JP2007164432A - Danger information detection device and danger information detection method - Google Patents

Abstract

To provide a danger information detection device and a danger information detection method capable of detecting an area that may be dangerous when driving on a curve before the vehicle enters the curve.
A driving behavior collection unit stores information acquired from a vehicle information detection unit in a driving behavior database as driving behavior information. Based on the acquired current position, a curve section existing ahead in the traveling direction of the host vehicle is extracted from the road information database 32. Then, the driving behavior prediction unit 22 predicts the driving state in the curve section existing ahead of the extracted driving direction based on the past driving behavior information accumulated in the driving behavior database 31. The recommended behavior calculation unit 24 acquires a recommended condition indicating a recommended driving state in the extracted curve section. The danger determination unit 23 determines a road section in which the predicted traveling information does not match the recommended condition as a dangerous section, and the presentation unit 25 outputs the determined dangerous section to the output unit 81 for presentation.
[Selection] Figure 1

Description

  The present invention relates to a danger information detection device and a danger information detection method.

  For example, there is a vehicle display device described in Patent Document 1 for the purpose of performing display so that the vehicle can smoothly travel along a curve.

  The vehicle display device includes a road information holding unit that holds curve road information, a current position detection unit that detects a current position, and a vehicle speed detection unit that detects a current vehicle speed when driving a vehicle such as an automobile. The road ahead of the current position obtained by the current position detection means is obtained based on the road information, and the area where the vehicle can smoothly travel at the current speed when passing through the road, and the current speed. A road search means for searching for a difficult-to-run area, a travel path determined by the road search means, and an area on the travel road that can smoothly run at the current speed, Display means for displaying the areas in different colors.

JP-A-9-257507

  However, in the above-described display device for a vehicle, since it is determined that the region where it is difficult to travel is uniquely determined with respect to the current vehicle speed without considering the past driving tendency, the vehicle display device travels in advance before entering the curve. There was a circumstance that the difficult area was not accurately indicated.

  The present invention has been made in view of the above circumstances, and provides a danger information detection device and a danger information detection method capable of detecting an area that may be dangerous when the vehicle travels before the vehicle enters the curve. The purpose is to do.

  The present invention provides, firstly, a position information acquisition unit that acquires position information indicating the current position of the host vehicle, a travel information acquisition unit that acquires travel information that indicates the driving state of the host vehicle, and road information related to a road shape. A map information storage unit that stores map information, and the map information storage unit is referred to based on the acquired position information, and the acquired travel information corresponds to the road information that is traveling when the travel information is acquired. In addition, the driving action output unit that outputs the driving action information, the driving action storage unit that accumulates the driving action information output from the driving action output unit, and the map information storage unit that is based on the acquired position information. A curve section extraction unit that extracts a curve section that exists in front of the traveling direction of the host vehicle, and travel in the extracted curve section based on the driving behavior information accumulated in the driving behavior storage section A driving behavior prediction unit that predicts a state and acquires it as predicted driving information, a recommended behavior acquisition unit that acquires a recommended condition indicating a driving state recommended in the extracted curve section, the predicted driving information and the recommendation A dangerous section determination unit that compares a condition and determines a road section in which the predicted traveling information does not conform to the recommended condition as a dangerous section; and a dangerous section presentation unit that presents the dangerous section determined by the dangerous section determination unit; A danger information detection apparatus comprising:

  By this configuration, it is possible to detect a region that can be dangerous when driving a curve before entering the curve by making a risk judgment based on the driving behavior at the time of passing the curve predicted from past driving behavior, Risk judgment and presentation according to the driving behavior tendency of Sone can be performed.

  Secondly, the present invention is the risk information detection apparatus according to the first aspect, wherein the driving behavior prediction unit includes a parameter of the road information based on driving behavior information accumulated in the driving behavior storage unit. The relationship between the parameters of the travel information is calculated, and the predicted travel information is acquired from the road information parameters of the extracted curve section using the relationship.

  With this configuration, it is possible to predict the driving behavior in the front curve section by applying the road shape of the front curve section to the relationship between the road shape obtained based on the past driving behavior information and the driving state. Therefore, driving behavior can be predicted easily.

  The third aspect of the present invention is the risk information detection apparatus according to the first or second aspect, wherein the predicted traveling information includes a change in vehicle speed in the extracted curve section.

  According to this configuration, by predicting a change in the vehicle speed in consideration of past driving tendency, it is possible to present a dangerous section based on the vehicle speed, such as a warning of overspeed, according to past driving behavior.

  Fourthly, the present invention is the risk information detecting apparatus according to the first or second aspect, wherein the predicted traveling information includes a change in acceleration of the vehicle in the extracted curve section.

  With this configuration, by predicting changes in acceleration taking into account past driving trends, it is possible to present dangerous sections based on acceleration, such as warnings of sudden acceleration and sudden deceleration, according to past driving behavior. it can.

  The fifth aspect of the present invention is the risk information detecting apparatus according to any one of the first to fourth aspects, wherein the road information includes a curve width, a bank angle, a curvature, and a road gradient. Including at least one of them.

  With this configuration, prediction of driving behavior is performed more accurately by predicting driving behavior in consideration of past driving trends according to information on the shape of the curve, such as curve width, bank angle, curvature, road gradient, etc. It is possible to determine the dangerous zone in consideration of past driving behavior according to the curve ahead.

  Sixth, the present invention is the danger information detecting apparatus according to any one of the first to fifth aspects, wherein the information indicating the presence or absence of a preceding vehicle when passing a curve, the information indicating the presence or absence of an oncoming vehicle, A traffic condition detection unit that detects traffic condition information including at least one of information indicating weather is further provided, and the driving behavior storage unit accumulates the traffic condition information as the driving behavior information.

  With this configuration, driving behavior is predicted more accurately by taking into account past driving trends according to information on traffic conditions when passing a curve such as the presence of a preceding vehicle, the presence of an oncoming vehicle, and weather. The risk zone can be determined by taking into account the past driving behavior according to the curve ahead.

  Seventhly, the present invention is the danger information detecting device according to any one of the first to sixth aspects, wherein the dangerous section presenting unit adds the dangerous section to the map information read from the map information storage unit. Are superimposed and displayed.

  With this configuration, the dangerous section determined based on the driving behavior predicted based on the past driving tendency is superimposed on the actually traveling map, so that the dangerous section can be visually recognized in an easy-to-understand manner. Can be presented.

  Eighthly, the present invention is the danger information detecting device according to any one of the first to sixth aspects, wherein the dangerous section presenting unit includes road information included in the map information read from the map information storage unit. Display information corresponding to the shape of the extracted curve section is generated, and the danger section is superimposed and displayed on the generated display information.

  With this configuration, it is possible to reduce a large amount of map data for map display, and it is possible to present a dangerous section in an easy-to-understand manner to the driver by displaying a schematic simple figure.

  Ninth, the present invention is the danger information detecting apparatus according to any one of the first to eighth aspects, wherein the map data storage unit stores speed limit information corresponding to a road, and obtains the recommended action. The unit obtains the speed limit in the extracted curve section from the speed limit speed information stored in the map data storage unit.

  With this configuration, it is possible to detect a curve section that is predicted to exceed the speed limit in the forward curve section as a dangerous section in view of past driving behavior trends.

  Tenthly, the present invention provides a step of acquiring position information indicating the current position of the host vehicle, a step of acquiring travel information indicating the traveling state of the host vehicle, and a map information storage unit based on the acquired position information. Referring to map information including road information related to the road shape stored in the vehicle, the acquired travel information and the road information traveling at the time of acquiring the travel information are associated with each other and stored in the drive behavior storage unit as driving behavior information Based on the acquired position information, a step of extracting a curve section existing ahead of the traveling direction of the host vehicle from the map information storage unit, and the driving behavior information accumulated in the driving behavior storage unit Predicting the driving state in the extracted curve section and obtaining the predicted driving information, and the recommended driving state in the extracted curve section Obtaining a recommended condition; comparing the predicted travel information with the recommended condition; determining a road section in which the predicted travel information does not match the recommended condition as a dangerous section; and A danger information detection method is provided that includes a step of presenting the determined danger section.

  By this method, it is possible to detect an area that can be dangerous when driving a curve before entering the curve by making a risk judgment based on the driving action at the time of passing a curve predicted from past driving actions. Risk judgment and presentation according to the tendency of the driving behavior of the driver can be performed.

  In the eleventh aspect of the present invention, there is provided a danger information detection program for executing the steps described in the tenth above on a computer.

  By this program, it is possible to detect areas that can be dangerous when driving on a curve before entering the curve by making a risk judgment based on driving behavior when passing a curve predicted from past driving actions. Risk judgment and presentation according to the tendency of the driving behavior of the driver can be performed.

  ADVANTAGE OF THE INVENTION According to this invention, the danger information detection apparatus and danger information detection method which can detect the area | region which may become dangerous at the time of curve driving | running | working before a vehicle approachs a curve can be provided.

(First embodiment)
FIG. 1 is a block diagram showing the main configuration of the danger information detection apparatus according to the first embodiment of the present invention. As shown in FIG. 1, the danger information detection device 20 of the present embodiment is installed in a vehicle 10, is connected to a vehicle information detection unit 11 and an output unit 81, and is a curve section that exists in front of the traveling direction of the vehicle 10. In this case, a dangerous zone that is predicted to be unable to travel safely is detected.

  The vehicle information detection unit 11 includes a position sensor 12 that detects position information indicating the current position of the vehicle 10 using a GPS (Global Positioning System) or the like, and a vehicle speed sensor 13 that detects the speed of the vehicle 10. In addition to the vehicle speed sensor 13, the vehicle information detection unit 11 has a configuration capable of detecting travel information indicating the travel state of the vehicle 10 such as an acceleration sensor that detects the acceleration of the vehicle 10 and an angular velocity that detects an angular velocity.

  The danger information detection device 20 includes a road information database 32, a driving action collection unit 21, a driving action database 31, a driving action prediction unit 22, a risk determination unit 23, a recommended action calculation unit 24, and a presentation unit 25. Have In the danger information detection apparatus 20, the driving action collection unit 21, the behavior prediction unit 22, the risk determination unit 23, the recommended behavior calculation unit 24, and the presentation unit 25 are mainly configured by a processor that is operated by the danger information detection program. .

  The road information database 32 functions as an example of a map information storage unit, and stores map information including road information related to the road shape. For example, the road information includes information indicating a road radius of curvature (hereinafter referred to as a curvature), road width, number of lanes, gradient, bank angle, and the like.

  The driving behavior collection unit 21 functions as an example of a position information acquisition unit and a travel information acquisition unit, and acquires position information output from the position sensor 12 and vehicle speed information output from the vehicle speed sensor 13.

  The driving action collection unit 21 functions as an example of a driving action output unit, refers to the road information database 32 based on the position information acquired from the position sensor 12, and the vehicle speed information acquired from the vehicle speed sensor 13. The road information on which the vehicle is traveling at the time of obtaining the vehicle speed information is associated and output to the driving behavior database 31 as driving behavior information. In the present embodiment, the case where the driving behavior information output to the driving behavior database 31 includes road information in a curve section when the vehicle 10 travels a curve and vehicle speed information during traveling will be described.

  The road information in the curve section included in the driving behavior information includes the curvature of the curve calculated from the road information extracted from the road information database 32 and the road width (total road width, road width or number of lanes only in the traveling direction). In this embodiment, it is referred to as a traffic environment in a curve. The traffic environment on the curve is not limited to the above, and any information indicating the shape of the curve such as a bank angle may be used.

  Here, the curvature calculation method will be described. FIG. 2 is a diagram for explaining a curvature calculation method. In FIG. 2, the difference in the direction of the straight line connected to the curve at the start point A and the end point B of the curve is the road intersection angle θ. If the length of the arc AB section, which is the curve length, is L, the curvature R is calculated as R = L / θ (θ is expressed in radians). Note that the driving behavior collection unit 21 may calculate the curvature from the angle between the links connecting the node information stored in the road information database 32.

  In addition, the traveling vehicle speed information includes the speed of the vehicle at the entrance, the middle point, and the exit of the curve (the curve entry speed, the curve turning speed, and the curve exit speed, respectively). . The driving action on the curve may be information indicating the running state detected by the vehicle information detection unit 11, and may have, for example, acceleration, angular velocity, or the like.

  Further, the driving behavior collection unit 21 functions as a curve segment extraction unit, and extracts road information of a curve segment existing ahead of the host vehicle from the road information database 32 based on the position information acquired from the position sensor 12. To do. For example, the driving behavior collection unit 21 monitors the curvature of the road up to a predetermined distance ahead of the traveling direction of the host vehicle based on the acquired position information, and there is a section having a curvature equal to or greater than a predetermined value. And extracted as a curve section.

  The driving behavior database 31 functions as an example of a driving behavior storage unit, and accumulates driving behavior information output from the driving behavior collection unit 21. The driving behavior prediction unit 22 functions as an example of a driving behavior prediction unit, and is based on past driving behavior information accumulated in the driving behavior database 31 and is ahead of the traveling direction extracted by the driving behavior collection unit 21. A traveling state in an existing curve section is predicted and acquired as predicted traveling information.

  The recommended action calculation unit 24 functions as an example of a recommended action acquisition unit, and acquires a recommended condition indicating a recommended driving state in an arbitrary curve section such as a curve section in front of the traveling direction. The risk determination unit 23 functions as an example of a risk zone determination unit, compares the predicted travel information output from the driving behavior prediction unit 22 with the recommended conditions output from the recommended behavior calculation unit 24, and the predicted travel information is recommended. Road sections that do not meet the conditions are determined as dangerous sections. The presentation unit 25 functions as an example of a danger zone presentation unit, and generates display information, voice information, and the like for presenting the danger zone determined by the danger determination unit 23 to a driver or the like.

  The output unit 81 includes a display device 82 and a speaker 83, and can output the display information and audio information output from the presentation unit 25 to present a portion determined as a dangerous zone to a driver or the like. it can.

  About the danger information detection apparatus comprised as mentioned above, the operation | movement is demonstrated using the flowchart of FIG.3 and FIG.4.

  FIG. 3 is a flowchart showing the procedure of the driving action accumulation process according to the first embodiment of the present invention. Regarding the driving action accumulation process for accumulating the traffic environment of the passing curve and the speed change in passing the curve in the driving action database 31. explain.

  From the position sensor 12 and the vehicle sensor 13, the position and vehicle speed information of the host vehicle are always collected (step S11). Based on the collected position information, the driving behavior collection unit 21 determines whether or not a curve exists on the road ahead in the traveling direction (step S12). If it is determined that the curve does not exist (NO in step S12), the process returns to step S11 again to acquire vehicle information and determine the presence of the curve.

  On the other hand, when it is determined that there is a curve (YES in step S12), traffic environment information including the curvature, road width, and slope in the forward curve is acquired from the road information database 32 (step S13). Further, the driving behavior collection unit 21 acquires the vehicle speed when the host vehicle actually passes this curve from the vehicle speed sensor 13 (step S14), and uses the traffic environment information of the acquired curve and the vehicle speed on the curve to drive the vehicle. Accumulate in the behavior database 32 (step S15).

  FIG. 5 is a diagram showing an example of driving behavior information accumulated in the driving behavior database according to the first embodiment of the present invention. As shown in FIG. 5, the driving behavior database 32 stores traffic environment information on a curve and driving behavior on a curve in association with each other. As a result, what kind of curve (curvature, road width, gradient) the vehicle 10 has passed with what vehicle speed change (approach speed, turning speed, escape speed) is stored in the driving action database. Can do. Here, the accumulated vehicle speed as the driving action is not limited to three places, and may be further subdivided. This makes it possible to perform processing with higher accuracy.

  FIG. 4 is a flowchart showing the procedure of the driving behavior prediction process and the dangerous section presentation processing according to the first embodiment of the present invention, and uses the traffic environment of the forward curve and the accumulated driving behavior database, A driving behavior prediction / danger presentation process that predicts a change in vehicle speed and presents danger information by comparing with a recommended speed will be described.

  From the position sensor 12 and the vehicle sensor 13, the position of the host vehicle and vehicle speed information are always collected (step S21). Based on the collected position information, the driving behavior collection unit 21 determines whether or not a curve exists on the road ahead in the traveling direction (step S22). When it is determined that the curve does not exist (NO in step S22), the process returns to step S21 again to acquire vehicle information and determine the presence of the curve.

  On the other hand, when it is determined that there is a curve (YES in step S22), traffic environment information having a curvature, a road width, and a gradient in the forward curve is acquired from the road information database 32 (step S23). Next, the driving behavior prediction unit 22 uses the traffic environment information on the forward curve and the accumulated driving behavior database 31 to take into account the driving habits of the driver. A change in vehicle speed is predicted (step S24).

  Here, a method for predicting a change in vehicle speed in the driving behavior prediction unit 22 will be described with reference to FIG. FIG. 6 is a conceptual diagram illustrating a driving behavior prediction method according to the first embodiment of the present invention. In FIG. 6, reference numeral 41 indicates driving behavior data stored in the driving behavior database 31, and reference numeral 42 indicates traffic environment information on a forward curve to be passed.

  In the driving behavior prediction unit 22, parameters of road information (in the example of FIG. 5, curvature r, road width w, gradient h) and driving information parameters based on the driving behavior data 41 accumulated in the driving behavior database 31 in advance. The relationship among (curve entry speed v1, curve turning speed v2, curve escape speed v3) is calculated. For example, the constants α1, β1, γ1, α2, β2, γ2, α3, β3, and γ3 are calculated by using a model equation such as Equations (1) to (3) using a technique such as multiple regression analysis. deep.

v1 = α1 * r + β1 * w + γ1 * h (1)
v2 = α2 * r + β2 * w + γ2 * h (2)
v3 = α3 * r + β3 * w + γ3 * h (3)

  The driving behavior prediction unit 22 uses the above equations (1) to (3) and the traffic environment (R, W, H) in the forward curve to be passed, acquired in step S23. As shown in equations (4) to (6), vehicle speed changes (V1, V2, V3) in the forward curve are predicted.

V1 = α1 * R + β1 * W + γ1 * H (4)
V2 = α2 * R + β2 * W + γ2 * H (5)
V3 = α3 * R + β3 * W + γ3 * H (6)

  When calculating a detailed speed change, a continuous change in the vehicle speed may be predicted from the traffic environment (R, W, H) using a technique such as vector quantization. Further, instead of the speed change, a change in acceleration in the front-rear direction and the left-right direction of the vehicle, or a change in running state such as an angular speed may be predicted.

  FIG. 7 is a conceptual diagram illustrating a change in vehicle speed predicted by the driving behavior prediction unit according to the first embodiment of the present invention. FIG. 7 shows that the length of the arrow 51 indicates the magnitude of the curve entry speed V1 predicted at the curve entry point A in the curve section (curvature r, road width w) between the points A to C in front of the traveling direction. The length of the arrow 52 indicates the magnitude of the curve turning speed V2 predicted at the curve middle point B, and the length of the arrow 53 indicates the magnitude of the curve escape speed V3 predicted at the curve exit point C.

  The recommended action calculation unit 24 uses the road information database 32 to calculate a recommended speed at which each curve can be safely traveled (step S25). Here, the recommended speed may be calculated from the road shape such as curvature, road width, and gradient stored in the road information database 32, or the legal speed defined for each road in the road information database 32 is stored. Alternatively, the legal speed may be used as the recommended speed.

  The risk determination unit 23 exceeds the recommended speed when passing the curve by comparing the change in the vehicle speed at the time of passing the curve predicted in consideration of the past driving behavior (driver's habit) and the recommended speed. A road section in which the predicted traveling state does not match the recommended condition is detected (step S26).

  FIG. 8 is a conceptual diagram illustrating the risk determination according to the first embodiment of the present invention, and shows a predicted speed change 61 and a recommended speed 62 from the curve entry point A to the exit point C. It is. The curve approach speed at the curve entry point A is V1, the curve turning speed at the curve middle point B is V2, the curve exit speed at the curve exit point C is V3, and the recommended speed that can safely pass through the curve is Vth. The danger determination unit 23 determines that the sections 63 and 64 in which the predicted speed change 61 exceeds the recommended speed 62 (speed Vth) are dangerous sections.

  The presenting unit 25 generates information to present the section determined to be dangerous by the risk determining unit 23 to the driver and outputs the information to the output unit 81 to give a warning. FIG. 9 is a diagram showing an example of the dangerous zone display according to the first embodiment of the present invention. As shown in FIG. 9, the presentation unit 25 refers to the map information stored in the road information database 32, superimposes information for identifying the sections 63 and 64 determined to be dangerous, and displays the information via the display device 82. A warning is given to the driver. At the same time, an alarm sound may be output from the speaker 83.

  In addition, the presentation unit 25 creates a schematic simple figure from the traffic environment in the curve such as the curvature of the curve, the road width, and the slope instead of displaying the dangerous section on the map, and displays the dangerous section on the simple figure. It may be displayed. As a result, a huge amount of map data for map display can be reduced. In addition, by displaying a schematic simple figure, it is possible to present the dangerous section more easily for the driver.

  According to the first embodiment of the present invention, the vehicle travels before entering the curve by predicting the driving behavior at the time of passing the curve based on the past driving behavior of the vehicle and making a risk judgment. It is possible to detect areas that can be dangerous at times, and by making driving behavior predictions taking into account the driving tendency of the driver, risk judgment and presentation according to the driver are taken into account, taking into account the driver's habit be able to.

  In addition, as the traffic environment information on the curve of the driving behavior database, the curvature, the road width, and the gradient are given as examples. However, other information may be added. FIG. 10 is a diagram showing another example of driving behavior information accumulated in the driving behavior database according to the first embodiment of the present invention. As shown in FIG. 10, the driving behavior database 31 includes vehicle speed information in a curve turning direction (right curve / left curve) and a vehicle's vehicle information at a predetermined distance before the curve (vehicle speed at 100 meters before the curve, etc.). The driving behavior prediction unit 22 accumulates and can predict the driving behavior on the driver's curve with higher accuracy by using these parameters.

(Second Embodiment)
FIG. 11 is a block diagram showing the main configuration of a danger information detection apparatus according to the second embodiment of the present invention. In FIG. 11, the same components as those in FIG.

  11, in addition to the components in FIG. 1, the vehicle 10 is provided with a traffic condition detection unit 14 having a preceding vehicle information detection unit 15, an oncoming vehicle information detection unit 16, and a weather information detection unit 17. And the driving action collection part 21 which functions as an example of the traffic condition acquisition part of this embodiment acquires the information detected by the traffic condition detection part 14 in addition to the information detected by the vehicle information detection part 11. The danger information detection device 20 determines a dangerous section using these acquired information.

  In this embodiment, the traffic situation on the curve is the presence / absence of a preceding vehicle, the presence / absence of an oncoming vehicle, and weather information.

  About the danger information detection method comprised as mentioned above, the operation | movement is demonstrated using the flowchart of FIG.12 and FIG.13.

  FIG. 12 is a flowchart showing the procedure of the driving action accumulation process according to the second embodiment of the present invention, in which the driving action accumulation process for accumulating in the driving action database 31 the traffic environment of the passing curve and the speed change in passing the curve. Will be described.

  The position sensor 12 and the vehicle sensor 13 always collect the position and vehicle speed information of the host vehicle (step S31). Based on the collected position information, the driving behavior collection unit 21 determines whether or not a curve exists on the road ahead in the traveling direction (step S32). When it is determined that the curve does not exist (NO in step S32), the process returns to step S31 again to acquire vehicle information and determine the presence of the curve.

  On the other hand, when it is determined that there is a curve (YES in step S32), the traffic environment information including the curvature, road width, and gradient in the forward curve is acquired from the road information database 32 (step S33).

  The driving behavior collection unit 12 acquires a change in vehicle speed when the host vehicle actually passes this curve from the vehicle speed sensor 13 (step S34). Further, the traffic situation detection unit 14 detects the traffic situation such as the presence of the preceding vehicle, the presence of the oncoming vehicle, and weather information by acquiring an image ahead of the vehicle (step S35), and the driving behavior collection unit 21 Stores the obtained traffic environment information of the curve, the change in the vehicle speed on the curve, and the traffic situation when passing the curve in the driving behavior database 32 (step S36).

  FIG. 14 is a diagram showing an example of driving behavior information accumulated in the driving behavior database according to the second embodiment of the present invention. As shown in FIG. 14, in the driving behavior database 32, traffic environment information on a curve, traffic situation information, and driving behavior on a curve are stored in association with each other. This makes it possible for the driver to change the shape of the curve (curvature, road width, slope) under what kind of intersection (presence / absence of preceding vehicle, presence / absence of oncoming vehicle, weather, etc.) (Passing speed, turning speed, escape speed) can be stored in the driving behavior database. Here, the accumulated vehicle speed as the driving action is not limited to three places, and may be further subdivided. This makes it possible to perform processing with higher accuracy.

  FIG. 13 is a flowchart showing the procedure of the driving behavior prediction processing and the dangerous zone presentation processing according to the second embodiment of the present invention, using the traffic environment of the forward curve and the accumulated driving behavior database. A driving behavior prediction / danger presentation process that predicts a change in vehicle speed and presents danger information by comparing with a recommended speed will be described.

  From the position sensor 12 and the vehicle sensor 13, the position of the host vehicle and vehicle speed information are always collected (step S41). Based on the collected position information, the driving behavior collection unit 21 determines whether or not a curve exists on the road ahead in the traveling direction (step S42). When it is determined that the curve does not exist (NO in step S42), the process returns to step S41 again to acquire vehicle information and determine the presence of the curve.

  On the other hand, when it is determined that there is a curve (YES in step S42), the traffic environment information including the curvature, road width, and gradient in the forward curve is acquired from the road information database 32 (step S43). At the same time, the driving behavior collection unit 21 acquires traffic status information including the presence / absence of a preceding vehicle, the presence / absence of an oncoming vehicle, weather information, and the like detected by the traffic status detection unit 14 from an image ahead of the vehicle (step) S44).

  Next, the driving behavior prediction unit 22 considers the driving habits of the driver and the surrounding traffic situation by using the traffic environment information on the forward curve, the current traffic situation, and the accumulated driving behavior database 31. Thus, the vehicle speed change on the forward curve to be passed is predicted (step S45).

  Here, a vehicle speed change prediction method in the driving behavior prediction unit will be described with reference to FIG. FIG. 15 is a conceptual diagram illustrating a driving behavior prediction method according to the second embodiment of the present invention. In FIG. 15, reference numeral 71 indicates driving behavior data stored in the driving behavior database 31, and reference numeral 72 indicates traffic environment information and traffic condition information on a forward curve to be passed.

  In the driving behavior prediction unit 22, parameters of road information (curvature r, road width w, gradient h in the example of FIG. 15) based on driving behavior data 71 accumulated in the driving behavior database 31 in advance and a curve are used. The relationship between traffic condition information (previous vehicle presence / absence c_front, oncoming vehicle presence / absence (c_counter, weather we) and travel information parameters (curve entry speed v1, curve turning speed v2, curve escape speed v3) is calculated in advance. For example, model equations such as equations (7) to (9) are converted into constants α1, β1, γ1, δ1, ε1, ζ1, α2, β2, γ2, δ2, using a method such as multiple regression analysis. ε2, ζ2, α3, β3, γ3, δ3, ε3, and ζ3 are calculated in advance.

v1 = α1 * r + β1 * w + γ1 * h + δ1 * c_front + ε1 * c_counter + ζ1 * we
... (7)
v2 = α2 * r + β2 * w + γ2 * h + δ2 * c_front + ε2 * c_counter + ζ2 * we
... (8)
v3 = α3 * r + β3 * w + γ3 * h + δ3 * c_front + ε3 * c_counter + ζ3 * we
... (9)

  The driving behavior prediction unit 22 obtains the traffic environment and traffic conditions (R, W, H, C_front, C_counter, WE) in the forward curve to be passed from now obtained in the above formulas (7) to (9) and step S43. ) Is used to predict vehicle speed changes (V1, V2, V3) on the forward curve as in the following equations (10) to (12).

V1 = α1 * R + β1 * W + γ1 * H + δ1 * C_front + ε1 * C_counter + ζ1 * WE
... (10)
V2 = α2 * R + β2 * W + γ2 * H + δ2 * C_front + ε2 * C_counter + ζ2 * WE
(11)
V3 = α3 * R + β3 * W + γ3 * H + δ3 * C_front + ε3 * C_counter + ζ3 * WE
(12)

  In addition, when calculating a detailed speed change, a method such as vector quantization is used to predict a continuous change in vehicle speed from the traffic environment and traffic conditions (R, W, H, C_front, C_counter, WE). May be.

  Since the processing after the calculation of the recommended speed (step S46) is the same as the processing after step S25 described with reference to FIG. 4 in the first embodiment, the description is omitted.

  According to the second embodiment of the present invention, the vehicle travels before entering the curve by predicting the driving behavior at the time of passing the curve based on the past driving behavior of the vehicle and making a risk judgment. It is possible to detect areas that can sometimes be dangerous, and by predicting driving behavior in consideration of the driving tendency and traffic conditions of the driver, it is highly accurate depending on the driver taking into account the driver's habit Risk judgment and presentation can be made.

  In addition, by adding a factor that affects the driving behavior on the curve, such as poor visibility on the curve, as the traffic status information on the curve collected by the traffic status detection unit 14, the past driving behavior is further used. It is possible to accurately predict the driving behavior on the driver's curve.

  INDUSTRIAL APPLICABILITY The danger information detection device and the danger information detection method of the present invention have an effect of being able to detect an area that can be dangerous when traveling on a curve before the vehicle enters the curve, and are useful for driving assistance devices and the like.

The block diagram which shows the main structures of the danger information detection apparatus which concerns on the 1st Embodiment of this invention. Diagram explaining how to calculate curvature The flowchart which shows the procedure of the driving | operation accumulation | storage process which concerns on the 1st Embodiment of this invention. The flowchart which shows the procedure of the driving action prediction process which concerns on the 1st Embodiment of this invention, and a dangerous area presentation process. The figure which shows an example of the driving action information accumulate | stored in the driving action database which concerns on the 1st Embodiment of this invention. The conceptual diagram explaining the driving action prediction method which concerns on the 1st Embodiment of this invention. The conceptual diagram explaining the vehicle speed change estimated by the driving action prediction part which concerns on the 1st Embodiment of this invention. The conceptual diagram explaining the danger determination which concerns on the 1st Embodiment of this invention The figure which shows an example of the danger area display which concerns on the 1st Embodiment of this invention. The figure which shows the other example of the driving action information accumulate | stored in the driving action database which concerns on the 1st Embodiment of this invention. The block diagram which shows the main structures of the danger information detection apparatus which concerns on the 2nd Embodiment of this invention. The flowchart which shows the procedure of the driving | operation accumulation | storage process which concerns on the 2nd Embodiment of this invention. The flowchart which shows the procedure of the driving action prediction process which concerns on the 2nd Embodiment of this invention, and a danger area presentation process. The figure which shows an example of the driving action information accumulate | stored in the driving action database which concerns on the 2nd Embodiment of this invention. The conceptual diagram explaining the driving action prediction method which concerns on the 2nd Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Vehicle 11 Vehicle information detection part 12 Position sensor 13 Vehicle speed sensor 14 Traffic condition detection part 15 Leading vehicle information 16 Oncoming vehicle information 17 Weather information 20 Danger detection / presentation device 21 Driving behavior detection part 22 Driving behavior prediction part 23 Risk judgment part 24 Recommended action calculation unit 25 Presentation unit 31 Driving action database 32 Road information database 41 Driving action database 42 Traffic environment information on forward curve 51 Curve approach speed 52 Curve turning speed 53 Curve escape speed 61 Predicted speed change 62 Recommended speed 63 Danger section 64 Dangerous section 71 Driving behavior data 72 Traffic environment information and traffic situation information 81 Output unit 82 Display device 83 Speaker

Claims (11)

A position information acquisition unit that acquires position information indicating the current position of the host vehicle;
A travel information acquisition unit that acquires travel information indicating the travel state of the host vehicle;
A map information storage unit for storing map information including road information on the road shape;
A driving action output unit that refers to the map information storage unit based on the acquired position information, and outputs the acquired driving information and driving road information as driving action information in association with the road information when the driving information is acquired. When,
A driving behavior storage unit that accumulates driving behavior information output from the driving behavior output unit;
Based on the acquired position information, a curve section extracting unit that extracts a curve section existing ahead of the traveling direction of the host vehicle from the map information storage unit;
Based on the driving behavior information accumulated in the driving behavior storage unit, a driving behavior prediction unit that predicts a driving state in the extracted curve section and obtains it as predicted driving information;
A recommended action acquisition unit for acquiring a recommended condition indicating a recommended driving state in the extracted curve section;
A dangerous section determination unit that compares the predicted traveling information with the recommended condition and determines a road section in which the predicted traveling information does not match the recommended condition as a dangerous section;
A danger information detection apparatus comprising: a danger section presenting section that presents a dangerous section determined by the dangerous section determination section. The danger information detection device according to claim 1,
The driving behavior prediction unit calculates a relationship between a parameter of the road information and a parameter of the driving information based on the driving behavior information accumulated in the driving behavior storage unit, and the extracted using the relationship A danger information detection device that acquires the predicted travel information from a parameter of road information of a curved section. The danger information detection device according to claim 1 or 2,
The risk information detection apparatus, wherein the predicted travel information includes a change in vehicle speed in the extracted curve section. The danger information detection device according to claim 1 or 2,
The predicted travel information is a danger information detection device including a change in vehicle acceleration in the extracted curve section. The danger information detection device according to any one of claims 1 to 4,
The danger information detection apparatus, wherein the road information includes at least one of a curve width, a bank angle, a curvature, and a road gradient. The danger information detection device according to any one of claims 1 to 5,
A traffic condition detection unit that detects traffic condition information including at least one of information indicating the presence or absence of a preceding vehicle when passing a curve, information indicating the presence or absence of an oncoming vehicle, and information indicating weather;
The driving behavior storage unit is a danger information detection device that accumulates the traffic situation information as the driving behavior information. The danger information detection device according to any one of claims 1 to 6,
The dangerous information presenting device, wherein the dangerous information presenting unit superimposes and displays the dangerous information on the map information read from the map information storage. The danger information detection device according to any one of claims 1 to 6,
The dangerous section presenting unit generates display information according to the shape of the extracted curve section based on road information included in the map information read from the map information storage unit, and the generated display of the dangerous section A danger information detection device that superimposes and displays information. The danger information detection device according to any one of claims 1 to 8,
The map data storage unit stores speed limit information corresponding to a road,
The recommended action acquisition unit is a danger information detection device that acquires a speed limit in the extracted curve section from speed limit speed information stored in the map data storage unit. Obtaining position information indicating the current position of the host vehicle;
Obtaining travel information indicating the travel state of the host vehicle;
Based on the acquired position information, map information including road information related to the road shape stored in the map information storage unit is referred to, and the acquired travel information corresponds to the road information traveling at the time of acquiring the travel information. And the step of accumulating in the driving behavior storage unit as driving behavior information,
Based on the acquired position information, a step of extracting a curve section existing ahead of the traveling direction of the host vehicle from the map information storage unit;
Based on the driving action information accumulated in the driving action storage unit, predicting the driving state in the extracted curve section and obtaining it as predicted driving information;
Obtaining a recommended condition indicating a recommended driving state in the extracted curve section;
Comparing the predicted travel information and the recommended condition, and determining a road section where the predicted travel information does not match the recommended condition as a dangerous section;
A danger information detection method comprising: presenting a dangerous section determined by the dangerous section determination unit.   A danger information detection program for executing each step according to claim 10.

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