Vehicle driving control system

Abstract

The present invention provides a vehicle driving control system, which can appropriately continue driving control without immediately stopping driving control even if a situation occurs in which traffic congestion information cannot be received normally when receiving traffic congestion information to control the driving of the vehicle. A driving control device starts to obtain traffic congestion information received and processed by a road traffic information collection device (S1), and checks whether the traffic congestion information can be received and normally obtained within a specified time (S2). If the traffic congestion information is not received within the specified time, the estimated value of the last position of the traffic congestion at time t is calculated (S4), and the reliability of the estimated value of the last position of the traffic congestion is determined (S5). If the result is determined to be reliable, the estimated value of the last position of the traffic congestion is used as the last position of the traffic congestion. If it is determined to be unreliable, it is considered as a communication abnormality, driving control is stopped, and information provision to the driver is stopped.

Description

Technical Field

[0001] The present invention relates to a vehicle travel control system for acquiring information on a traffic congestion section to control the travel of the vehicle. Background Art

[0002] In vehicles such as automobiles, driving control systems have been developed to reduce the burden on drivers and achieve comfortable and safe driving, and some have already been put into practical use. In this driving control system, there is a system that not only obtains driving environment information detected by on-board equipment, but also obtains traffic information from the outside via communication, and implements driving control based on the traffic congestion occurring in the direction of travel.

[0003] For example, Patent Document 1 (Japanese Patent Application Laid-Open No. 2015-108955) discloses a technology for determining that a road is in traffic congestion and controlling any one of the accelerator, brake, and warning light when the road traffic information is traffic congestion information and the speed is below a predetermined speed.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Publication No. 2015-108955 Summary of the invention

[0007] Technical issues

[0008] However, when receiving traffic congestion information from the outside, there may be a period of time when traffic congestion information cannot be received due to important reasons such as radio wave interference in the communication line and / or a bad antenna of the vehicle-mounted device. In this case, it is determined that the communication is abnormal. At this time, if the traffic congestion information is stopped from being provided to the driver or the driving control is stopped, the driving assistance performance for the driver is reduced, resulting in a reduction in the commercial value of the vehicle.

[0009] At this time, a method of continuing to store the last received traffic congestion information on the vehicle side is considered, but as time passes, the stored information may not match the actual traffic congestion situation, resulting in erroneous information presentation and / or vehicle control.

[0010] The present invention is completed in view of the above situation, and its purpose is to provide a vehicle driving control system that can correctly continue driving control without immediately stopping driving control even if a situation occurs where traffic congestion information cannot be received normally when controlling the driving of the vehicle.

[0011] Technical Solution

[0012] A driving control system of a vehicle according to one embodiment of the present invention uses information about a traffic congestion section obtained from outside the vehicle through communication to control driving in the above-mentioned traffic congestion section. The driving control system of the above-mentioned vehicle comprises: a traffic congestion position estimation unit, which uses a probability distribution model of the above-mentioned traffic congestion section to estimate the position of the above-mentioned traffic congestion section when the information about the above-mentioned traffic congestion section cannot be obtained within a specified time; and a reliability judgment unit, which judges the reliability of the position of the above-mentioned traffic congestion section estimated by the above-mentioned traffic congestion position estimation unit based on changes in the above-mentioned probability distribution model caused by the passage of time.

[0013] Effects of the Invention

[0014] According to the present invention, when the travel of the host vehicle is controlled by receiving traffic congestion information, even if a situation occurs in which the traffic congestion information cannot be normally received, the travel control can be correctly continued without immediately stopping the travel control. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a diagram showing the configuration of a vehicle's travel control system.

[0016] Figure 2 It is an explanatory diagram showing the elapse of time after receiving traffic congestion information and changes in the reliability of the traffic congestion information.

[0017] Figure 3 This is a flow chart of a driving control process for traffic congestion.

[0018] Explanation of symbols

[0019] 1: Driving control system

[0020] 10: External environment recognition device

[0021] 20: Positioning device

[0022] 30: Map information processing device

[0023] 35: Road traffic information collection device

[0024] 40: Engine control unit

[0025] 50: Transmission control device

[0026] 60: Brake control device

[0027] 70: Steering control device

[0028] 80: Alarm control device

[0029] 100: Driving control device

[0030] 101: Traffic congestion detection department

[0031] 102: Traffic congestion location estimation unit

[0032] 103: Reliability Judgment Department

[0033] 104: Driving control unit

[0034] 150: Communication bus DETAILED DESCRIPTION

[0035] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Figure 1 In the figure, reference numeral 1 is a driving control system for a vehicle such as an automobile, which performs driving control including autonomous automatic driving of the vehicle. The driving control system 1 is structured with a driving control device 100 as the center, and includes an external environment recognition device 10, a positioning device 20, a map information processing device 30, a road traffic information collection device 35, an engine control device 40, a transmission control device 50, a brake control device 60, a steering control device 70, and an alarm control device 80, and each device is connected to a network via a communication bus 150.

[0036] The external environment recognition device 10 includes: various devices for environment recognition such as a vehicle-mounted camera unit 11, a radar device 12 such as a millimeter wave radar and / or a laser radar, and / or various sensors such as an outside temperature sensor 13 that detects the outside temperature as one of the meteorological conditions of the outside environment in which the vehicle is traveling. In addition to using detection information of objects around the vehicle detected by the camera unit 11 and / or the radar device 12, and environmental information such as the outside temperature detected by the outside temperature sensor 13 to recognize the external environment around the vehicle, the external environment recognition device 10 also uses the position information of the vehicle located by the positioning device 20, the map information from the map information processing device 30, and traffic information such as traffic congestion information collected by the road traffic information collection device 35 to recognize the external environment around the vehicle.

[0037] For example, when a stereo camera composed of two cameras that photograph the same object from different viewing angles is mounted as the camera unit 11, the external environment can be recognized in three dimensions by stereo processing a pair of left and right images photographed by the stereo camera. The camera unit 11 as a stereo camera is configured, for example, by arranging two color cameras having shutter synchronization with a photographing element such as a CCD and / or a CMOS on the left and right sides of the vehicle width direction with a predetermined base line length near the rearview mirror inside the front window in the upper part of the vehicle interior.

[0038] The pixel offset (parallax) of the corresponding positions between the left and right images captured by the camera unit 11 as a stereo camera is obtained by matching processing, and a distance image is generated by converting the pixel offset into brightness data, etc. The coordinates of the points on the distance image are converted into points in the real space centered on the vehicle according to the principle of triangulation, and the white lines (lane lines) of the road on which the vehicle is traveling, obstacles, vehicles traveling in front of the vehicle, etc. are recognized three-dimensionally.

[0039] By extracting a group of points that are candidates for white lines from an image and calculating straight lines and / or curves connecting the candidate points, it is possible to identify white lines on a road as lane lines. For example, in a white line detection area set on an image, edges whose brightness changes by a predetermined amount or more are detected on a plurality of search lines set along the horizontal direction (vehicle width direction), a group of white line start points and white line end points are detected for each search line, and the middle area between the white line start point and the white line end point is extracted as a white line candidate point.

[0040] Then, the time series data of the spatial coordinate position of the white line candidate point based on the vehicle movement amount per unit time is processed to calculate a model approximating the left and right white lines, and the white line is recognized using the model. As the approximate model of the white line, an approximate model obtained by connecting straight line components obtained by Hough transform or a model approximated by a curve such as a quadratic equation can be used.

[0041] The positioning device 20 detects the vehicle position of the host vehicle mainly by positioning based on signals from multiple navigation satellites such as GNSS (Global Navigation Satellite System) satellites. In addition, when the positioning accuracy is deteriorated due to the capture state of the signal (radio wave) from the satellite and / or the multi-channel influence caused by the reflection of the radio wave, the vehicle position of the host vehicle is detected by positioning using autonomous navigation using vehicle-mounted sensors such as a gyro sensor 22 and / or a vehicle speed sensor 23.

[0042] In the positioning performed by multiple navigation satellites, a signal including information related to the orbit and time, etc. transmitted from the navigation satellite is received via the receiver 21, and the own position of the host vehicle is located as an absolute position including longitude, latitude, altitude and time information based on the received signal. In addition, in the positioning performed by autonomous navigation, the position of the host vehicle as a relative position change amount is located based on the travel direction of the host vehicle detected by the gyro sensor 22 and the moving distance of the host vehicle calculated based on the vehicle speed pulse output from the vehicle speed sensor 23, etc.

[0043] The map information processing device 30 includes a map database DB, and determines and outputs the position on the map data of the map database DB based on the position data of the vehicle located by the positioning device 20. The map database DB is a database storing high-precision maps produced for vehicle control including driving assistance control for automatic driving, and is stored in a large-capacity storage medium such as a HDD (hard disk drive) and / or an SSD (solid state drive).

[0044] In detail, the high-precision map is constructed as a multi-dimensional map (dynamic map) that stores static information such as road shapes and / or connections between roads, and dynamic information such as traffic information collected through infrastructure communication in multiple levels. Road data includes the type of white line on the road, the number of lanes, the width of the lanes, point column data indicating the center position of the lane in the width direction, the curvature of the lane, the direction of travel of the lane, the speed limit, etc. It is stored together with attribute data such as the reliability of the data and / or the date of data update.

[0045] In addition, the map information processing device 30 performs maintenance management of the map database DB, checks the nodes, links, and data points of the map database DB and always maintains them in the latest state, and also creates and adds new data to areas where data does not exist in the database to build a more detailed database. The data update and new data addition of the map database DB are performed by comparing the position data obtained by positioning using the positioning device 20 with the data stored in the map database DB.

[0046] The road traffic information collection device 35 receives radio waves from, for example, an information distribution server in an intelligent transportation system (ITS) to collect road traffic information. For example, it obtains road traffic information such as the presence or absence of road construction (location and time period), the presence or absence of an accident (accident location and time), and road traffic (road traffic congestion) at predetermined intervals (for example, every 30 minutes), and transmits the information to the travel control device 100.

[0047] The engine control device 40 controls the operating state of the engine (not shown) based on signals from various sensors that detect the operating state of the engine and various control information sent via the communication bus 150. The engine control device 40 performs engine control mainly including fuel injection control, ignition timing control, and electronic throttle opening control based on, for example, the amount of intake air, throttle opening, engine water temperature, intake air temperature, air-fuel ratio, crank angle, accelerator opening, and other vehicle information.

[0048] The transmission control device 50 controls the oil pressure supplied to the automatic transmission (not shown) based on signals from sensors that detect the shift position and / or vehicle speed and / or various control information sent via the communication bus 150, and controls the automatic transmission according to a preset shift characteristic.

[0049] The brake control device 60 controls the brake devices (not shown) of the four wheels independently of the driver's brake operation based on, for example, the brake switch, the wheel speeds of the four wheels, the steering angle, the yaw rate, and other vehicle information. In addition, the brake control device 60 calculates the brake hydraulic pressure of each wheel based on the braking force of each wheel to perform anti-lock brake system control and / or anti-skid control, etc.

[0050] The steering control device 70 controls the steering torque generated by the electric power steering motor (not shown) provided in the steering system based on, for example, the vehicle speed, the steering torque of the driver, the steering angle, the yaw rate, and other vehicle information. The control of the steering torque is performed as a current control of the electric power steering motor to achieve a target steering torque for making the actual steering angle consistent with the target steering angle. In the absence of an override caused by the steering operation of the driver, the drive current of the electric power steering motor is controlled by, for example, PID control.

[0051] The alarm control device 80 is a device that controls the output of alarms and various information to be presented to the driver when abnormalities occur in various devices of the vehicle and / or to draw the attention of the driver. For example, at least one of visual outputs such as monitors, displays, and warning lights and auditory outputs such as speakers / buzzers is used to provide warnings / information presentations. During the execution of driving assistance control including automatic driving, the alarm control device 80 presents the control state of the driving assistance control to the driver. In addition, when the driving assistance control including automatic driving is stopped according to the driver's operation, the alarm control device 80 notifies the driver of the driving state at that time.

[0052] Next, the driving control device 100, which is the center of the driving control system 1, will be described. In the manual driving mode in which the driver holds the steering wheel and steers, when the driver operates a switch and / or panel not shown in the figure to set the driving mode to driving assistance, the driving control device 100 performs driving control of the driving assistance mode including automatic driving via the engine control device 40, the transmission control device 50, the brake control device 60 and the steering control device 70. In the driving control of the driving assistance mode, the driving control device 100 controls the vehicle based on the external environment information recognized by the external environment recognition device 10, the position information of the vehicle located by the positioning device 20, and the high-precision map information in the map database DB of the map information processing device 30 so that the vehicle travels along the target path at a predetermined speed.

[0053] In addition, when the driving control device 100 detects traffic congestion on the road ahead that is outside the field of view of the camera and cannot be recognized by the external environment recognition device 10, etc., based on the road traffic information from the road traffic information collection device 35, the driving control device 100 decelerates the host vehicle toward the end position of the traffic congestion section (the end of the traffic congestion). At this time, even if the traffic congestion information obtained as external information from outside the host vehicle is interrupted, the driving control device 100 continues the control without interrupting the driving control as much as possible.

[0054] That is, the road traffic information collection device 35 is set to obtain traffic congestion information from a server outside the vehicle at regular intervals, but sometimes a period of time during which traffic congestion information cannot be received from the server occurs due to important factors such as radio wave interference of the network line and / or poor condition of the vehicle-mounted antenna. In the case where the traffic congestion information obtained at regular intervals by the road traffic information collection device 35 is interrupted, the driving control device 100 estimates the position of the traffic congestion section based on at least the last acquired traffic congestion information and the time after the information is interrupted. Then, driving control is implemented when the reliability of the estimated position of the traffic congestion section exceeds a predetermined threshold.

[0055] Therefore, the driving control device 100 includes a traffic congestion detection unit 101, a traffic congestion position estimation unit 102, a reliability determination unit 103, and a driving control unit 104 as functional units for driving control in response to traffic congestion. Through these functional units, even when the traffic congestion information acquired regularly is interrupted, the driving control device 100 can appropriately estimate the position of the traffic congestion section and continue the control without interrupting the driving assistance mode.

[0056] Specifically, the traffic congestion detection unit 101 obtains road traffic information from the road traffic information collection device 35, and obtains traffic congestion information from the road traffic information to check whether traffic congestion occurs on the road ahead. The traffic congestion information includes information such as the front position of the traffic congestion section (traffic congestion front position), the last position of the traffic congestion section (traffic congestion last position), the moving speed of the last position of the traffic congestion section (traffic congestion last speed), and the length of the traffic congestion section. The traffic congestion detection unit 101 obtains at least the traffic congestion last position and the traffic congestion last speed.

[0057] At this time, the traffic congestion detection unit 101 monitors whether the road traffic information collection device 35 can receive radio waves from the external server and obtain traffic congestion information within a specified time (for example, 30 seconds). If the traffic congestion information cannot be obtained from the road traffic information collection device 35 within the specified time, the traffic congestion detection unit 101 instructs the traffic congestion position estimation unit 102 to estimate the position of the traffic congestion section.

[0058] The traffic congestion position estimation unit 102 estimates the position of the traffic congestion section using a probability distribution model that probabilistically expresses the deviation of the traffic congestion section. In this embodiment, the last position of the traffic congestion is estimated as the position of the traffic congestion section, and the last position of the traffic congestion x is estimated using a traffic congestion distribution model f(x) expressed by a probability density function with the last position of the traffic congestion x as a variable.

[0059] As the traffic congestion distribution model f(x), as shown in the following formula (1), a model is used in which the deviation of the position of the traffic congestion section (the end position of the traffic congestion) is assumed to follow a normal distribution. The variance σ in the traffic congestion distribution model f(x) is 2 Calculated based on past reception data.

[0060] f(x)=N(x,σ 2 )…(1)

[0061] In addition, as the traffic congestion distribution model f(x), for example, a model assuming Poisson distribution for traffic congestion caused by a sudden accident or the like may be applied.

[0062] The traffic congestion position estimation unit 102 denotes the time at which the traffic congestion information is last acquired as t0, the last position of the traffic congestion at time t0 as x0, and the last speed of the traffic congestion as v0, and estimates the last position of the traffic congestion at time t after time t0 using the following formula (2) based on formula (1). It should be noted that σ in formula (2) t 2 represents the variance σ at time t0 0 2 Changes over time.

[0063] f(x)=N(x0+v0(t-t0),σ 0 2 +σ t 2 )…(2)

[0064] That is, if the last information of traffic congestion cannot be obtained within the specified time, Figure 2As shown in FIG. 1 , relative to the time t0 when the last traffic congestion end information is obtained, as time passes after t1 seconds, t2 seconds, and t3 seconds, the probability that the last position of the traffic congestion is estimated to be the center of the normal distribution gradually decreases and the reliability decreases, and the last vehicle in the traffic congestion moves at a speed v and the variance increases. Therefore, in the traffic congestion distribution model f(x) at time t after time t0 just after receiving, the traffic congestion position estimation unit 102 uses the last position xt corresponding to the end of the vehicle side within a predetermined range of the standard deviation σ (for example, a range of ±3σ) in the normal distribution as the traffic congestion last position estimation value as shown in the following formula (3).

[0065] xt=x0+v0(t-t0)-3(σ 0 2 +σ t 2 )…(3)

[0066] At this time, since the position of the last end of the traffic jam also changes due to the conditions of the vehicles traveling around the vehicle (mainly in front), the estimated value of the last end of the traffic jam can be corrected using the number of surrounding vehicles after the traffic jam information is finally acquired and the moving speed of the last end of the traffic jam. That is, since the preceding vehicle in front of the vehicle and other vehicles that have surpassed the vehicle are important factors for the change of the last end of the traffic jam, the estimated value of the last end of the traffic jam estimated by the traffic congestion distribution model f(x) can be corrected based on the distance increase formed by the number of these vehicles and the distance change formed by the moving speed of the last end of the traffic congestion.

[0067] The reliability determination unit 103 determines the reliability of the traffic congestion last position estimation value xt by comparing the probability Pt of the center of the normal distribution of the traffic congestion last position estimation value xt estimated by the traffic congestion position estimation unit 102 with a preset threshold value H. The threshold value H is set to a value of about 60 to 70% of the probability Pt0 of the center at the time t0 when the traffic congestion last position information can be finally obtained, for example.

[0068] like Figure 2 As shown, at the end position xt0 of the traffic congestion relative to the time t0 when the last information of the end of the traffic congestion can be obtained, the estimated value of the end position of the traffic congestion xt1 = x0 + v0 (t-t0) - 3 (σ 0 2 +σ t 2), the probability Pt1 of the center of the traffic congestion distribution model f(x0+v0(t1-t0)) after t1 seconds is compared with the threshold value H. Then, when the probability Pt1 is greater than the threshold value H, it is determined that the reliability of the traffic congestion last position estimation value xt1 is at a level that can implement driving control, and the traffic congestion last position estimation value xt1 can be used for driving control.

[0069] In addition, the same is true when the probability Pt2 of the center of the traffic congestion distribution model f(x0+v0(t2-t0)) after time t0 to t2 seconds is greater than the threshold value H, and it is determined that the reliability of the traffic congestion last position estimation value xt2 after t2 seconds is at a level that can implement driving control. On the other hand, when the probability Pt3 of the center of the traffic congestion distribution model f(x0+v0(t3-t0)) after time t0 to t3 seconds decreases below the threshold value H, it is determined that the error of the traffic congestion last position estimation value xt3 after t3 seconds is large, and the reliability of the traffic congestion last position estimation value xt3 is lower than the level that can implement driving control, and the occurrence of abnormality is notified to the driving control unit 104, and the provision of traffic congestion information to the driver is stopped.

[0070] When the traffic congestion detection unit 101 detects that the road ahead is congested, the driving control unit 104 implements driving control to decelerate the host vehicle with the end of the traffic congestion as the target position based on the traffic congestion information received from the external information distribution server by the road traffic information collection device 35. Then, when the end of the traffic congestion is approached and can be recognized from the host vehicle, the vehicle is transferred to the deceleration control including stopping the vehicle based on the external environment information from the external environment recognition device 10.

[0071] At this time, when the road traffic information collection device 35 cannot receive traffic congestion information within the specified time due to poor communication, etc. at a location other than the external environment recognition performed by the external environment recognition device 10, the driving control unit 104 continues or interrupts driving control based on the judgment result of the reliability of the traffic congestion last position estimation value xt inferred by the traffic congestion position estimation unit 102.

[0072] That is, when the reliability determination unit 103 determines that the reliability of the traffic jam last position estimation value xt is at a level at which the travel control can be continued, the travel control unit 104 uses the traffic jam last position estimation value xt to continue the travel control without interrupting the travel control. On the other hand, when the reliability determination unit 103 determines that the reliability of the traffic jam last position estimation value xt is lower than the level at which the travel control can be performed and the traffic jam last position estimation value xt cannot be used for the travel control, the travel control is stopped.

[0073] Next, use Figure 3 The flowchart of will explain the above-mentioned driving control processing for traffic congestion.

[0074] Figure 3 The driving control process shown is a process executed at regular intervals in the driving control device 100. First, in the initial step S1, the driving control device 100 starts to obtain traffic congestion information received and processed via the road traffic information collection device 35. Next, the process proceeds to step S2 to check whether the traffic congestion information can be received and obtained normally within a specified time (for example, 30 seconds).

[0075] If the traffic congestion information can be received within the prescribed time and is normally acquired, the process proceeds from step S2 to step S3, updates the traffic congestion distribution model f(x) that assumes the normal distribution of the last position x of the traffic congestion, and exits the process. On the other hand, if the traffic congestion information is not received within the prescribed time, the process proceeds from step S2 to step S4, and calculates the estimated value xt of the last position of the traffic congestion at time t. The last position xt of the traffic congestion is calculated as the position corresponding to the end of the vehicle side of the ±3σ region in the traffic congestion distribution model f(x) at time t after the last traffic congestion information is received, as described in the above formula (3).

[0076] Thereafter, the process proceeds to step S5, where the probability Pt of the center of the normal distribution of the traffic jam end position at time t is compared with a preset threshold value H to determine whether the estimation is reliable. As a result, if Pt>H and the estimation is reliable, in step S6, the traffic jam end position estimation value xt is used as the traffic jam end position for driving control and providing information to the driver. On the other hand, if Pt≤H ​​and the estimation is not reliable, the process proceeds to step S7 as a communication abnormality, and driving control is stopped, and the provision of traffic jam information to the driver is stopped.

[0077] Thus, in this embodiment, in the process of implementing driving control for receiving traffic congestion information from outside the vehicle and decelerating the vehicle toward the end of the traffic congestion, in the case of a time period in which the traffic congestion information cannot be received due to poor communication, the probability distribution model of the traffic congestion information is used to estimate the end position of the traffic congestion. Thus, even when the traffic congestion information cannot be received, the driving control can be continued without immediately stopping the driving control, and the frequency of abnormal stopping of the information provision to the driver and the driving control function can be suppressed, and the commercial quality of the vehicle can be greatly improved.

Claims

1. A vehicle driving control system, characterized in that: The vehicle driving control system controls the driving in the traffic congestion section by using information of the traffic congestion section acquired from outside the vehicle through communication, and comprises: a traffic congestion position estimation unit that estimates the position of the traffic congestion section using a probability distribution model of the traffic congestion section when the information of the traffic congestion section cannot be obtained within a specified time; as well as a reliability determination unit that determines the reliability of the position of the traffic congestion section estimated by the traffic congestion position estimation unit based on the change of the probability distribution model over time, The reliability judgment unit compares the probability at the center of the normal distribution of the position of the traffic congestion section estimated by the traffic congestion position estimation unit with a preset threshold value to judge the reliability of the position of the traffic congestion section estimated by the traffic congestion position estimation unit. In the probability distribution model, the change of the probability distribution model due to the passage of time is realized by the variance of the deviation increasing with the passage of time. The traffic congestion position estimation unit uses the last position corresponding to the end of the predetermined range of the deviation on the host vehicle side in the normal distribution as the position of the traffic congestion section.

2. The vehicle driving control system according to claim 1, characterized in that: The information of the traffic congestion section includes at least the last position of the traffic congestion section and the last moving speed of the traffic congestion section.

3. The vehicle driving control system according to claim 2, characterized in that: The traffic congestion position estimation unit estimates the last position of the traffic congestion section based on the last moving speed of the traffic congestion section and the elapsed time since the information of the traffic congestion section was last acquired.

4. The vehicle travel control system according to any one of claims 1 to 3, characterized in that: The traffic congestion position estimation unit uses the probability distribution model as a model in which the position of the traffic congestion section follows a normal distribution, and estimates the last position of the traffic congestion section.

5. The vehicle driving control system according to claim 4, characterized in that: The traffic congestion position estimation unit estimates an end of a region of a predetermined range of the normal distribution on the host vehicle side as the last position of the traffic congestion section.

6. The vehicle travel control system according to any one of claims 1 to 3, characterized in that: The traffic congestion position estimation unit corrects the estimated value of the last position of the traffic congestion section based on the conditions of a preceding vehicle ahead of the host vehicle and other vehicles that have passed the host vehicle.

7. The vehicle driving control system according to claim 4, characterized in that: The traffic congestion position estimation unit corrects the estimated value of the last position of the traffic congestion section based on the conditions of a preceding vehicle ahead of the host vehicle and other vehicles that have passed the host vehicle.

8. The vehicle travel control system according to any one of claims 1 to 3, characterized in that: When the reliability of the estimated value at the last position of the traffic congestion section decreases to or below a predetermined value, the reliability determination unit determines that the estimated value at the last position of the traffic congestion section cannot be used for the travel control and stops the travel control.

9. The vehicle driving control system according to claim 4, characterized in that: When the reliability of the estimated value at the last position of the traffic congestion section decreases to or below a predetermined value, the reliability determination unit determines that the estimated value at the last position of the traffic congestion section cannot be used for the travel control and stops the travel control.

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