CN107886772A - Weak tendency traffic participant collision warning systems - Google Patents
Weak tendency traffic participant collision warning systems Download PDFInfo
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- CN107886772A CN107886772A CN201711107165.9A CN201711107165A CN107886772A CN 107886772 A CN107886772 A CN 107886772A CN 201711107165 A CN201711107165 A CN 201711107165A CN 107886772 A CN107886772 A CN 107886772A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/161—Decentralised systems, e.g. inter-vehicle communication
- G08G1/163—Decentralised systems, e.g. inter-vehicle communication involving continuous checking
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
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Abstract
The invention discloses weak tendency traffic participant collision warning systems, vehicle end module combines this car location information, speed information, pedestrian position information and pedestrian's velocity information and judges whether both space paths intersect, disjoint parallel condition, judge whether that both have risk of collision by judging whether parallel transverse spacing is too short, and in order to reduce rate of false alarm, further calculate whether vehicle may form pursuit relation apart from both upper with pedestrian's parallel longitudinal direction on longitudinal coordinate, so as to carry out risk of collision alarm；In addition to the concept that path is intersected, the parallel concept in path of introducing judges the method for risk of collision, can reduce rate of false alarm, while the traffic safety scene of weak tendency traffic participant pedestrian is more comprehensively considered, is protected safely.
Description
Technical field
The present invention relates to a kind of vehicle drive assist system, more particularly to weak tendency traffic participant anti-collision warning method.
Background technology
The drive assist system of prior art based on active sensor mainly based on being detected, for being collided between vehicle
The driving auxiliary avoided.And according to traffic accident annual statistics, 20% or so traffic accident is to collide pedestrian accident, and pedestrian,
Bicycle, motorcycle, because it lacks external crash protection facility, crash as weak tendency traffic participant with vehicle
The death rate it is of a relatively high.A kind of consider a variety of pedestrians and vehicle scene, the weak tendency of path factor therefore, it is necessary to provide
Traffic participant anti-collision warning method, improve the accuracy that anti-collision warning judges.
The content of the invention
The invention discloses weak tendency traffic participant collision warning systems, consider under parallel path, crossedpath factor
Whether pedestrian and vehicle Encounter Time difference improve anti-collision warning accuracy in early warning range.
Weak tendency traffic participant collision warning systems disclosed by the invention, including pedestrian's end module and vehicle end module, institute
It is as follows including vehicle localization module, vehicle-mounted ECU module and alarm module, step to state vehicle end module：
The speed of pedestrian, acceleration, three dimensional local information are sent to vehicle end module by step 1) pedestrian's end module；
Step 2) the vehicle end module gathers the speed of this car, acceleration, three-dimensional position letter by vehicle localization module
Breath；
Vehicle-mounted ECU in step 3) vehicle end module is calculated using this car as the center of circle, and R_Danger is the vehicle collision of radius
Potential danger region, wherein R_Danger=V_HV × (T_Reaction+T_Braking)；
V_HV is this car present speed；
T_Reaction is the time of driver's reaction that statistical method obtains；
T_Braking is maximum braking time；
Whether step 4) judges pedestrian in vehicle collision potential danger region；
Vehicle-mounted ECU calculates pedestrian and the distance S of this car according to pedestrian and Ben Che three dimensional local information；
If S is more than R_Danger, pedestrian is not in danger zone；
If S is less than or equal to R_Danger, then it represents that pedestrian is in danger zone, then into step 5)；
Step 5) calculates whether pedestrian's direct of travel and vehicle heading have intersection point,
There is intersection point, into step 6)；
Without intersection point, it is whether parallel with route or travel by vehicle to calculate pedestrian；It is such as not parallel, judge collisionless danger；As parallel,
Then compare vehicle and the horizontal spacing of pedestrian, if horizontal spacing is less than or equal to setting spacing dSetting, show that vehicle has collision pedestrian's
It is dangerous；As vehicle and the horizontal spacing of pedestrian are more than setting spacing dSetting, judge collisionless danger.
Step 6)
Calculate pedestrian and the time difference dT=of this car range intersections | T_P-T_HV |, compare whether dT is less than or equal to early warning threshold
Value T_warn, if the alarm module alarm less than or equal to if, if judging more than if, collisionless is dangerous；Wherein, pedestrian to intersection point when
Between T_P=S_P/V_P, pedestrian's speed is V_P, and pedestrian's range intersections distance is S_P；This car to intersection point time T_HV=S_
HV/V_HV, the distance S_HV of this car range intersections, this car vehicle velocity V _ HV.
Further, it is such as parallel in step 5), then compare vehicle and the horizontal spacing of pedestrian, if horizontal spacing is less than or equal to
Set spacing dSetting, show that vehicle has the danger of collision pedestrian, then into step 7)；
Step 7)
Calculate whether this car longitudinal direction catch-up time T_HVtoP parallel with pedestrian's longitudinal direction is less than or equal to threshold value of warning
T_warn, if the alarm module alarm less than or equal to if, if judging more than if, collisionless is dangerous；Wherein, T_HVtoP=S_HVtoP/
(V_HV-V_P), this car vehicle velocity V _ HV, pedestrian speed V_P, vehicle and pedestrian's distance S_HVtoP.
Further, threshold value of warning T_warn=vehicle commander/speed+early warning buffer time.
Further, warning message is sent to board units HMI module by alarm module, and board units HMI module is carried out
Image and buzzing alarm.
Further, warning message is sent to pedestrian's end module by alarm module, and warning message includes pedestrian ID, Hang Renwei
Put, risk of collision warning message.
Further, three dimensional local information includes：Longitude, latitude, altitude information.
Further, spacing d is setSettingFor 2m.
Advantageous effects of the present invention are：
Vehicle end module judges two with reference to this car location information, speed information, pedestrian position information and pedestrian's velocity information
Whether person's space path intersects, disjoint parallel condition, judges whether two by judging whether parallel transverse spacing is too short
Whether person has risk of collision, and in order to reduce rate of false alarm, further calculate vehicle and may with pedestrian's parallel longitudinal direction apart from both upper
Pursuit relation is formed on longitudinal coordinate, so as to carry out risk of collision alarm；In addition to the concept that path is intersected, the path of introducing is put down
The method that row concept judges risk of collision, rate of false alarm can be reduced, while cause the traffic peace of weak tendency traffic participant pedestrian
Whole scene more comprehensively considers, is protected safely.
Brief description of the drawings
Fig. 1 is weak tendency traffic participant collision warning systems workflow diagram of the present invention.
Embodiment
Weak tendency traffic participant collision warning systems, including：Pedestrian's end module and vehicle end module.Vehicle end module includes
Vehicle localization module, vehicle-mounted ECU module and alarm module.
The weak tendency traffic participant collision warning systems job step is as follows：
Step 1) pedestrian end module is by the speed of pedestrian, acceleration, three dimensional local information (longitude, latitude, altitude information)
It is sent to vehicle end module；
Step 2) vehicle end module gathers the speed of this car, acceleration, three dimensional local information (warp by vehicle localization module
Degree, latitude, altitude information)；
Vehicle-mounted ECU in step 3) vehicle end module is calculated using this car as the center of circle, and R_Danger is the vehicle collision of radius
Potential danger region, wherein R_Danger=V_HV × (T_Reaction+T_Braking)；
V_HV is this car present speed；
T_Reaction is the time of driver's reaction that statistical method obtains；
T_Braking is maximum braking time；
Whether step 4) judges pedestrian in vehicle collision potential danger region；
Vehicle-mounted ECU calculates pedestrian and the distance S of this car according to pedestrian and Ben Che three dimensional local information；
If S is more than R_Danger, pedestrian is not in danger zone；
If S is less than or equal to R_Danger, then it represents that pedestrian is in danger zone, then into step 5)；
Step 5) calculates whether pedestrian's direct of travel and vehicle heading have intersection point,
There is intersection point, into step 6)；
Without intersection point, it is whether parallel with route or travel by vehicle to calculate pedestrian；It is such as not parallel, judge collisionless danger；As parallel,
Then compare vehicle and the horizontal spacing of pedestrian, if horizontal spacing is less than or equal to setting spacing dSetting(may be set to 2m) shows vehicle
There is the danger of collision pedestrian, into step 7)；As vehicle and the horizontal spacing of pedestrian are more than setting spacing dSetting, judge collisionless
It is dangerous.
Step 6)
Calculate pedestrian and the time difference dT=of this car range intersections | T_P-T_HV |, compare whether dT is less than or equal to early warning threshold
Value T_warn, threshold value of warning T_warn=vehicle commander/speed+early warning buffer time, if the alarm module alarm less than or equal to if, if greatly
In then judge collisionless danger；Wherein, pedestrian is to the time T_P=S_P/V_P of intersection point, and pedestrian's speed is V_P, and pedestrian's distance is handed over
Point distance is S_P；This car is to the time T_HV=S_HV/V_HV of intersection point, the distance S_HV of this car range intersections, and this car vehicle velocity V _
HV。
Step 7)
Calculate whether this car longitudinal direction catch-up time T_HVtoP parallel with pedestrian's longitudinal direction is less than or equal to threshold value of warning
T_warn, if the alarm module alarm less than or equal to if, if judging more than if, collisionless is dangerous；Wherein, T_HVtoP=S_HVtoP/
(V_HV-V_P), this car vehicle velocity V _ HV, pedestrian speed V_P, vehicle and pedestrian's distance S_HVtoP.This car longitudinal direction and pedestrian
The parallel catch-up time of longitudinal direction looks up to be vertical, the catch-up time that Ben Che and pedestrian's fore-and-aft distance need when being 0.
Warning message is sent to board units HMI (HumanMachineInterface, man-machine interaction) mould by alarm module
Block, board units HMI module carry out image and buzzing alarm；Warning message is sent to pedestrian's end module by alarm module, alarm
Packet ID containing pedestrian, pedestrian position, risk of collision warning message, pedestrian's end module compare the pedestrian ID entrained by warning information
It is whether identical with itself pedestrian ID.If ID is different, pedestrian's end module is without dither and phonetic warning.If ID is identical, OK
People's end module carries out dither and phonetic warning.
Claims (7)
1. weak tendency traffic participant collision warning systems, it is characterised in that：Including pedestrian's end module and vehicle end module, the car
It is as follows that end module includes vehicle localization module, vehicle-mounted ECU module and alarm module, step：
The speed of pedestrian, acceleration, three dimensional local information are sent to vehicle end module by step 1) pedestrian's end module；
Step 2) the vehicle end module gathers the speed of this car, acceleration, three dimensional local information by vehicle localization module；
Vehicle-mounted ECU in step 3) vehicle end module is calculated using this car as the center of circle, and R_Danger is that the vehicle collision of radius is potential
Danger zone, wherein R_Danger=V_HV × (T_Reaction+T_Braking)；
V_HV is this car present speed；
T_Reaction is the time of driver's reaction that statistical method obtains；
T_Braking is maximum braking time；
Whether step 4) judges pedestrian in vehicle collision potential danger region；
Vehicle-mounted ECU calculates pedestrian and the distance S of this car according to pedestrian and Ben Che three dimensional local information；
If S is more than R_Danger, pedestrian is not in danger zone；
If S is less than or equal to R_Danger, then it represents that pedestrian is in danger zone, then into step 5)；
Step 5) calculates whether pedestrian's direct of travel and vehicle heading have intersection point,
There is intersection point, into step 6)；
Without intersection point, it is whether parallel with route or travel by vehicle to calculate pedestrian；It is such as not parallel, judge collisionless danger；It is such as parallel, then compare
Compared with vehicle and the horizontal spacing of pedestrian, if horizontal spacing is less than or equal to setting spacing dSetting, show that vehicle has the danger of collision pedestrian
Danger；As vehicle and the horizontal spacing of pedestrian are more than setting spacing dSetting, judge collisionless danger.
Step 6)
Calculate pedestrian and the time difference dT=of this car range intersections | T_P-T_HV |, compare whether dT is less than or equal to threshold value of warning T_
Warn, if the alarm module alarm less than or equal to if, if judging more than if, collisionless is dangerous；Wherein, pedestrian to intersection point time T_P
=S_P/V_P, pedestrian's speed are V_P, and pedestrian's range intersections distance is S_P；This car to intersection point time T_HV=S_HV/V_
HV, the distance S_HV of this car range intersections, this car vehicle velocity V _ HV.
2. weak tendency traffic participant collision warning systems as claimed in claim 1, it is characterised in that：As parallel in step 5),
Then compare vehicle and the horizontal spacing of pedestrian, if horizontal spacing is less than or equal to setting spacing dSetting, show that vehicle has collision pedestrian's
Danger, then into step 7)；
Step 7)
Calculate whether this car longitudinal direction catch-up time T_HVtoP parallel with pedestrian's longitudinal direction is less than or equal to threshold value of warning T_
Warn, if the alarm module alarm less than or equal to if, if judging more than if, collisionless is dangerous；Wherein, T_HVtoP=S_HVtoP/
(V_HV-V_P), this car vehicle velocity V _ HV, pedestrian speed V_P, vehicle and pedestrian's distance S_HVtoP.
3. weak tendency traffic participant collision warning systems as claimed in claim 1 or 2, it is characterised in that：Threshold value of warning T_
Warn=vehicle commander/speed+early warning buffer time.
4. weak tendency traffic participant collision warning systems as claimed in claim 3, it is characterised in that：Alarm module is by alarm signal
Breath is sent to board units HMI module, and board units HMI module carries out image and buzzing alarm.
5. weak tendency traffic participant collision warning systems as claimed in claim 4, it is characterised in that：Alarm module is by alarm signal
Breath is sent to pedestrian's end module, and warning message includes pedestrian ID, pedestrian position, risk of collision warning message.
6. weak tendency traffic participant collision warning systems as claimed in claim 5, it is characterised in that：Three dimensional local information bag
Include：Longitude, latitude, altitude information.
7. weak tendency traffic participant collision warning systems as claimed in claim 6, it is characterised in that：Set spacing dSettingFor 2m.
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| CN201711107165.9A CN107886772A (en) | 2017-11-10 | 2017-11-10 | Weak tendency traffic participant collision warning systems |
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108615410A (en) * | 2018-05-15 | 2018-10-02 | 中国民航大学 | The system and control method of the pedestrian that is blocked are identified for airport pilotless automobile |
| CN109035865A (en) * | 2018-08-29 | 2018-12-18 | 中国科学院微电子研究所 | Data processing method and device for security assistance |
| CN109448439A (en) * | 2018-12-25 | 2019-03-08 | 科大讯飞股份有限公司 | Vehicle safe driving method and device |
| CN109686124A (en) * | 2018-11-28 | 2019-04-26 | 法法汽车(中国)有限公司 | Anticollision based reminding method and system, storage medium and electronic equipment |
| CN109817021A (en) * | 2019-01-15 | 2019-05-28 | 北京百度网讯科技有限公司 | A kind of laser radar trackside blind area traffic participant preventing collision method and device |
| CN110162062A (en) * | 2019-06-10 | 2019-08-23 | 北京百度网讯科技有限公司 | Vehicle driving planing method, device, equipment and readable storage medium storing program for executing |
| CN110544377A (en) * | 2019-08-31 | 2019-12-06 | 武汉理工大学 | intersection pedestrian collision avoidance method based on vehicle-road cooperation |
| CN111477003A (en) * | 2020-04-13 | 2020-07-31 | 联陆智能交通科技(上海)有限公司 | Calculation method and system for acquiring time of collision with weak traffic and medium |
| CN113212449A (en) * | 2021-04-30 | 2021-08-06 | 重庆长安汽车股份有限公司 | Function trigger parameter adjusting method of front collision early warning system |
| CN114220295A (en) * | 2021-11-10 | 2022-03-22 | 岚图汽车科技有限公司 | Traffic early warning system, control method, storage medium, control device, and vehicle |
| CN114620013A (en) * | 2022-03-16 | 2022-06-14 | 中国第一汽车股份有限公司 | Method, device, equipment and medium for protecting pedestrians in front of vehicle |
| CN114730527A (en) * | 2019-12-12 | 2022-07-08 | 英特尔公司 | Vulnerable road user safety technology based on responsibility sensitive safety |
| CN114999224A (en) * | 2022-04-29 | 2022-09-02 | 湖南喜宝达信息科技有限公司 | Electric bicycle and environment intelligent sensing obstacle avoidance method and storage medium thereof |
| WO2023035710A1 (en) * | 2021-09-10 | 2023-03-16 | 广州汽车集团股份有限公司 | Collision early-warning method for vulnerable traffic participant, and system thereof, and storage medium |
| CN116246489A (en) * | 2023-02-06 | 2023-06-09 | 云控智行科技有限公司 | Pedestrian protection method, device and equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108615410A (en) * | 2018-05-15 | 2018-10-02 | 中国民航大学 | The system and control method of the pedestrian that is blocked are identified for airport pilotless automobile |
| CN109035865A (en) * | 2018-08-29 | 2018-12-18 | 中国科学院微电子研究所 | Data processing method and device for security assistance |
| CN109686124A (en) * | 2018-11-28 | 2019-04-26 | 法法汽车(中国)有限公司 | Anticollision based reminding method and system, storage medium and electronic equipment |
| CN109448439A (en) * | 2018-12-25 | 2019-03-08 | 科大讯飞股份有限公司 | Vehicle safe driving method and device |
| CN109817021A (en) * | 2019-01-15 | 2019-05-28 | 北京百度网讯科技有限公司 | A kind of laser radar trackside blind area traffic participant preventing collision method and device |
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| CN114730527A (en) * | 2019-12-12 | 2022-07-08 | 英特尔公司 | Vulnerable road user safety technology based on responsibility sensitive safety |
| CN111477003A (en) * | 2020-04-13 | 2020-07-31 | 联陆智能交通科技(上海)有限公司 | Calculation method and system for acquiring time of collision with weak traffic and medium |
| CN113212449A (en) * | 2021-04-30 | 2021-08-06 | 重庆长安汽车股份有限公司 | Function trigger parameter adjusting method of front collision early warning system |
| CN113212449B (en) * | 2021-04-30 | 2022-06-07 | 重庆长安汽车股份有限公司 | Function trigger parameter adjusting method of front collision early warning system |
| WO2023035710A1 (en) * | 2021-09-10 | 2023-03-16 | 广州汽车集团股份有限公司 | Collision early-warning method for vulnerable traffic participant, and system thereof, and storage medium |
| CN114220295A (en) * | 2021-11-10 | 2022-03-22 | 岚图汽车科技有限公司 | Traffic early warning system, control method, storage medium, control device, and vehicle |
| CN114220295B (en) * | 2021-11-10 | 2023-03-14 | 岚图汽车科技有限公司 | Traffic early warning system, control method, storage medium, control device, and vehicle |
| CN114620013A (en) * | 2022-03-16 | 2022-06-14 | 中国第一汽车股份有限公司 | Method, device, equipment and medium for protecting pedestrians in front of vehicle |
| CN114999224A (en) * | 2022-04-29 | 2022-09-02 | 湖南喜宝达信息科技有限公司 | Electric bicycle and environment intelligent sensing obstacle avoidance method and storage medium thereof |
| CN114999224B (en) * | 2022-04-29 | 2023-11-14 | 湖南喜宝达信息科技有限公司 | Electric bicycle, intelligent environment sensing obstacle avoidance method for electric bicycle and storage medium |
| CN116246489A (en) * | 2023-02-06 | 2023-06-09 | 云控智行科技有限公司 | Pedestrian protection method, device and equipment |
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