JP2012203649A - Drive support device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a drive support device capable of appropriately supporting drive even when disturbance occurs.SOLUTION: An ECU 6 of a drive support device 1 comprises: a position/speed information acquisition part 8 for acquiring information of a speed of a present vehicle, a relative distance and a relative speed or the like between the present vehicle and a preceding vehicle; a hazard sense index calculation part 9 for calculating PRE of a driver of the present vehicle to the preceding vehicle on the basis of the information; a hazard sense index fluctuation amount calculation part 11 for calculating a PRE fluctuation amount indicating time sequential data of the PRE of the driver; a forgetting parameter determination part 12 for determining a forgetting parameter on the basis of a change rate of the PRE fluctuation amount; a hazard prediction part 13 for predicting the hazard of the present vehicle to the preceding vehicle using the forgetting parameter; an operation timing calculation part 14 for calculating brake operation timing and handle operation timing of the driver corresponding to a hazard prediction result; and a drive support part 15 for executing control so as to issue an alarm by an alarm 7 when the driver does not operate a brake or a handle at the required timing.

Description

  The present invention relates to a driving support device that supports driving of a host vehicle.

  As a conventional driving support device, for example, as described in Patent Document 1, a perceived relative distance and a perceived relative speed between a perceived object and a host vehicle based on a driver's perception are calculated, and a perceived relative distance and a perceived relative speed are calculated. It is known that deceleration control is started when the ratio to the speed exceeds a threshold value.

JP 2010-274838 A

  However, in the above-described prior art, when disturbance such as noise occurs when acquiring driving data of the driver in an actual driving environment, it may be difficult to appropriately perform driving support such as deceleration control. .

  An object of the present invention is to provide a driving support device that can perform appropriate driving support even when a disturbance occurs.

  The driving support device according to the present invention includes an information acquisition unit that acquires information on a relative relationship between the host vehicle and a front obstacle, and a vehicle's vehicle with respect to the front obstacle based on the information on the relative relationship acquired by the information acquisition unit. A risk index calculation unit that calculates a driver's risk index, and a support unit that supports driving of the host vehicle using the risk index calculated by the risk index calculation unit It is.

  Thus, in the driving support device of the present invention, information on the relative relationship between the host vehicle and the front obstacle is acquired, and the driver's risk index for the obstacle is calculated based on the information on the relative relationship. This risk index is a stable variable. Therefore, by providing driving assistance for the host vehicle using the danger index, appropriate driving assistance can be realized even if a disturbance such as noise occurs.

  Preferably, the support means obtains a risk index fluctuation amount representing time series data of the driver's risk index, performs a risk prediction of the host vehicle against a forward obstacle based on the risk index fluctuation amount, and Depending on the result, driving assistance of the vehicle is performed.

  The risk index fluctuation amount representing the time series data of the driver's risk index varies depending on the driving experience of the driver. Therefore, by predicting the risk of the host vehicle against the obstacle ahead based on the amount of change in the risk index, and supporting the driving of the host vehicle according to the result of the risk prediction, Driving assistance can be realized.

  According to the present invention, driving assistance for the host vehicle can be appropriately performed even when disturbances such as noise occur.

It is a schematic block diagram which shows one Embodiment of the driving assistance device concerning this invention. It is a conceptual diagram which shows the time series of the parameter of PRE calculated by the danger index calculation part shown in FIG. It is a graph which shows an example of the sigmoid function used when determining a forgetting parameter by the forgetting parameter determination part shown in FIG.

  DESCRIPTION OF EMBODIMENTS Hereinafter, a preferred embodiment of a driving support apparatus according to the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a schematic configuration diagram showing an embodiment of a driving support apparatus according to the present invention. In the figure, the driving support device 1 of the present embodiment is a device that supports driving of the host vehicle when a front obstacle such as a preceding vehicle exists ahead of the host vehicle. In addition, as a front obstacle, a bicycle, a pedestrian, etc. other than a preceding vehicle are also considered.

  The driving support device 1 detects a vehicle speed sensor 2 that detects the speed of the host vehicle, a front radar 3 that irradiates a preceding vehicle traveling in front of the host vehicle with electromagnetic waves and lasers, and measures the reflected waves, and detects a brake operation. Brake sensor 4 for steering, steering sensor 5 for detecting steering operation, ECU (Electronic Control Unit) 6 composed of CPU, memory such as ROM and RAM, input / output circuit, etc., and alarm for warning by voice and display And a container 7.

  The ECU 6 includes a position / speed information acquisition unit 8, a risk index calculation unit 9, a storage unit 10, a risk index variation calculation unit 11, a forgetting parameter determination unit 12, a risk prediction unit 13, and an operation timing. A calculation unit 14 and a driving support unit 15 are included.

  The position / speed information acquisition unit 8 acquires information such as the speed of the host vehicle, the relative distance between the host vehicle and the preceding vehicle, and the relative speed based on the detection signal of the vehicle speed sensor 2 and the measurement signal of the front radar 3.

The danger index calculation unit 9 drives the host vehicle with respect to the preceding vehicle based on information such as the speed of the host vehicle, the relative distance between the host vehicle and the preceding vehicle, and the relative speed acquired by the position / speed information acquiring unit 8. The risk index of the person is calculated. Here, a perceptual approach feeling index (PRE: Perceptual Risk Estimate) is calculated as the risk index. PRE is obtained by dividing the perceptual speed by the perceptual distance, and is represented by the following equation.

  Here, D is the relative distance between the host vehicle and the preceding vehicle, Vr is the relative speed between the host vehicle and the preceding vehicle, Vs is the speed of the host vehicle, and Ap is the acceleration of the preceding vehicle. In addition, α, β, and n represent adaptation parameters determined for each driver.

  The adaptation parameters α, β, n are calculated from three consecutive sets of time series data as shown in FIG. At this time, if the variation of the time series data of the adaptation parameters α, β, n is abrupt, a filtering process is performed.

When the same driver is in the same state (for example, during normal driving), PRE tends to be constant. Therefore, the relationship of the following formula is obtained.

  The adaptation parameters α, β, n are determined from the above equations (1) to (3). Thus, the driver-specific PRE is calculated from the above equation (1). The driver-specific PRE is sequentially stored in the storage unit 10.

  The danger index fluctuation amount calculation unit 11 calculates a PRE fluctuation amount representing time series data of the driver's PRE (danger feeling index) sequentially stored in the storage unit 10. The amount of PRE variation varies depending on the driving experience and driving skill of the driver. For example, the amount of PRE fluctuation increases as the driving skill decreases.

で定義される。ＰＲＥ変動量νΔは絶対値の和であるため、νΔ≧０となる。 The amount of PRE fluctuation is the sum of all the small sections showing how much the PRE value is open at the left end and the right side of each small section created by the division Δ in the closed section [a, b]. . That is, the closed interval [a, b] is defined as I ₁ = [a, x ₁ ], I ₂ = [x ₁ , x ₂ ],..., I _n = [x _n−1 , b] (a = x ₀ < The PRE fluctuation amount νΔ with respect to the division Δ divided into x ₁ <x ₂ <... <x _n = b) is

Defined by Since the PRE fluctuation amount νΔ is the sum of absolute values, νΔ ≧ 0.

  As an example of the measurement method of the PRE fluctuation amount, the PRE fluctuation amount is measured a plurality of times from about 6 seconds before the predicted collision time (TTC) to the preceding vehicle, and the average value of the PRE fluctuation amount at that time is taken.

  The forgetting parameter determination unit 12 detects the change point of the PRE fluctuation amount calculated by the danger index fluctuation amount calculation unit 11, and determines the forgetting parameter based on the rate of change of the PRE fluctuation amount. The forgetting parameter is a parameter having a forgetting function for updating the estimated value so as to reduce the influence of data before the i time point.

For example, as shown in FIG. 3, the value of the sigmoid function represented by F (x) = 1 / [1 + exp {−a (x−b)}] is considered as the value of the forgetting parameter, and the sigmoid inverse of the forgetting parameter value is obtained. The forgetting parameter value is updated by multiplying the function value by the change rate of the PRE fluctuation amount. In the graph of FIG. 3, r ₀ is a reference value of the forgetting parameter r, and r _min is a minimum value of the forgetting parameter r.

As an example of the method of updating the forgetting parameter, z = z ₀ × when the PRE fluctuation amount at a certain time of the driver is _VA and the PRE fluctuation amount after the predetermined period of time of the same driver is V _B. (V _B / V _A ) is obtained, and F (z) is determined as a new forgetting parameter value.

  The risk prediction unit 13 uses the forgetting parameter calculated and determined by the forgetting parameter determination unit 12 to perform risk prediction of the host vehicle with respect to the preceding vehicle by a known method.

  The operation timing calculation unit 14 calculates the driver's brake operation timing and steering operation timing according to the risk prediction result of the host vehicle by the risk prediction unit 13.

  The driving support unit 15 performs driving support by controlling the alarm device 7 based on the brake operation timing and the steering operation timing calculated by the operation timing calculation unit 14 and the detection signals of the brake sensor 4 and the steering sensor 5.

  Specifically, the driving support unit 15 controls the alarm device 7 to generate an alarm when the brake operation by the driver is not detected by the brake sensor 4 despite the brake operation timing, If the steering operation by the driver is not detected by the steering sensor 5 in spite of the steering operation timing, the alarm 7 is controlled to generate an alarm.

  In the above, the position / velocity information acquisition unit 8 of the vehicle speed sensor 2, the forward radar 3, and the ECU 6 constitutes an information acquisition unit that acquires information on the relative relationship between the host vehicle and the front obstacle. The risk index calculation unit 9 of the ECU 6 constitutes a risk index calculation unit that calculates the driver's risk index for the front obstacle based on the information on the relative relationship acquired by the information acquisition unit. The brake sensor 4, the steering sensor 5, the storage unit 10 of the ECU 6, the danger index variation calculation unit 11, the forgetting parameter determination unit 12, the risk prediction unit 13, the operation timing calculation unit 14, the driving support unit 15, and the alarm device 7 Support means for supporting driving of the host vehicle is configured using the risk index calculated by the risk index calculation means.

  As described above, in the present embodiment, based on information such as the speed of the own vehicle, the relative distance between the own vehicle and the preceding vehicle, and the relative speed, the driver's PRE (risk index) for the preceding vehicle. ), A PRE fluctuation amount representing time series data of the PRE is calculated, a forgetting parameter is determined based on a rate of change of the PRE fluctuation amount, and a risk prediction of the own vehicle with respect to the preceding vehicle is performed using the forgetting parameter. The brake operation timing and steering operation timing of the driver are calculated. Here, PRE takes a stable variable. For this reason, when acquiring the driver's PRE data in the actual driving environment, the driver's specific brake operation timing and steering operation timing can be obtained even if noise or the like is mixed.

  Also, the amount of PRE fluctuation varies depending on the driving experience and driving skill of the driver. By determining the forgetting parameter according to the change of the PRE fluctuation amount, an appropriate brake operation according to the driving experience and driving skill of the driver is performed. Timing and handle operation timing can be obtained.

  As a result, it is possible to perform driving support in which an alarm is issued from the alarm device 7 at an appropriate timing when the driver does not perform a brake operation or a steering wheel operation at a necessary timing.

  The present invention is not limited to the above embodiment. For example, in the above-described embodiment, the driving support is performed such that the warning is issued when the driver does not perform the brake operation or the steering wheel operation at a necessary timing. However, the driving support device of the present invention is not particularly limited thereto. For example, the present invention can be applied to a device that automatically controls a brake or a handle at a necessary timing.

DESCRIPTION OF SYMBOLS 1 ... Driving assistance device, 2 ... Vehicle speed sensor (information acquisition means), 3 ... Front radar (information acquisition means), 4 ... Brake sensor (support means), 5 ... Steering sensor (support means), 6 ... ECU, 7 ... Alarm device (support means), 8 ... Position / speed information acquisition section (information acquisition means), 9 ... Risk index calculation section (risk index calculation means), 10 ... Storage section (support means), 11 ... Risk index Fluctuation amount calculation unit (support means), 12 ... forgetting parameter determination unit (support means), 13 ... danger prediction unit (support means), 14 ... operation timing calculation unit (support means), 15 ... driving support unit (support means) .

Claims (2)

Information acquisition means for acquiring information on the relative relationship between the host vehicle and the front obstacle;
A risk index calculation unit that calculates a risk index of the driver of the host vehicle with respect to the forward obstacle based on the information on the relative relationship acquired by the information acquisition unit;
A driving support apparatus, comprising: support means for supporting driving of the host vehicle using the risk index calculated by the risk index calculation means. The support means calculates a risk index fluctuation amount representing time series data of the driver's risk index, performs a risk prediction of the host vehicle against the front obstacle based on the risk index fluctuation amount, and The driving support apparatus according to claim 1, wherein driving support of the host vehicle is performed according to a risk prediction result.

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