JP5903985B2 - Method for evaluating driving behavior induced by traffic congestion - Google Patents

Description

  The present invention relates to a method for evaluating driving behavior induced by a traffic jam.

  There is a demand for managing the traveling state of a vehicle traveling on a predetermined road and suppressing the occurrence of traffic congestion safely and effectively. Therefore, it is required to correctly evaluate the driving behavior that causes the traffic jam.

The cause of traffic congestion occurs when the number of vehicles traveling on a road exceeds the traffic capacity of that road. On the other hand, there is a case where traffic congestion occurs even though the traffic capacity is below. One of the causes is the driver's unintentional deceleration behavior, and it is known that the deceleration of the preceding vehicle propagates to the rear vehicle while increasing the deceleration (deceleration propagation) to a group of vehicles with a short inter-vehicle distance. It has been. A speed reduction notification service has been proposed that prompts the driver (driver) to properly reduce the inter-vehicle distance for the problem of traffic congestion due to the deceleration propagation phenomenon.

  In this speed reduction notification service, when deceleration of the own vehicle is detected at a traffic jam frequent spot, this is detected as traffic jam induction behavior and notified to the driver. Here, the distance between the preceding vehicle and the following vehicle is acquired, and (1) when the distance to the preceding vehicle is not less than a predetermined value, (2) only when the distance between the following vehicle is not more than a certain value The traffic congestion-inducing behavior is detected. This excludes (1-1) the case where the distance from the preceding vehicle is short and the vehicle must be decelerated, and (2-1) the case where the distance from the vehicle behind is too long and the deceleration of the host vehicle does not induce traffic jams. be able to.

JP 2008-222123 A JP 2009-151562 A JP-A-10-205367 JP 2006-039806 A

“Reduction of Sag Traffic Congestion by Optimizing Lane Utilization” (Civil Engineering Data, 47 (10), 38-43, 2005-10, Civil Engineering Research Center) ”http://www.nilim.go.jp/english /its/3paper/pdf/051201dogishi_3.pdf ”

  However, when a predetermined condition is set only by using the inter-vehicle distance as in the method of the speed reduction notification service described above, the same inter-vehicle distance condition is different, but the risk level with the preceding vehicle and the traffic congestion inducing behavior to the rear vehicle are different. The state cannot be distinguished. Therefore, it cannot be accurately evaluated whether deceleration is an action that is naturally performed for safety or an unnecessary and traffic congestion-inducing action that should be avoided.

  According to the embodiment, a traffic jam-inducing driving behavior evaluation method that accurately evaluates whether the deceleration behavior is a traffic jam-inducing behavior is realized.

  According to the first aspect, there is provided a traffic jam-inducing driving behavior evaluation method for evaluating the degree of incentive of deceleration behavior to traffic jam. According to the method for evaluating driving behavior that induces traffic congestion, it is detected that the host vehicle has decelerated, the presence of the preceding vehicle and the rear vehicle is determined when the deceleration of the host vehicle is detected, and the presence of the preceding vehicle and the rear vehicle is confirmed. In this case, travel information including at least the speed and acceleration of the preceding vehicle, the host vehicle, and the subsequent vehicle is acquired. In addition, the vehicle's minimum deceleration is calculated from the travel information related to the preceding vehicle and the vehicle, and the vehicle's minimum deceleration is compared with the vehicle's deceleration. Determine. If the host vehicle deceleration is a traffic jam-inducing behavior, the minimum rear vehicle deceleration is calculated from the travel information related to the rear vehicle and the host vehicle, and the traffic congestion incentive for the subsequent vehicle of the host vehicle is calculated using the rear vehicle minimum deceleration. Calculate the degree.

  According to the traffic congestion-inducing driving behavior evaluation method of the first aspect, it is possible to accurately evaluate whether the deceleration behavior is a traffic congestion-inducing behavior, and the evaluation results can be used for various purposes.

FIG. 1 is a diagram for explaining a problem when a deceleration action is evaluated based on the head time of a preceding vehicle. (A) illustrates the relationship between the preceding vehicle and the own vehicle, and (B) is under different conditions. It is a table | surface which shows the potential collision margin distance. FIG. 2 is a diagram for explaining a method of calculating a potential collision margin distance. FIG. 3 is a diagram for explaining a problem in the case where the deceleration action is evaluated by the head time with the rear vehicle. (A) illustrates the relationship between the rear vehicle and the own vehicle, and (B) is under different conditions. It is a table | surface which shows the potential collision margin distance. FIG. 4 is a diagram illustrating an example of a vehicle that acquires the traveling speed and acceleration of a preceding vehicle and a rear vehicle. FIG. 5 is a diagram illustrating a configuration example of the in-vehicle device, and illustrates only a portion related to the traffic congestion-inducing driving behavior evaluation device. FIG. 6 is a diagram illustrating an example of a system configuration in which travel information of other vehicles can be collected using a communication terminal. FIG. 7 is a functional block diagram of the traffic jam-inducing driving behavior evaluation apparatus. FIG. 8 is a diagram illustrating a structure example of a travel information DB that stores data. FIG. 9 is a diagram showing data items used in the first embodiment in the travel information DB, and shows how data is updated in one processing cycle. FIG. 10 is a flowchart showing a processing operation in the congestion-inducing driving behavior evaluation device of the first embodiment. FIG. 11 is a flowchart showing the processing operation in the congestion-inducing driving behavior evaluation apparatus of the first embodiment. FIG. 12 is a flowchart illustrating a processing operation in the traffic jam-inducing driving behavior evaluation apparatus according to the first embodiment. FIG. 13 is a diagram illustrating a calculation example in the first embodiment when the vehicle's minimum deceleration is obtained under two different conditions and it is determined whether or not it is an object to be evaluated as a traffic jam-inducing action. FIG. 14 is a diagram illustrating a calculation example in the first embodiment in which it is evaluated how much congestion induces the deceleration of the own vehicle in the rear vehicle under two different conditions. FIG. 15 is a flowchart illustrating a processing operation in the traffic jam-inducing driving behavior evaluation apparatus according to the second embodiment. FIG. 16 is a flowchart illustrating a processing operation in the traffic jam-inducing driving behavior evaluation apparatus according to the second embodiment. FIG. 17 is a flowchart illustrating a processing operation in the traffic jam-inducing driving behavior evaluation apparatus according to the second embodiment. FIG. 18 shows the calculation when determining whether or not the vehicle's minimum deceleration and the vehicle's maximum deceleration are to be evaluated as traffic congestion-inducing behaviors under two different conditions in the second embodiment. It is a figure which shows an example. FIG. 19 is a diagram illustrating a calculation example in the second embodiment in which it is evaluated how much congestion induces the deceleration of the own vehicle in the rear vehicle under two different conditions. FIG. 20 is a diagram illustrating a calculation example in the third embodiment in which it is evaluated how much congestion induces the deceleration of the own vehicle in the rear vehicle under two different conditions.

  Up to now, the distance between the preceding vehicle and the rear vehicle and the traveling speed of the host vehicle and the rear vehicle are obtained, and the vehicle head time obtained by dividing the inter-vehicle distance by the traveling speed is calculated to evaluate whether the deceleration action is a congestion-inducing action. It has been proposed to do. According to this method, the congestion-inducing behavior detection is performed only when (1) the vehicle head time with the preceding vehicle is greater than or equal to a predetermined value and (2) the vehicle head time with the rear vehicle is less than or equal to a predetermined value. When the vehicle deceleration is detected at a traffic jam occurrence point set by a predetermined method, this method detects the traffic jam inducing action and notifies the driver of the traffic jam inducing action. As a result, (1-1) the case where the distance to the preceding vehicle is short and the vehicle must be decelerated, and (2-1) the case where the distance from the rear vehicle is long and the deceleration of the host vehicle does not induce traffic jams are excluded. be able to.

In the above method, the vehicle head time with the preceding vehicle and the vehicle head time with the rear vehicle are used. However, the risk level with the preceding vehicle and the traffic congestion-inducing behavior to the rear vehicle cannot be accurately evaluated.
Before describing the embodiment, problems in the case where the deceleration action is evaluated by the vehicle head time with the preceding vehicle and the vehicle head time with the rear vehicle will be described.

FIG. 1 is a diagram for explaining a problem when a deceleration action is evaluated based on the head time of a preceding vehicle. (A) illustrates the relationship between the preceding vehicle and the own vehicle, and (B) is under different conditions. It is a table | surface which shows the potential collision margin distance. In the table, two different conditions are shown, and the case where the traveling speed is represented by km / h is shown above each condition, and the case where the traveling speed is represented by m / s is shown below.
FIG. 2 is a diagram for explaining a method of calculating a potential collision margin distance.

  As shown in FIG. 1A, it is assumed that the preceding vehicle 10a travels on the road at a speed Va, and the vehicle 10b travels behind the distance D, that is, the inter-vehicle distance D, at the speed Vb. .

  In the above method, when the vehicle head time is 3 seconds or less, it is evaluated that the deceleration action is not a traffic congestion inducing action. Therefore, the case of Condition 1 and Condition 2 where the vehicle head time is 2.0 seconds will be examined. Condition 1 is an inter-vehicle distance D of 33 m, Va = 60 km / h (16.7 m / s), and Vb = 60 km / h (16.7 m / s). Condition 2 is an inter-vehicle distance D of 50 m, Va = 60 km / h (16.7 m / s), and Vb = 90 km / h (25.0 m / s). The vehicle head time in the case of condition 1 is (33 m) / (16.7 m / s) = 2.0. The vehicle head time in the case of Condition 2 is (50 m) / (25.0 m / s) = 2.0.

  Here, the potential collision margin distance under condition 1 and condition 2 is calculated. As shown in FIG. 2, the potential collision margin distance represents a potential danger of rear-end collision, that is, a margin for risk, assuming a follow-up traveling time. First, it is assumed that the preceding vehicle has suddenly braked and the own vehicle driver has applied the brake after a reaction time of T seconds, and the distance between the preceding vehicle stop position and the own vehicle stop position is set as a collision margin distance. In this case, since the preceding vehicle is not braked, it becomes a marginal distance for a potential collision.

A formula for calculating the potential collision margin distance will be described. Preceding vehicle is traveling at a speed V _F, and the vehicle is traveling at a speed V, vehicle distance is assumed to be D _F. Here, in order to avoid danger, the preceding vehicle performs maximum deceleration (rapid braking) at acceleration −α, and the driver of the own vehicle delays by the reaction time T with respect to the sudden deceleration of the preceding vehicle, and maximum deceleration at acceleration −α. Suppose that (sudden braking) was performed. The distance traveled by the preceding vehicle from the start of the maximum deceleration to the stop is V _F ² / 2α, the distance the host vehicle travels during the reaction time T is V × T, and the host vehicle decelerates the maximum. The distance traveled from the start to the stop is V ² / 2α. Therefore, the inter-vehicle distance D when the preceding vehicle and the host vehicle are stopped is D = D _F −V × T + (V _F ² −V ² ) / 2α. This inter-vehicle distance D is a potential collision margin distance, which is a distance remaining when the host vehicle performs maximum deceleration with respect to the maximum deceleration (rapid braking) of the preceding vehicle. If the potential collision margin distance is negative, it means that the possibility of rear-end collision is increased.

  The potential collision margin distance indicates how much the driver is aware of the danger of a potential preceding vehicle, and a driver who is preparing to respond to the risk has a long potential collision margin distance. On the other hand, it is considered that a driver with a short potential collision margin is not ready for a potential risk. However, in order to suppress the smooth running of the road, that is, the occurrence of traffic congestion, it is not preferable that the potential collision margin distance is longer than necessary, and it is desirable that the appropriate potential collision margin distance is maintained for each vehicle. .

  The potential collision margin distance calculated for the above conditions 1 and 2 is shown in FIG. As shown in the figure, even if the same vehicle head time is 2.0 seconds, the potential collision margin distance is 22 m in the case of the condition 1 and 3 m in the case of the condition 2 and is greatly different. In the case of condition 1, the potential collision margin distance has a margin of 22 m, whereas in the case of condition 2, the potential collision margin distance has a margin of 3 m. As described above, according to the above method, two different conditions are equally evaluated as not traffic jam-inducing behavior. One is a case where the potential collision margin distance is 3m and there is no margin, and the evaluation is considered to be appropriate, but the other is a case where the potential collision margin distance is 22m and there is a margin. It is not reasonable to evaluate. As described above, it is problematic to evaluate the condition that the collision margin with the preceding vehicle is not equal to the traffic congestion inducing action.

  FIG. 3 is a diagram for explaining a problem in the case where the deceleration action is evaluated by the head time with the rear vehicle. (A) illustrates the relationship between the rear vehicle and the own vehicle, and (B) is under different conditions. It is a table | surface which shows the potential collision margin distance. In the table, two different conditions are shown, and the traveling speed is represented by km / h. The calculation method of the potential collision margin distance in FIG. 3B is the same as the method described in FIG.

  As shown in FIG. 3A, it is assumed that the host vehicle 10b travels on the road at a speed Vb and is behind the distance D, that is, the inter-vehicle distance D, and the rear vehicle 10c travels at the speed Vc. .

  In the above method, when the vehicle head time is 10 seconds or less, it is evaluated that the deceleration action of the own vehicle does not become a traffic jam induction action. Therefore, the cases of Condition 3 and Condition 4 where the vehicle head time is 3.0 seconds are examined. Condition 3 is an inter-vehicle distance D of 50 m, Vb = 60 km / h (16.7 m / s), and Vc = 60 km / h (16.7 m / s). Condition 4 is an inter-vehicle distance D of 83 m, Vb = 60 km / h (16.7 m / s), and Vc = 100 km / h (27.8 m / s). The vehicle head time in condition 3 is (50 m) / (16.7 m / s) = 3.0. The vehicle head time in condition 4 is (83 m) / (27.8 m / s) = 3.0.

  The potential collision margin distances under conditions 3 and 4 calculated by the above calculation method were 38 m and 22 m, as shown in FIG. Even under the condition of the same vehicle head time = 3 seconds, condition 3 has a potential margin distance of 38 m, and condition 4 has a potential margin distance of 22 m, which is almost double. Here, when the own vehicle decelerates at the same deceleration, it is determined that traffic congestion-inducing behavior is the same in the case of condition 3 with a margin with the rear vehicle and the condition 4 with a small margin with the rear vehicle. Has a problem.

  As described above, the risk level with the preceding vehicle and the traffic congestion-inducing behavior to the following vehicle cannot be accurately evaluated only by using the heading time with the preceding vehicle and the heading time with the rear vehicle. In the embodiments described below, a method and an apparatus for evaluating a traffic jam-inducing driving behavior that can more accurately evaluate the incentive of occurrence of a traffic jam in a deceleration behavior are disclosed.

  The traffic congestion-inducing driving behavior evaluation apparatus according to the first embodiment is mounted on a vehicle, for example, and a vehicle equipped with the traffic congestion-inducing driving behavior evaluation apparatus is the host vehicle. In addition to detecting the traveling speed and acceleration of the own vehicle, the own vehicle acquires the traveling speed and acceleration of the preceding vehicle and the rear vehicle, and the congestion-inducing driving behavior evaluation device is based on the traffic-inducing driving behavior. Or evaluate the degree of incentive to the traffic jam. Therefore, the own vehicle needs to acquire the traveling speed and acceleration of the preceding vehicle and the rear vehicle. In the second embodiment to be described later, the distance between the preceding vehicle and the rear vehicle is also acquired.

  FIG. 4 is a diagram illustrating an example of a vehicle that acquires the traveling speed and acceleration of a preceding vehicle and a rear vehicle. As shown in FIG. 4, the vehicle 10 includes a front radar device 12 that measures the relative speed of the front vehicle with respect to the own vehicle and a rear radar device 13 that measures the relative speed of the rear vehicle with respect to the own vehicle. ing. The speed of the target vehicle can be obtained by measuring the relative speed with the target vehicle with the radar device and adding it to the own vehicle speed. Furthermore, the relative acceleration of the target vehicle can be acquired by measuring the relative speed of the target vehicle twice in a short time with the radar device and dividing the change by the time. In general, some laser devices can measure the distance to the target vehicle, and some directly detect relative acceleration. In some cases, the target vehicle is not a single vehicle, and the relative speed and the inter-vehicle distance of a plurality of vehicles can be detected. The traveling speed and acceleration of the own vehicle can be measured with a speedometer and an accelerometer installed in the own vehicle. As described above, in addition to detecting the traveling speed and acceleration of the own vehicle, the own vehicle acquires the relative speed and relative acceleration of the preceding vehicle and the rear vehicle.

  In recent years, vehicles such as automobiles are equipped with a large number of electronic devices such as sensors, actuators, control devices, etc., which are connected by an in-vehicle LAN to collect data detected by a plurality of sensors, and the entire vehicle An in-vehicle device that integrally controls the vehicle has been proposed. In-vehicle LAN standards have also been proposed. It is desirable that the vehicle equipped with the traffic congestion-inducing driving behavior evaluation apparatus of the first embodiment is also equipped with such an in-vehicle apparatus, and the traffic congestion-inducing driving behavior evaluation apparatus is formed as a part of the in-vehicle apparatus. Hereinafter, a case where the traffic congestion-inducing driving behavior evaluation device is formed as a part of the in-vehicle device will be described as an example.

  FIG. 5 is a diagram illustrating a configuration example of the in-vehicle device, and illustrates only a portion related to the traffic congestion-inducing driving behavior evaluation device.

  The in-vehicle device includes an arithmetic device 21, a preceding vehicle speed measuring device 22, a rear vehicle speed measuring device 23, a speed sensor 24, an acceleration sensor 25, a display device 26, a car navigation device 27, and a GPS sensor 28. , And a LAN signal path 29. The preceding vehicle speed measuring device 22 and the rear vehicle speed measuring device 23 correspond to the front radar device 12 and the rear radar device 13 in FIG. 4, but are not limited to the radar device, and the relative speeds of the preceding vehicle and the rear vehicle are the same. Anything can be used as long as it can be measured. It is desirable that the preceding vehicle speed measuring device 22 and the rear vehicle speed measuring device 23 can also measure the distance between the preceding vehicle and the rear vehicle. The traffic congestion-inducing driving behavior evaluation device is realized by a program on the arithmetic device 21, that is, a computer. Since each part of FIG. 5 is widely known, further description is omitted.

  FIG. 6 is a diagram illustrating an example of a system configuration in which travel information of other vehicles can be collected using a communication terminal such as a smartphone that has begun to spread in recent years. Vehicles 10 </ b> X- 10 </ b> Z are equipped with an in-vehicle device 20 that can connect the communication terminal 30. The communication terminal 30 is, for example, a communication terminal carried by a driver (driver). When the driver gets on the vehicle, the driver connects the communication terminal 30 to the connection connector of the in-vehicle device 20. In response to this, the in-vehicle device 20 sets the communication terminal 30 in a state in which the communication terminal 30 can always communicate with the travel management center 100. The communication terminal 30 is from the in-vehicle device 20. It receives information on the travel position of the host vehicle (position detected by the GPS sensor 28), travel speed (speed measured by the speed sensor 24), and acceleration (acceleration measured by the acceleration sensor 24), and transmits the information to the travel management center 100. . The travel management center 100 can detect the positional relationship between the preceding vehicle and the rear vehicle from the traveling position of each vehicle, and therefore transmits information on the speed and acceleration of the preceding vehicle and the rear vehicle to each vehicle. In this case, each vehicle does not need to have the preceding vehicle speed measuring device 22 and the rear vehicle speed measuring device 23.

In the system as shown in FIG. 6, a traffic congestion incentive driving behavior evaluation device may be provided in the travel management center 100 to evaluate the travel of each car.
Furthermore, when the car navigation device 27 has a communication function, or when the in-vehicle device 20 itself has a communication function, it is possible to construct a system as shown in FIG. 6 without the communication terminal 30. In the embodiment described below, the case where the in-vehicle device has the preceding vehicle speed measuring device 22 and the rear vehicle speed measuring device 23 as shown in FIG. 5 will be described as an example, but the same applies to the case of the system shown in FIG. Applicable.

  FIG. 7 is a functional block diagram of the traffic jam-inducing driving behavior evaluation apparatus. As described above, the congestion-induced driving behavior evaluation device is realized by a program on the arithmetic device 21, that is, a computer.

  The traffic congestion-inducing driving behavior evaluation device includes a preceding vehicle relative speed acquisition unit 31, a preceding vehicle acceleration detection unit 32, a host vehicle speed acquisition unit 33, a host vehicle acceleration acquisition unit 34, a rear vehicle relative speed acquisition unit 35, A data storage unit 36, a travel position acquisition unit 37, and a heavy traffic jam section determination unit 38 are included. The congestion-inducing driving behavior evaluation apparatus further includes a congestion-inducing behavior determining unit 41 and a congestion-inducing factor determining unit 42. Although not used in the first embodiment, when the preceding vehicle speed measuring device 22 and the rear vehicle speed measuring device 23 can measure the inter-vehicle distance, the preceding vehicle distance acquisition unit 39 and the rear vehicle distance are used. It is desirable to have the acquisition unit 40.

  The preceding vehicle relative speed acquisition unit 31 periodically reads the relative speed of the preceding vehicle measured by the preceding vehicle speed measuring device 22, sends it to the preceding vehicle acceleration detection unit 32, and stores it in the data storage unit 36. The preceding vehicle acceleration detection unit 32 calculates the relative acceleration of the preceding vehicle from the change in the relative speed of the preceding vehicle and stores it in the data storage unit 36. The own vehicle speed acquisition unit 33 periodically reads the own vehicle speed measured by the speed sensor 24 and stores it in the data storage unit 36. The own vehicle acceleration detection unit 34 periodically reads the acceleration of the own vehicle measured by the acceleration sensor 25 and stores it in the data storage unit 36. If only the speed sensor 24 is mounted and the acceleration sensor 25 is not mounted, the acceleration can be calculated from the change in speed. The rear vehicle relative speed acquisition unit 35 periodically reads the rear vehicle relative speed measured by the rear vehicle speed measurement device 23. Although not shown, it is also possible to provide a rear vehicle acceleration detection unit and calculate the relative acceleration of the rear vehicle from the change in the relative speed of the rear preceding vehicle. The preceding vehicle distance acquisition unit 39 and the rear vehicle distance acquisition unit 40 periodically read the inter-vehicle distance between the preceding vehicle and the rear vehicle measured by the preceding vehicle speed measurement device 22 and the rear vehicle speed measurement device 23, and the data storage unit 36. To remember.

  The data storage unit 36 stores the data acquired by the preceding vehicle relative speed acquisition unit 31, the preceding vehicle acceleration detection unit 32, the host vehicle speed acquisition unit 33, the host vehicle acceleration acquisition unit 34, and the rear vehicle relative speed acquisition unit 35 in a database format. Remember. The data storage unit 36 further stores the inter-vehicle distance between the preceding vehicle and the rear vehicle acquired by the preceding vehicle distance acquisition unit 39 and the rear vehicle distance acquisition unit 40 in a database format. Although not shown, the data storage unit 36 also stores the position of the host vehicle detected by the GPS sensor 28, the travel distance of the host vehicle, and the like. The data storage unit 36 stores these data in a database (DB) format, and deletes old data and updates it by writing the latest data for each minimum time unit for reading the sensor output via the in-vehicle LAN. .

FIG. 8 is a diagram showing an example of the structure of a travel information DB that stores the above data. The travel information DB includes items as illustrated, but actually includes more items.
FIG. 9 is a diagram showing data items used in the first embodiment in the travel information DB, and shows how data is updated in one processing cycle.

  The data storage unit 36 further stores digital map information (map), and the digital map information includes a heavy traffic jam area map indicating a heavy traffic jam section. The heavy traffic jam section map is data that predetermines sections where traffic jams frequently occur based on traffic statistical information, and is stored in the data storage unit 36 as described above. Note that, as the heavy traffic jam area map, information for determining whether the section is a heavy traffic jam section in the time zone may be acquired by communication or the like.

  The travel position acquisition unit 37 reads the current position detected by the GPS sensor 28 and sends it to the heavy traffic jam section determination unit 38. The heavy traffic jam section determination unit 38 determines whether or not the current position enters the heavy traffic jam area of the map stored in the data storage unit 36. If so, the traffic jam triggering behavior determination unit 41 is activated. Makes the traffic jam inducing behavior determination unit 41 non-operating. In the first embodiment, the traffic jam inducing behavior determination process is performed only when the vehicle is traveling in a traffic jam frequent section, and the process is not performed even if there is deceleration in other sections. However, in 1st Embodiment, it is not limited to this, It is also possible to always perform traffic congestion inducement driving action evaluation processing.

  The traffic jam inducing action determination unit 41 determines whether the deceleration action is a braking action inevitable for safety, in other words, a traffic jam inducing action based on the speed and acceleration of the preceding vehicle and the speed and acceleration of the host vehicle. . When it is determined that deceleration is a traffic congestion-inducing action, the traffic congestion incentive degree determination unit 42 determines the traffic congestion incentive degree of deceleration from the speed and acceleration of the preceding vehicle, the speed and acceleration of the host vehicle, and the speed of the rear vehicle. .

Next, the processing operation in the traffic congestion-inducing driving behavior evaluation device of the first embodiment will be described.
FIG. 10 to FIG. 12 are flowcharts showing processing operations in the traffic jam-inducing driving behavior evaluation device of the first embodiment.

In step S <b> 11, the traveling position acquisition unit 37 collates information indicating the current position of the vehicle such as the GPS sensor 28 with the digital map information, and specifies a road section where the own vehicle is currently traveling.
In step S12, the heavy traffic jam section determination unit 38 determines whether or not the traveling road segment is a heavy traffic jam section. If YES, go to step S13.

  In step S <b> 13, the host vehicle speed acquisition unit 33 acquires host vehicle deceleration information from the change in the host vehicle speed detected by the speed sensor 24 or the host vehicle acceleration detected by the acceleration sensor 25 via the in-vehicle LAN.

In step S14, the traffic congestion inducing behavior determination unit 41 determines whether the deceleration is greater than or equal to a threshold value. If the deceleration is smaller than the threshold value, the process returns to step S11. Here, deceleration is defined as negative acceleration. That is, if the deceleration is positive, the speed decreases. When the vehicle speed detected by the speed sensor 24 and the vehicle acceleration detected by the acceleration sensor 25 are always stored in the data storage unit 36 at regular intervals, the traffic jam inducing behavior determination unit 41 may Data may be read from 36. Hereinafter, in the case of data reading, all such data access methods are possible.

  In step S15, information is acquired as to whether the rear vehicle speed measuring device 23 detects a rear vehicle, in other words, "no rear vehicle". For example, the rear vehicle speed measuring device 23 outputs a signal indicating “no rear vehicle” when the measurable range is limited and there is no rear vehicle in the range. Further, when the measurable range of the rear vehicle speed measuring device 23 is long, if the inter-vehicle distance from the rear vehicle acquired by the rear vehicle distance acquisition unit 40 is not within a predetermined distance (for example, 100 m), “rear vehicle A signal indicating “none” may be output.

  In step S16, the traffic jam inducing action determination unit 41 determines whether there is a rear vehicle. If there is no rear vehicle, the deceleration does not cause traffic jam, so the process returns to step S11. If there is a rear vehicle, the process proceeds to step S17. move on.

  In step S <b> 17, the rear vehicle relative speed acquisition unit 35 acquires the rear vehicle relative speed and stores it in the travel information DB of the data storage unit 36.

In step S18, the relative speed of the rear vehicle one cycle before is read from the travel information DB.
In step S19, the rear vehicle relative acceleration is calculated from the difference between the relative speeds of the rear vehicle one cycle before this time and stored in the travel information DB.

  In step S <b> 20, the host vehicle speed acquisition unit 33 and the host vehicle acceleration acquisition unit 34 acquire the absolute speed and absolute acceleration of the host vehicle and store them in the travel information DB of the data storage unit 36.

  In step S21, the absolute speed and absolute acceleration of the rear vehicle are calculated from the relative speed and relative acceleration of the rear vehicle acquired in steps S17 and S19 and the absolute speed and absolute acceleration of the host vehicle.

  In step S22, the presence of a preceding vehicle is detected as in step S15.

  In step S23, the traffic congestion inducing behavior determination unit 41 determines whether there is a preceding vehicle. If there is no preceding vehicle, the process proceeds to step S23. If there is a selected vehicle, the process proceeds to step S24.

  In step S24, a predetermined minimum deceleration of the own vehicle when there is no preceding vehicle is set, and the process proceeds to step S31 described later. The minimum deceleration of the host vehicle when there is no preceding vehicle is determined in advance based on, for example, vehicle performance and road form, and is preferably changed according to the situation at the time, for example, the rain condition. .

  In step S <b> 25, the preceding vehicle relative speed acquisition unit 31 acquires the relative speed of the preceding vehicle and stores it in the travel information DB of the data storage unit 36.

In step S26, the preceding vehicle acceleration detection unit 32 reads the relative speed of the preceding vehicle one cycle before from the travel information DB.
In step S27, the preceding vehicle acceleration detection unit 32 calculates the preceding vehicle relative acceleration from the difference in relative speed between the current vehicle and the preceding vehicle one cycle before, and stores it in the travel information DB.

  In step S <b> 28, the host vehicle speed acquisition unit 33 and the host vehicle acceleration acquisition unit 34 acquire the absolute speed and absolute acceleration of the host vehicle and store them in the travel information DB of the data storage unit 36. If the elapsed time from step S20 is small, this step S28 can be omitted.

  In step S29, as in step S21, the absolute speed and absolute acceleration of the preceding vehicle are calculated.

  In step S30, the own vehicle minimum deceleration is calculated. Hereinafter, a calculation method for obtaining the minimum deceleration aomin of the host vehicle with the preceding vehicle absolute speed Vfa, the preceding vehicle absolute acceleration a2, the host vehicle absolute speed Voa, and the host vehicle absolute acceleration aoa will be described in detail. Since the vehicle is decelerating, the host vehicle absolute acceleration aoa is referred to as host vehicle deceleration aoa.

  The own vehicle minimum deceleration aomin is defined as a deceleration that may cause a collision if the deceleration is smaller than this. There are several ways of definition. In the first embodiment, the definition is as follows.

(1) When the host vehicle absolute speed Voa is smaller than the preceding vehicle absolute speed Vfa, there is no collision risk if the speed relationship is maintained, so the host vehicle minimum deceleration aomin = 0 is set.
(2) When the host vehicle absolute speed Voa is larger than the preceding vehicle absolute speed Vfa, and when the host vehicle is decelerated at the host vehicle minimum deceleration aomin, the host vehicle minimum reduction is assumed as the speed of the host vehicle and the preceding vehicle coincide at time t. Define velocity aomin. Here, there are several ways of taking the time t. In the first embodiment, the time t_stop at which the speed of the preceding vehicle becomes 0 when the preceding vehicle deceleration is maintained is adopted.

In this case, aomin = Voa / Vfa * a2.
Of course, the definition method of aomin is not limited to this method.

In step S31, the own vehicle deceleration aoa is compared with the own vehicle minimum deceleration aomin, and the detected deceleration is congested depending on how much the own vehicle deceleration aoa exceeds the minimum vehicle deceleration. Determine if it is an incentive action.
Here, a predetermined threshold is set, and if the excess amount of the own vehicle deceleration aoa with respect to the own vehicle minimum deceleration aomin exceeds this threshold, the own vehicle deceleration action is an excessive deceleration speed and is evaluated as a traffic jam inducing action. Judged to be the target

  On the other hand, if the vehicle speed is smaller than the threshold value, the vehicle deceleration action is not excessive in order to avoid danger with the preceding vehicle. Therefore, the vehicle deceleration action is not considered as a target for evaluating the traffic congestion inducing action.

  In order to evaluate the influence of the own vehicle deceleration on the rear vehicle when the own vehicle deceleration is determined as an evaluation target of the traffic jam-inducing action or when the preceding vehicle does not exist in step S23 but the own vehicle deceleration is detected, Proceed to S32.

In step S32, the rear vehicle minimum deceleration armin is calculated from the own vehicle absolute speed Vfa, the own vehicle absolute acceleration aoa, and the rear vehicle absolute speed Vrr by the same method as the own vehicle minimum deceleration aomin.
In this case, armin = Vfa / Vrr * aoa.

  In step S33, a threshold value for the rear vehicle minimum deceleration armin is set. The threshold is arbitrarily set.

  In step S34, it is determined whether the rear vehicle minimum deceleration armin exceeds the set threshold value. If not, the process proceeds to step S35. Proceed and determine that the traffic is congested. In the case of traffic jam inducing driving, the determination result is stored in the travel information DB of the data storage unit 36.

  FIG. 13 shows an example of calculation in the first embodiment in the case of determining whether or not the vehicle minimum deceleration aomin is obtained under two different conditions P and Q and evaluated as a traffic jam-inducing action. FIG. 13A illustrates the relationship between the preceding vehicle and the host vehicle, and FIGS. 13B and 13C are tables illustrating calculation examples under the conditions P and Q. FIG.

As shown in FIG. 13A, the preceding vehicle 10a travels at a speed Va on an uphill road that is a heavy traffic jam section, and the host vehicle 10b travels at a speed Vb at an inter-vehicle distance D. Assume that the car decelerates at a2. Condition P is Va = 70 km / h (19.4 m / s), Vb = 80 km / h (22.2 m / s), and a2 = 0.05 G (0.49 m / s ² ). Condition Q is Va = 70 km / h (19.4 m / s), Vb = 100 km / h (27.8 m / s), and a2 = 0.05 G (0.49 m / s ² ). Assume that the host vehicle decelerates at a speed of 0.1 G (0.98 m / s ² ) with respect to the deceleration of the preceding vehicle.

(B) in FIG. 13 is the case of the condition P, and the own vehicle minimum deceleration aomin = Vb / Va * a2 = 22.2 / 19.4 * 0.49 = 0.56 m / s ² , 0.057G. On the other hand, since the own vehicle took the deceleration action at 0.1 G (0.98 m / s ² ), the difference of 0.043 G (0.42 m / s ² ) is excessive deceleration.

FIG. 13C shows the case of condition Q, and the own vehicle minimum deceleration aomin = Vb / Va * a2 = 27.8 / 19.4 * 0.49 = 0.70 m / s ² , 0.071G. On the other hand, since the own vehicle took a deceleration action at 0.1 G (0.98 m / s ² ), the difference of 0.029 G (0.42 m / s ² ) is an excessive deceleration. Comparing the two, it can be seen that the excess amount of the own vehicle deceleration aoa is larger in the condition P than in the condition Q.

  FIG. 14 is a diagram illustrating a calculation example in the first embodiment in which it is evaluated how much congestion induces the vehicle behind the vehicle to decelerate under two different conditions R and S. FIG. 14A illustrates the relationship between the host vehicle and the rear vehicle, and FIGS. 14B and 14C are tables illustrating examples of calculation under conditions R and S. FIG.

As shown in FIG. 14A, the host vehicle 10b travels at a speed Vb on an uphill road that is a heavy traffic jam section, and the rear vehicle 10c travels at a speed Vc at an inter-vehicle distance D. Assume that the car decelerates at aoa. Condition R is Vb = 70 km / h (19.4 m / s), Vc = 80 km / h (22.2 m / s), and aoa = 0.05 G (0.49 m / s ² ). Condition S is Vb = 50 km / h (13.9 m / s), Vc = 100 km / h (27.8 m / s), and aoa = 0.05 G (0.49 m / s ² ).

FIG. 14B shows the rearward vehicle minimum deceleration (rear vehicle collision avoidance deceleration) armin = Vc / Vb * aoa = 22.2 / 19.4 * 0.49 = 0. 56 m / s ² , which is 0.057G.

(C) in FIG. 14 is for the condition S, and the rear vehicle minimum deceleration armin = Vc / Vb * oaa = 27.8 / 19.4 * 0.49 = 0.70 m / s ² , 0.071G.

  Comparing conditions R and S, both of the vehicles decelerate at the same deceleration of 0.05G. However, since condition S is a driving action that forces greater deceleration to the rear vehicle, condition S is more It is evaluated as a deceleration action that induces traffic congestion.

  Next, a traffic jam-inducing driving behavior evaluation apparatus according to the second embodiment will be described. The traffic congestion-inducing driving behavior evaluation device of the second embodiment has a configuration similar to that of the traffic congestion-inducing driving behavior evaluation device of the first embodiment, and processing for evaluating the vehicle deceleration behavior as traffic congestion-inducing behavior and traffic congestion of the vehicle deceleration The process for evaluating the degree of incentive is different.

FIG. 15 to FIG. 17 are flowcharts showing processing operations in the traffic jam-inducing driving behavior evaluation device of the second embodiment.
The traffic congestion-inducing driving behavior evaluation device of the second embodiment performs the same steps from step S11 to S29 of the first embodiment, but in step S17 and step S25, the rear inter-vehicle distance D2 along with the relative speed of the rear vehicle and the preceding vehicle. And the preceding inter-vehicle distance D1 is acquired. The inter-vehicle distance is obtained using a radar device, but various methods are known such as calculation by image analysis using a camera image, and any method may be used.

  After step S29, in step S41, the host vehicle collision avoidance deceleration is obtained from the preceding vehicle absolute speed Vfa, the host vehicle absolute speed Voa, and the preceding inter-vehicle distance D1, and is set to the host vehicle minimum deceleration aomin. As described above, the host vehicle collision avoidance deceleration is defined as the minimum deceleration for avoiding a collision with the current vehicle when the current deceleration of the preceding vehicle is maintained. Although there are several methods for obtaining the minimum deceleration, the method shown in FIG. 2 is used in the second embodiment. The driver may use a value obtained from the daily driving behavior of each driver as the predetermined reaction time Tr, or may use a statistical average value. In the second embodiment, an average value of 0.7 seconds was used.

  In step S42, the own vehicle potential collision avoidance deceleration is calculated from the preceding vehicle absolute speed Vfa, the own vehicle absolute speed Voa, and the preceding inter-vehicle distance D1, and is set to the own vehicle maximum deceleration aomax. There are several methods for obtaining the own vehicle maximum deceleration aomax. In the second embodiment, the maximum deceleration is defined as a deceleration necessary to avoid a potential collision, and the following procedure is used. Ask.

  (1) It is assumed that the potential deceleration of the preceding vehicle is afp (= sudden braking). The deceleration afp at this time may be set for each vehicle type, and an average sudden braking amount may be used. In the second embodiment, 0.6G announced as an average value is used.

  (2) Assume that the host vehicle starts to decelerate after the reaction time Tr in order to avoid a potential collision. Similar to the method described in FIG. 2, the minimum deceleration aop necessary to avoid a potential collision with the preceding vehicle is obtained. This is set as the maximum deceleration aomax that the host vehicle can perform.

In step S43, the degree of unnecessary deceleration of the own vehicle is calculated using the own vehicle minimum deceleration aomin, the own vehicle maximum deceleration aomax, and the own vehicle deceleration ao. The unnecessary degree of deceleration is obtained by the following formula.
Deceleration unnecessary = (ao-aomin) / (ao-aomax)

  In step S51, it is determined whether or not the deceleration unnecessary degree is larger than a preset threshold value. If it is smaller, the process proceeds to step S52, and if larger, the process proceeds to step S54.

In step S52, since the own vehicle deceleration action is a deceleration action that is not excessive in order to avoid danger with the preceding vehicle, the own vehicle deceleration action is not considered as an object to be evaluated as a traffic jam inducing action.
In step S53, the process returns to step S11.

  Step S54 determines that the host vehicle deceleration is a traffic congestion-inducing behavior evaluation target when the deceleration unnecessary degree is greater than a preset threshold value or when no preceding vehicle exists but the host vehicle deceleration is detected. Proceed to step S61 to evaluate the influence of deceleration on the rear vehicle.

  In step S61, the rear vehicle minimum speed armin is calculated in the same manner as S32 in the first embodiment and S41 in the second embodiment.

In step S 63 , the vehicle deceleration action is evaluated using the value of the rear vehicle minimum speed armin as the degree of congestion incentive. Specifically, the rear wheel minimum speed armin may determine whether it exceeds a preset threshold value, does not exceed, the flow proceeds to step S 64, if exceeded, the process proceeds to step S 65.

In step S64 , it is determined that the deceleration action of the own vehicle is not a traffic jam-inducing driving.
In step S <b> 65 , the deceleration action of the host vehicle is a traffic jam inducing operation, and the data is stored in the travel information of the data storage unit 36.

  FIG. 18 shows whether the subject vehicle minimum deceleration aomin and the subject vehicle maximum deceleration aomax are obtained under two different conditions T and U and evaluated as traffic congestion-inducing behavior. It is a figure which shows the example of a calculation in the case of judging. 18A illustrates the relationship between the preceding vehicle and the host vehicle, and FIGS. 18B and 18C are tables illustrating examples of computations under the condition T and the condition U. FIG.

As shown in FIG. 18A, the preceding vehicle 10a travels at a speed Va on an uphill road that is a heavy traffic jam section, and the host vehicle 10b travels at a speed Vb at an inter-vehicle distance D1. Assume that the car decelerates at a2. Condition T is Va = 70 km / h (19.4 m / s), Vb = 70 km / h (19.4 m / s), a2 = 0.05 G (0.49 m / s ² ), and D1 = 60 m It is. Condition U is Va = 52 km / h (14.4 m / s), Vb = 70 km / h (19.4 m / s), a2 = 0.05 G (0.49 m / s ² ), and D1 = 36 m It is. Assume that the host vehicle decelerates at a speed of 0.1 G (0.98 m / s ² ) with respect to the deceleration of the preceding vehicle.

FIG. 18B shows the case of condition T. First, the time t_stop = 39.7 seconds from when Va = 19.4 m / s to when the preceding vehicle decelerates to 0.05 G and stops. The distance traveled before the preceding vehicle stops is L1 = 19.4 * 39.7−0.5 * 19.4 * 39.7 ² = 385.8 m. The distance the host vehicle travels to the preceding vehicle stop position = L1 + the inter-vehicle distance = 445.8 m. The own vehicle minimum deceleration aomin is a deceleration in which the own vehicle starts to decelerate after a reaction time of 0.7 seconds after the preceding vehicle decelerates and does not collide with the preceding vehicle. Distance traveled by own vehicle before starting deceleration = 19.44 * 0.7 = 13.6 m.

Therefore, the deceleration distance = 445.8-13.6 = 432.2 m. Therefore, deceleration = 19.4 ² /432.2/2=0.43 m / s ² = 0.044G.

The own vehicle maximum deceleration aomax is calculated by changing the preceding vehicle deceleration a2 = 0.05G to the maximum deceleration = 0.6G in the calculation of the own vehicle minimum deceleration aomin. t_stop = 3.3 seconds, L1 = 19.4 * 3.3-0.5 * (0.6 * 9.8) * 3.3 ² = 47.0 m, L1 + vehicle distance = 47 + 60 = 107m. Finally, the own vehicle minimum deceleration aomax = 19.4 ² /(107-19.44*0.7)/2=2.0 m / s ² = 0.21G. Therefore, the unnecessary degree of deceleration = (0.1−0.044) / (0.21−0.044) = 0.34.

FIG. 18C shows the case of the condition U. Calculated in the same manner as in the case of condition T, t_stop = 29.5 seconds, L1 = 22.9m, L1 + inter-vehicle distance = 248.9m, own vehicle minimum deceleration aomin = 0.75 m / s ² = 0.076G It is.

Similarly, t_stop = 2.5 seconds, L1 = 18.2 m, L1 + inter-vehicle distance = 54.2 m, and the own vehicle minimum deceleration aomax = 4.7 m / s ² = 0.48G. . Therefore, the unnecessary degree of deceleration = (0.1−0.076) / (0.48−0.076) = 0.059.

  FIG. 19 is a diagram illustrating a calculation example in the second embodiment in which it is evaluated how much congestion induces the vehicle behind the vehicle to decelerate under two different conditions V and W. 19A illustrates the relationship between the host vehicle 10b and the rear vehicle 10c, and FIGS. 19B and 19C are tables illustrating examples of calculation under the conditions V and W. FIG.

As shown in FIG. 19A, the host vehicle 10b travels at a speed Vb on an uphill road that is a heavy traffic jam section, and the rear vehicle 10c travels at a speed Vc at an inter-vehicle distance D. Assume that the car decelerates at aoa. Condition V is Vb = 75 km / h (20.8 m / s), Vc = 80 km / h (22.2 m / s), aoa = 0.05 G (0.49 m / s ² ), and inter-vehicle distance = It is 50m. Condition W is Vb = 50 km / h (13.9 m / s), Vc = 80 km / h (22.2 m / s), and aoa = 0.05 G (0.49 m / s ² ).

FIG. 19B shows the condition V, and the rear vehicle minimum deceleration (rear vehicle collision avoidance deceleration) armin is calculated by the same method as described in FIG. First, t_stop = 42.5 seconds, L1 = 442.9 m, and L1 + inter-vehicle distance = 492.9 m. The rear vehicle minimum deceleration armin = 20.8 ² /(432.9-20.83*0.7)/2=0.52 m / s ² = 0.051G.

FIG. 19C shows the case of condition W, t_stop = 28.3 seconds, L1 = 196.8 m, and L1 + inter-vehicle distance = 226.8 m. The rear vehicle minimum deceleration armin = 13.9 ² /(226.8-13.88*0.7)/2=1.17 m / s ² = 0.12G.

  Comparing conditions V and W, both of the vehicles are decelerating at the same deceleration of 0.05G. However, since condition W is a driving action that forces greater deceleration to the rear vehicle, condition W is more It is evaluated as a deceleration action that induces traffic congestion.

  Next, a traffic jam-inducing driving behavior evaluation apparatus according to a third embodiment will be described. The traffic jam-inducing driving behavior evaluation apparatus of the third embodiment has a configuration similar to that of the traffic jam-induced driving behavior evaluation apparatus of the second embodiment, and the processing for evaluating the traffic jam incentive degree of own vehicle deceleration is different. Specifically, the change is evaluated on the basis of the rear vehicle minimum deceleration at the initial stage of deceleration, and the deceleration is continuously performed to evaluate the increase in the influence on the rear vehicle.

  FIG. 20 is a diagram illustrating a calculation example in the third embodiment in which it is evaluated how much congestion induces the rear vehicle to decelerate the own vehicle under two different conditions X and Y. 19A illustrates the relationship between the host vehicle 10b and the rear vehicle 10c, and FIGS. 19B and 19C are tables illustrating calculation examples under the conditions X and Y. (D ) Shows the change in the minimum deceleration of the rear vehicle.

As shown in FIG. 20A, the host vehicle 10b travels at a speed Vb on an uphill road that is a heavy traffic jam section, and the rear vehicle 10c travels at a speed Vc at an inter-vehicle distance D. Assume that the car decelerates at aoa. Condition V is an initial stage of deceleration, time t = 0, Vb = 75 km / h (20.8 m / s), Vc = 80 km / h (22.2 m / s), and aoa = 0.05 G ( 0.49 m / s ² ), and the inter-vehicle distance is 50 m. Condition Y is t = 8 after 8 seconds, Vb = 60.9 km / h (16.9 m / s), Vc = 80 km / h (22.2 m / s), and aoa = 0.05 G (0. 49 m / s ² ), and the inter-vehicle distance = 23.2 m.

  FIG. 20B shows the condition X, where the rear vehicle minimum deceleration (rear vehicle collision avoidance deceleration) armin = 0.052G. FIG. 20C shows the case of condition Y, armin = 0.084G.

  This is a table in FIG. 19C where the preceding vehicle is unaware of the deceleration of the own vehicle (unconscious deceleration continues) and 5 seconds have passed. At this time, armin = 0.084G, and the degree of congestion incentive to the rear vehicle has increased by 0.032G in 5 seconds. Based on this increased amount, it is determined that the driver continues the traffic jam inducing behavior.

  If the driver notices that the vehicle is decelerating and the driver takes a driving action that corrects the traffic congestion-inducing action, the amount of change becomes a negative value. With this evaluation, it is also possible to detect the driver's traffic avoidance driving behavior.

  As described above, in the first to third embodiments, it is possible to determine the deceleration for avoiding danger and the deceleration that is more than necessary and has a high possibility of inducing traffic congestion even at the same inter-vehicle distance. Moreover, even if the deceleration is the same, the influence on the rear vehicle can be quantitatively evaluated, and the difference in the cause of the traffic jam can be determined. Furthermore, the feedback method can be changed depending on the degree of incentive for traffic jams, and more appropriate driving support can be achieved.

  Moreover, it is possible to collect data on the degree of incentive for traffic jams over a long period of time, and to change incentives for drivers (such as highway fares) depending on the magnitude of the incentive level of traffic jams.

  The embodiment has been described above, but all examples and conditions described herein are described for the purpose of helping understanding of the concept of the invention applied to the invention and technology. In particular, the examples and conditions described are not intended to limit the scope of the invention, and the construction of such examples in the specification does not indicate the advantages and disadvantages of the invention. Although embodiments of the invention have been described in detail, it should be understood that various changes, substitutions and modifications can be made without departing from the spirit and scope of the invention.

DESCRIPTION OF SYMBOLS 10a Prior vehicle 10b Own vehicle 10c Rear vehicle 21 Computation device 22 Previous vehicle speed measurement device 23 Rear vehicle speed measurement device 24 Speed sensor 25 Acceleration sensor

Claims (5)

A computer that evaluates the degree of incentive to slowdown traffic jams,
Sensor mounted on the vehicle is a result detects that the vehicle has been decelerated by the other vehicle information obtained via the sensor and the communication terminal mounted on the mounting the sensors or vehicle on the vehicle, the vehicle during deceleration detection, it determines whether the preceding vehicle and the rear vehicle is present,
When the preceding vehicle and the presence of the rear wheel, the other vehicle information obtained via the sensor and the communication terminal mounted on the mounting the sensors or vehicle on the vehicle, at least the preceding vehicle, the own vehicle, the following vehicle speed and acceleration Get travel information including
Based on the acquired travel information, calculate a minimum deceleration of the host vehicle that indicates a minimum deceleration of the host vehicle that can avoid a collision with the preceding vehicle,
Based on a comparison result between the calculated minimum deceleration of the host vehicle and the deceleration of the host vehicle acquired by the sensor, it is determined whether or not the deceleration of the host vehicle causes a traffic jam,
If deceleration of the vehicle to trigger congestion, based on the acquired traveling information, calculates a rear wheel minimum deceleration the exhibit minimal deceleration collision avoidable rear wheel of the vehicle,
Outputting an evaluation result about the driving of the own vehicle based on the calculated minimum deceleration of the rear vehicle,
A method for evaluating driving behavior induced by traffic congestion. The computer obtains the inter-vehicle distance from the preceding vehicle and the succeeding vehicle based on the other vehicle information obtained through the sensor mounted on the vehicle or the sensor mounted on the vehicle and the communication terminal ,
The method for evaluating driving behavior according to claim 1, wherein a preceding vehicle or a rear vehicle having an inter-vehicle distance of a predetermined distance or more is not a preceding vehicle or a rear vehicle. The computer sets the minimum deceleration of the host vehicle to zero when the ratio of the preceding vehicle to the preceding vehicle is greater than 1, and to a value obtained by multiplying the preceding speed ratio by the acceleration of the preceding vehicle if greater than 1. The method according to claim 1, wherein the driving behavior is evaluated according to a traffic jam. Computer
Based on the inter-vehicle distance from the preceding vehicle whose existence has been confirmed and the travel information related to the preceding vehicle and the own vehicle, when the preceding vehicle suddenly brakes, the own vehicle capable of avoiding a collision with the preceding vehicle calculating a vehicle collision avoidance deceleration showing a deceleration, and set the vehicle collision avoidance deceleration in the host vehicle maximize deceleration,
When deceleration of the vehicle to determine whether to trigger a congestion, the vehicle deceleration, the calculated deceleration unnecessary degree from the vehicle minimum deceleration and the vehicle maximum limit deceleration, the The method according to claim 2 , wherein the determination is based on a value of the degree of unnecessary deceleration. Computer
Evaluation when outputting the result, congestion incentive driving action evaluation method according to any one of claims 1 4, characterized in that there use the time variation of the rear wheel minimum deceleration.

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