensor data for calculating the position, angular velocity, and vehicle speed of each vehicle. When the processing of step 104 is completed, the processing proceeds to step 106. In step 106, based on the behavior data of each vehicle, the traveling trajectory of each vehicle for a predetermined time in the road section is respectively calculated. Here, for example, an optimization method such as a Kalman filter may be used to calculate a more accurate traveling trajectory. When the processing of step 106 is completed, the processing proceeds to step 108.

[0023] In step 108, by superimposing the driving trajectories of each vehicle calculated in step 106 on a map, the size of the space where there is no driving trajectory on the road is calculated. FIG. 2 is a diagram showing an example of the space where there is no driving trajectory of each vehicle. As shown in FIG. 2, the space where there is no driving trajectory of each vehicle is highly likely that there is some kind of traffic obstacle and the vehicle is not driving. Here, on the road in this road section, the space where there is no driving trajectory of each vehicle is calculated as the space where there may be a traffic obstacle. When the processing of step 108 is completed, the process proceeds to step 110.

[0024] In step 110, it is determined whether the size of the space calculated in the processing of step 108 is greater than or equal to a predetermined threshold. The threshold here is a threshold for determining the presence or absence of traffic obstacles such as obstacles, steps, depressions, cracks, etc. on the road, and for example, a preset value is used. As a result, if the determination is not established, it is determined that there is no traffic obstacle in this road section, and the processing of this routine is terminated.

[0025] On the other hand, in the processing of step 110, if the determination is established, it is determined that there is a traffic obstacle in the space on the road, and the process proceeds to step 112. In step 112, it is notified that there is a traffic obstacle in the space on the road. Here, for example, the information terminal device notifies that there is a traffic obstacle in the space by wired communication or wireless communication. The information terminal device notifies the received position information of the space and the fact that there is a traffic obstacle to a display (not shown), etc. Thereby, the staff of the road operator who recognizes this notification can go to the location of the traffic obstacle and take measures to remove the traffic obstacle.

[0026] As described above, according to the obstacle detection system of this embodiment, when multiple vehicles are performing evasive maneuvers in succession, the presence or absence of a traffic obstruction is determined by whether the size of the space where the driving trajectories of each vehicle do not exist is greater than or equal to a threshold. If no space is formed where the driving trajectories of each vehicle do not exist, there is a high probability that there is no traffic obstruction on the road. Therefore, according to the obstacle detection system of this embodiment, it is possible to determine the presence or absence of a traffic obstruction on the road more reliably.

Claims

[Claim 1] An obstacle detection system that detects road obstacles that obstruct vehicle traffic, At least one storage device containing at least one program, The system comprises at least one processor coupled with the at least one storage device, The at least one processor, by executing the at least one program, A process to determine whether the multiple vehicles continuously exhibited evasive behavior to avoid obstacles on the road, based on time-series behavioral data relating to the behavior of multiple vehicles traveling on a predetermined road section on the road; When the aforementioned multiple vehicles exhibit the avoidance behavior, the process involves extracting the behavior data of the aforementioned multiple vehicles traveling on the road section. A process to calculate the driving trajectory of each of the multiple vehicles based on the aforementioned behavior data, If the size of the space on the road section where the driving trajectories of the multiple vehicles do not exist is greater than or equal to a threshold, the process of determining that an obstacle exists in that space, A fault detection system configured to perform the following actions.

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