JP2008084003A - Vehicular drive support system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a drive support system for quickly and accurately predicting a traffic congestion even when a phenomenon causing the traffic congestion suddenly occurs. <P>SOLUTION: An ECU 5 for achieving the drive support system includes a traffic congestion cause detection block 5A for detecting the occurrence of a traffic congestion cause from information of other vehicles; a traffic density calculation block 5B for calculating a traffic density from information of other vehicles existing on a route where the traffic congestion cause occurs and road information of the route; and an information providing block 5C for providing information of the traffic congestion to the driver. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a driving support system that predicts a traffic jam using information acquired by inter-vehicle communication and provides information.

  The traffic jam prediction information provided by the Telematics Center, etc. was predicted based on past traffic jam information, so it predicts sudden traffic jams caused by sudden events (accidents, construction, and stopped vehicles). It is not possible.

Here, traffic congestion is judged using the current position, traveling direction and speed of the vehicle, and the result of calculating the current traffic congestion level and the reliability of the information is sent to the service provider. (See, for example, Patent Document 1).
JP 2001-118190 A

  However, even if the traffic jam information is provided as in Patent Document 1, if an event that causes traffic jam occurs suddenly, there is a problem that the traffic jam cannot be quickly and accurately predicted.

  The present invention has been made in view of the above-described problems, and its object is to grasp the situation of other vehicles in real time through inter-vehicle communication, so that even if an event that causes a traffic jam occurs unexpectedly, it can be performed quickly and accurately. It is to realize a driving support system that can predict traffic congestion.

  In order to solve the above-described problems and achieve the object, a first embodiment according to the present invention includes a map data storage unit that stores map data, and an inter-vehicle communication unit that transmits and receives vehicle information between other vehicles. The vehicle state detecting means for detecting the traveling state of the own vehicle, the congestion cause detecting means for detecting the occurrence of the congestion cause, the other vehicle information acquired by the inter-vehicle communication means, and the congestion cause acquired from the map data are Traffic density calculating means for calculating a traffic density representing a ratio of the number of vehicles existing on the route causing the congestion after a predetermined time to the area of the route from the road information of the generated route.

  According to the first aspect, by grasping the situation of other vehicles in real time by inter-vehicle communication, it is possible to quickly and accurately predict traffic congestion even when an event that causes traffic congestion suddenly occurs. .

  In the second mode, the road information includes intersection information of the route causing the traffic jam, and the traffic density is an inflow / outflow with respect to the current traffic density and the route causing the traffic jam. And the number of vehicles to be calculated.

  Further, in the third mode, the number of vehicles flowing into and out of the route causing the traffic jam is the vehicle position on the branch road connected to the intersection of the route causing the traffic jam and the direction indicated by the blinker, or It is detected from the route guidance information on the branch road.

  In the fourth embodiment, the number of vehicles flowing into and out of the route on which the cause of the traffic jam occurs is corrected by a coefficient that varies depending on the cause of the traffic jam.

  According to these forms, it is possible to perform highly accurate traffic jam prediction in consideration of vehicles flowing into and out of the route where the traffic jam has occurred.

  In the fifth embodiment, a traffic time predicting means for predicting a traffic jam occurrence time or a traffic jam elimination time from the traffic density, and an arrival time calculation for calculating a time at which the vehicle reaches the route on which the traffic jam has occurred. Means for determining whether the host vehicle encounters traffic jam from the arrival time of the host vehicle and the occurrence time or resolution time of the traffic jam, and information that provides traffic jam information when it is determined that the vehicle encounters the traffic jam Providing means. According to this form, it is possible to notify the vehicle in advance whether or not a traffic jam will be encountered.

  Further, in the sixth aspect, the occurrence or elimination of the traffic jam is caused by the fact that the number of vehicles existing on the route causing the traffic jam after a predetermined time exceeds the maximum allowable number determined from the area of the route causing the traffic jam. It is determined by whether or not. According to this aspect, it is possible to accurately determine the occurrence or elimination of traffic congestion.

  According to the present invention, it is possible to quickly and accurately predict a traffic jam even when an event that causes a traffic jam occurs unexpectedly by grasping the situation of another vehicle in real time through inter-vehicle communication.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

  The embodiment described below is an example as means for realizing the present invention, and the present invention can be applied to a modified or modified embodiment described below without departing from the spirit of the present invention.

[System configuration]
FIG. 1 is a block diagram showing a configuration of a driving support system according to an embodiment of the present invention.

  In FIG. 1, a driving support system 1 mounted on a vehicle includes an inter-vehicle communication device 2 that transmits and receives various information to and from one or a plurality of other vehicles (also referred to as counterpart vehicles) mounted with the system. The car navigation device 3, the driving state detection device 4 that outputs information on the driving state of the host vehicle, and the occurrence of traffic jams are predicted based on various information acquired from these devices 2, 3, and 4. ECU5 which performs driving support control which provides information to a driver about information.

  The inter-vehicle communication device 2 includes a transmission / reception antenna 21 and, for example, distributes own vehicle information and receives other vehicle information by wireless communication with other vehicles existing within a range of several hundred meters around the own vehicle position. Note that road-to-vehicle communication such as DSRC (narrow band wireless communication system) may be used if the distance to another vehicle is about several tens of meters.

  The car navigation device 3 includes a GPS antenna 31 and a GPS receiver 32 and outputs, for example, position information of the own vehicle (information on latitude, longitude, direction, etc.) to the ECU 5. In addition, the car navigation device 3 includes a display 33 that displays an image such as map information and a speaker 34 that emits a voice message or the like by route guidance or the like. The ECU 5 uses the display 33 and the speaker 34 to display an image, sound, or the like. To provide information to the driver.

  Further, the car navigation device 3 includes a map database (hereinafter referred to as a map DB) 35, and the ECU 5 from the map DB 35, for example, the position coordinates of the host vehicle after map matching, the front intersection coordinates (columns), and each intersection. Distance, presence / absence of traffic lights at each intersection, intersection angle at each intersection (road connection angle), road information for each branch (road type (national road, prefectural road, etc.), route number, road width, number of lanes, etc.) The vehicle's travel route information (road type, route number, road width, number of lanes, etc.) is obtained (hereinafter, this information is referred to as navigation information). In addition, by incorporating DGPS (differential GPS) in the car navigation device 3, it is possible to receive correction data of FM multiplex broadcasting, correct GPS position information, and improve positioning accuracy.

  The traveling state detection device 4 is an autonomous navigation that includes, for example, a vehicle speed sensor that detects the vehicle speed of the host vehicle, an acceleration sensor that detects acceleration, a yaw rate sensor that detects yaw rate, a gyrometer that detects the traveling direction (direction) of the host vehicle, and the like. Sensors such as devices, and switches such as an ignition switch, a hazard switch, a brake switch, and a winker switch that output an on / off signal, and the ECU 5 obtains the traveling state information of the own vehicle from these sensors and switches. .

  The ECU 5 is a computer having a CPU 51, a RAM 52, and a ROM 53 as basic configurations. The ROM 53 will be described later using a communication program for exchanging information between different vehicles by the inter-vehicle communication device 2, other vehicle information, navigation information, traveling state information, and the like acquired via the inter-vehicle communication device 2. Stores a program that predicts traffic jams and provides information to the driver through images and sounds.

  In addition to navigation information and traveling state information regarding the position, speed, traveling direction (direction), etc. of the own vehicle, the ECU 5 determines the vehicle size (full length, full width, etc.) of the own vehicle and the type of vehicle (large vehicle, passenger car, emergency vehicle). Etc.) including the unique identification (ID) information (transmission source information) and the ID information (transmission destination information) of the other vehicle with respect to the other vehicle existing within a predetermined vehicle-to-vehicle communication range. 2 (hereinafter, this information is referred to as own vehicle information). Similarly, the ECU 5 receives distribution information related to other vehicles (hereinafter referred to as other vehicle information) from other vehicles.

  In the inter-vehicle communication according to the present embodiment, a broadcast communication method (broadcast method) that enables simultaneous delivery to a plurality of vehicles is applied, but a multicast method that specifies a transmission source and a destination vehicle by ID information is applied. May be.

  Further, the inter-vehicle communication of the present embodiment has a communication interval of about 0.1 second, and information is distributed for grasping as a parked vehicle even when the ignition switch of the vehicle is off. However, in order to save power, it is set longer than the communication interval when the ignition switch is turned on.

  In addition, when an infrastructure device (for example, a beacon used for road-to-vehicle communication) is provided at an intersection on the road surface or in the vicinity of the intersection, the vehicle is used by using the infrastructure device provided near the vehicle. Can also distribute its own vehicle information to other nearby vehicles.

  In the present embodiment, information is provided by using the display 33 and the speaker 34 of the car navigation device 3. For example, a head-up display, a buzzer that emits an alarm sound, or a driver is seated. You may use the sheet vibrator etc. which vibrate a sheet | seat.

  Further, the vehicle is provided with, for example, a CCD camera that images the front of the traveling path of the own vehicle that monitors the surroundings of the own vehicle, a laser radar that measures the distance between the front vehicle and the clearance sonar using ultrasonic waves, The ECU 5 may use the information obtained from these cameras and radars to monitor other vehicles that are traveling in front of the host vehicle or parked in front of the host vehicle and perform traffic jam prediction.

  FIG. 2 is a functional block diagram of an ECU that realizes the driving support system of the present embodiment.

  In FIG. 2, 5A is a traffic jam cause detection block for detecting the occurrence of the traffic jam cause from other vehicle information. 5B is a traffic density calculation block for calculating the traffic density from the vehicle information existing on the route where the cause of the traffic jam has occurred and the road information of the route. 5C is an information providing block that provides traffic information to the driver.

[Congestion prediction processing]
3A and 3B are diagrams for explaining the outline of the traffic jam prediction process of the present embodiment.

  In this embodiment, as shown to Fig.3 (a), the stop vehicle (or parking vehicle) which causes traffic congestion is detected from the other vehicle information acquired by the inter-vehicle communication, and exists on the route where this stop vehicle exists. A traffic jam is predicted by calculating the traffic density after a predetermined time on the route from various information such as the number of other vehicles, the number of lanes, and the width.

  Further, as shown in FIG. 3B, at the time when the vehicle arrives at the section where the traffic jam is predicted, it is predicted based on the traffic density whether the traffic jam has occurred or has been eliminated, and the vehicle Provides information on traffic jams when they encounter traffic jams.

  FIG. 4 is a flowchart showing a traffic jam prediction process by the vehicle driving support system of the present embodiment.

  In FIG. 4, first, the ECU 5 identifies the cause of the traffic jam (S1). Here, for example, the stopped vehicle is identified as the cause of the traffic jam from information such as the brake switch included in the other vehicle information being ON, the hazard switch being ON, the vehicle position (road shoulder position), and the vehicle speed being zero. Further, when an airbag is deployed due to an accident or the like, the accident vehicle can be identified as a cause of traffic congestion by transmitting airbag deployment information included in other vehicle information.

  Next, the ECU 5 calculates the number of other vehicles present in the vicinity of the cause of the traffic jam from the other vehicle information acquired by inter-vehicle communication (S3).

  Next, the ECU 5 determines the number of vehicles on the route where the cause of the traffic jam (vehicle) exists, the average speed, the number of lanes and the width of the route acquired from the map DB 35, the number of intersections, intersection information (only for turning right and left, for traveling straight, etc.) ) To calculate the traffic density after a predetermined time on the route (S5). Details will be described later.

  Next, the ECU 5 predicts the occurrence time and resolution time of the traffic jam on the route and the traffic jam distance (traffic zone) from the traffic density (S7). Details will be described later.

  Next, the ECU 5 calculates the time when the host vehicle reaches the traffic jam section (S9). This is obtained by adding the current time and the value obtained by dividing the distance to the traffic jam section by the average speed of the vehicle.

  Then, the ECU 5 determines whether there is traffic jam on the route at the time when the vehicle reaches the traffic jam section (S11), and provides traffic jam information when it is judged that the vehicle encounters traffic jam ( S13).

  Note that, along with the provision of information in S13, a route search for avoiding traffic jams may be performed by the car navigation device 3, and route guidance for avoiding traffic jams may be executed.

  According to the traffic jam prediction process, it is possible to quickly and accurately perform traffic jam prediction even when an event that causes traffic jam occurs unexpectedly by grasping the status of other vehicles in real time by inter-vehicle communication. . In addition, the vehicle can be notified in advance whether or not a traffic jam will be encountered.

[Calculation of traffic density]
Next, the traffic density calculation method in S5 of FIG. 4 will be described.

  FIG. 5 is a diagram for explaining the traffic density calculation method in S5 of FIG.

  First, if A is defined as the current traffic density, B as the rate of increase in traffic density, and C as the rate of decrease in traffic density, the future traffic density Dens is given by the following equation.

Dens = A + B-C
The current traffic density A is given by the following equation.

A = Nv / (L × m)
The traffic density increase rate B is given by the following equation.

  Where Ri is the amount of inflow from each intersection of the route L per unit time, Si is the inflow coefficient at each intersection of the route L, V is the average speed of vehicles existing on the route, u (0 <u <1) Represents an increase coefficient, respectively.

  Here, the inflow coefficient Si is a correction coefficient for excluding a vehicle that may flow into the lane opposite to the host vehicle on the route L from the inflow amount Ri from each intersection of the route L. The inflow coefficient Si is appropriately set in the range of 0 <Si <1, depending on the type of intersection (only for turning right and left, or only for going straight).

  U is a value uniquely determined by the number of lanes of the route L, the number of vehicles, and the average speed.

  The first term in the above formula represents the number of vehicles entering the route L from each intersection, and the second term represents the number of vehicles entering the route L from the rear.

  Next, the traffic density reduction rate C is given by the following equation.

C = (Nv × V × t) / (L × m)
However, t represents an outflow coefficient for calculating the number of vehicles leaving the route L, and is appropriately set within a range of 0 <t <1. For example, a state where a vehicle causing traffic congestion is blocking one lane on the route L (t = 0.5), a state where all traffic lanes are blocked (t = 0), It is set as in a stopped state (t = 0.75).

  To summarize the above, the traffic density Dens [number / area / time] is given by the following equation.

  The number of vehicles flowing into and out of the route L is the vehicle position of the other vehicle on the branch road connected to the intersection of the route L and the indicated direction of the turn signal, as other vehicle information acquired by inter-vehicle communication, Or it can also detect from the route guidance information by the car navigation apparatus of the other vehicle on the said branch road.

  In this way, it is possible to perform highly accurate traffic jam prediction using the traffic density in consideration of vehicles flowing into and out of the route where the traffic jam has occurred.

[Calculation of congestion distance]
Next, a method for predicting the occurrence time of the traffic jam and the traffic jam distance in S7 of FIG. 4 will be described.

  Here, the congestion distance after T time is predicted.

  First, the number of vehicles included in the route L after time T is obtained by the following equation.

  Here, as shown in FIG. 6, it is known that there is a proportional relationship between the traffic capacity (route length L × number of lanes m) and the maximum allowable number.

  Therefore, after the time T, the number of vehicles included in the route L is obtained, and if the number of vehicles is in the traffic jam area of FIG. 6 as the traffic capacity, it is predicted that traffic jam will occur, and if it is in the traffic jam area, the traffic jam is resolved. To do.

  Here, by adding T to the current time, it is possible to predict the occurrence time of traffic jams or the time of cancellation of traffic jams, and the vehicle encounters traffic jams from the arrival time of the vehicle's route L and the occurrence time or resolution time of traffic jams. It is possible to judge with accuracy.

It is a block diagram which shows the structure of the driving assistance system of embodiment which concerns on this invention. It is a functional block diagram of ECU which implement | achieves the driving assistance system of this embodiment. It is a figure explaining the outline | summary of the traffic congestion prediction process of this embodiment. It is a flowchart which shows the traffic congestion prediction process by the vehicle driving assistance system of this embodiment. It is a figure explaining the calculation method of the traffic density in S5 of FIG. It is a figure which shows the relationship between traffic capacity and a maximum permissible number.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Driving assistance system 2 Inter-vehicle communication apparatus 3 Car navigation apparatus 4 Running condition detection apparatus 5 ECU
21 Transmission / reception antenna 31 GPS antenna 32 GPS receiver 33 Display 34 Speaker 35 Map DB
51 CPU
52 RAM
53 ROM

Claims (6)

Map data storage means for storing map data;
Vehicle-to-vehicle communication means for transmitting and receiving vehicle information between other vehicles;
Own vehicle state detecting means for detecting the traveling state of the own vehicle;
A traffic jam cause detection means for detecting the occurrence of the traffic jam cause,
The area of the route of the number of vehicles existing on the route where the cause of the traffic jam occurs after a predetermined time from the other vehicle information obtained by the inter-vehicle communication means and the road information of the route where the traffic jam cause occurred obtained from the map data And a traffic density calculating means for calculating a traffic density representing a ratio to the vehicle driving support system. The road information includes intersection information of a route in which the cause of the traffic jam occurs,
2. The vehicle driving support system according to claim 1, wherein the traffic density is calculated using a current traffic density and a number of vehicles flowing into and out of the route causing the traffic jam. .   The number of vehicles flowing into and out of the route causing the traffic jam is detected from the position of the vehicle on the branch road connected to the intersection of the route causing the traffic jam and the direction of the turn signal, or route guidance information on the branch road. The vehicle driving support system according to claim 2, wherein:   4. The vehicle driving support system according to claim 3, wherein the number of vehicles flowing into and out of the route in which the cause of the traffic jam occurs is corrected by a coefficient that varies depending on the traffic jam cause. A traffic time prediction means for predicting the occurrence time of traffic jam or the cancellation time of traffic jam from the traffic density;
An arrival time calculating means for calculating a time at which the own vehicle reaches the route on which the cause of the traffic congestion has occurred;
Judgment means for judging whether the own vehicle encounters traffic jam from the arrival time of the own vehicle and the occurrence time or the cancellation time of the traffic jam,
The vehicle driving support system according to claim 1, further comprising information providing means for providing information on traffic jam when it is determined that the traffic jam is encountered.   The occurrence or elimination of the traffic jam is determined by whether or not the number of vehicles existing on the route causing the traffic jam after a predetermined time exceeds the maximum allowable number determined from the area of the route causing the traffic jam. The vehicle driving support system according to claim 5.

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