CN113370973A - Forward collision early warning algorithm considering driving intention prediction of front vehicle - Google Patents
Forward collision early warning algorithm considering driving intention prediction of front vehicle Download PDFInfo
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- CN113370973A CN113370973A CN202110619312.0A CN202110619312A CN113370973A CN 113370973 A CN113370973 A CN 113370973A CN 202110619312 A CN202110619312 A CN 202110619312A CN 113370973 A CN113370973 A CN 113370973A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
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- Automation & Control Theory (AREA)
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- Mathematical Physics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention relates to a forward collision early warning algorithm, which comprises the following steps: collecting a vehicle-mounted forward camera video; obtaining the running state of a vehicle in front of the vehicle in the video through target detection, and analyzing a forward collision risk scene; determining key indexes and parameters of a forward collision risk scene to obtain the correlation between the motion state of a forward vehicle and the running state of the vehicle in the scene; dividing the state type of the front vehicle, the change type of the vehicle distance and the driving state type of the vehicle, and establishing a driving intention prediction model of the front vehicle; and the driving intention prediction result of the front vehicle is brought into a forward collision early warning algorithm, so that the accuracy of the forward collision early warning algorithm is improved. Compared with the prior art, the early warning method has the advantages of higher early warning accuracy, simpler calculation steps, less time consumption and low requirement on hardware.
Description
Technical Field
The invention relates to the field of safe driving of automobiles, in particular to forward collision early warning considering the prediction of driving intention of a front automobile.
Background
Among the reasons for the occurrence of the rear-end collision accident, the failure of maintaining a safe distance due to the inattention of the driver, delayed driving reaction and wrong danger perception cognition is the main factors for the final occurrence of the collision. It is studied that 90% of factors causing the occurrence of an accident are related to a driver in a rear-end accident occurrence mechanism. Aiming at rear-end accidents, the emergence of a Forward Collision avoidance Warning (FCW) system provides great potential for improving driving safety and relieving and reducing the occurrence of rear-end accidents. The FCW system utilizes sensors to detect the road and motion conditions in front of the vehicle, and gives alarm information to a driver at a proper time when the front side has potential collision danger, so that the driver is assisted to avoid collision and accidents more effectively.
The development and study of FCW systems is now attracting worldwide attention, and to date, mature systems have been developed and tested by automobile manufacturers in many countries. At the same time, the potentially enormous safety gains of FCW systems have also been demonstrated through several studies. Internationally, active safety systems for vehicles are gaining increasing attention, and developed countries have begun to progressively regulate the installation and configuration of vehicles with respect to FCW systems. In comparison, the development of the FCW system is still in the initial stage in China, especially far behind the developed countries abroad in the technical aspect. In addition, due to differences in driving behaviors and habits, FCW systems that are applied abroad are not necessarily applicable to chinese drivers and cannot be accepted by chinese drivers.
Disclosure of Invention
The present invention is directed to overcoming the above-mentioned drawbacks of the prior art and providing a forward collision warning method considering the prediction of the driving intention of a leading vehicle.
The purpose of the invention can be realized by the following technical scheme:
a forward collision warning considering a prediction of driving intent of a preceding vehicle, the method comprising the steps of:
step S1: acquiring a front vehicle motion video acquired by a camera in front of a vehicle;
step S2: analyzing common risk scenes and vehicle running characteristics in a forward collision scene;
step S3: determining a front vehicle through target detection, and detecting the motion speed, acceleration and vehicle distance change conditions of the front vehicle in a video by means of a video identification method;
step S4: establishing a driving intention prediction model in four states of acceleration, deceleration, uniform speed and stillness of a front vehicle;
step S5: and (3) integrating the driving intention prediction result into a forward collision early warning algorithm, comparing forward collision early warning TTC indexes considering the driving intention prediction result, optimizing the forward collision early warning algorithm, and finishing forward collision early warning.
The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein the driving intention of the preceding vehicle is collected by a vehicle-mounted camera.
The forward collision warning algorithm considering the preceding vehicle driving intention prediction as claimed in claim 1, wherein the process of the preceding vehicle driving intention prediction comprises:
step S31: calculating a correlation model corresponding to the change of the corresponding driving state of the vehicle under each type of driving state of the front vehicle, wherein the driving state of the vehicle comprises the change of the distance between the vehicles and the change of the speed of the vehicle;
step S32: and establishing a driving intention prediction model under four states of acceleration, deceleration, constant speed and static of the front vehicle by using the hidden Markov model. The state variables in the model are the driving states of the front vehicles, and the observation variables comprise the distance change (distance is increased, distance is unchanged and distance is reduced) and the driving states of the self vehicles (emergency braking, deceleration and no braking);
step S33: and calculating by adopting a test set to obtain a state transition probability matrix A, an observation probability matrix B and an initial state probability vector in the driving intention prediction model.
Step S34: and predicting the driving intention state by adopting a Viterbi algorithm, wherein the result of obtaining the optimal path is the predicted driving intention of the front vehicle. And (4) bringing the driving intention result into a forward collision early warning algorithm to finish the forward collision early warning algorithm.
Compared with the prior art, the invention has the following advantages:
(1) compared with the existing forward collision early warning algorithm, the method has simpler calculation steps, consumes less time and has low requirement on hardware.
(2) The method is a universal algorithm, does not need special instruments or customized hardware, detects and detects the driving intention of the front vehicle through a simple video sensor comprising a mobile phone camera and in combination with the traffic engineering theory, and has practical significance for the subsequent formation of a perfect forward collision early warning system and the like.
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FIG. 1 is a flow chart of the present invention;
fig. 2 is vehicle forward video selection.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Examples
The embodiment provides a forward collision early warning algorithm considering the prediction of the driving intention of a front vehicle, and as shown in fig. 1, a forward camera is used for recording a driving video of the front vehicle, so that the collision risks of different degrees are early warned in a grading manner, and rear-end collision traffic accidents are reduced. The method comprises the following steps:
step S1: acquiring a front vehicle motion video acquired by a camera in front of a vehicle;
step S2: analyzing common risk scenes and vehicle running characteristics in a forward collision scene;
step S3: determining a front vehicle through target detection, and detecting the motion speed, acceleration and vehicle distance change conditions of the front vehicle in a video by means of a video identification method;
step S4: establishing a driving intention prediction model in four states of acceleration, deceleration, uniform speed and stillness of a front vehicle;
step S5: and (3) integrating the driving intention prediction result into a forward collision early warning algorithm, comparing forward collision early warning TTC indexes considering the driving intention prediction result, optimizing the forward collision early warning algorithm, and finishing forward collision early warning.
The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein the driving intention of the preceding vehicle is collected by a vehicle-mounted camera.
The forward collision warning algorithm considering the preceding vehicle driving intention prediction as claimed in claim 1, wherein the process of the preceding vehicle driving intention prediction comprises:
step S31: calculating a correlation model corresponding to the change of the corresponding driving state of the vehicle under each type of driving state of the front vehicle, wherein the driving state of the vehicle comprises the change of the distance between the vehicles and the change of the speed of the vehicle;
step S32: and establishing a driving intention prediction model under four states of acceleration, deceleration, constant speed and static of the front vehicle by using the hidden Markov model. The state variables in the model are the driving states of the front vehicles, and the observation variables comprise the distance change (distance is increased, distance is unchanged and distance is reduced) and the driving states of the self vehicles (emergency braking, deceleration and no braking);
step S33: and calculating by adopting a test set to obtain a state transition probability matrix A, an observation probability matrix B and an initial state probability vector in the driving intention prediction model.
Step S34: and predicting the driving intention state by adopting a Viterbi algorithm, wherein the result of obtaining the optimal path is the predicted driving intention of the front vehicle. And (4) bringing the driving intention result into a forward collision early warning algorithm to finish the forward collision early warning algorithm.
Claims (10)
1. A forward collision warning algorithm taking into account a prediction of driving intent of a preceding vehicle, the method comprising the steps of:
step S1: acquiring a front vehicle motion video acquired by a camera in front of a vehicle;
step S2: analyzing common risk scenes and vehicle running characteristics in a forward collision scene;
step S3: determining a front vehicle through target detection, and detecting the motion speed, acceleration and vehicle distance change conditions of the front vehicle in a video by means of a video identification method;
step S4: establishing a driving intention prediction model in four states of acceleration, deceleration, uniform speed and stillness of a front vehicle;
step S5: and (3) integrating the driving intention prediction result into a forward collision early warning algorithm, comparing forward collision early warning TTC indexes considering the driving intention prediction result, optimizing the forward collision early warning algorithm, and finishing forward collision early warning.
2. The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein the driving intention of the preceding vehicle is collected by a vehicle-mounted camera.
3. The forward collision warning algorithm considering the preceding vehicle driving intention prediction as claimed in claim 1, wherein the process of the preceding vehicle driving intention prediction comprises:
step S31: calculating a correlation model corresponding to the change of the corresponding driving state of the vehicle under each type of driving state of the front vehicle, wherein the driving state of the vehicle comprises the change of the distance between the vehicles and the change of the speed of the vehicle;
step S32: and establishing a driving intention prediction model under four states of acceleration, deceleration, constant speed and static of the front vehicle by using the hidden Markov model. The state variables in the model are the driving states of the front vehicles, and the observation variables comprise the distance change (distance is increased, distance is unchanged and distance is reduced) and the driving states of the self vehicles (emergency braking, deceleration and no braking);
step S33: and calculating by adopting a test set to obtain a state transition probability matrix A, an observation probability matrix B and an initial state probability vector in the driving intention prediction model.
Step S34: and predicting the driving intention state by adopting a Viterbi algorithm, wherein the result of obtaining the optimal path is the predicted driving intention of the front vehicle. And (4) bringing the driving intention result into a forward collision early warning algorithm to finish the forward collision early warning algorithm.
4. The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein the prediction model of the driving intention of the preceding vehicle comprises three elements:
π＝[0.139 0.196 0.377 0.288]T
5. the forward collision warning algorithm considering the preceding vehicle driving intention prediction as claimed in claim 1, wherein the frequency of the preceding vehicle driving intention prediction is 10Hz, and the driving intention of the next 1s is predicted according to the driving state of the preceding vehicle of the first 5s and the driving state of the vehicle.
6. The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein the driving intention of the preceding vehicle is divided into four driving intentions of acceleration, deceleration, uniform speed and standstill.
7. The forward collision warning algorithm according to claim 1, wherein the observed variables include distance increase, distance decrease, and distance invariance, and the vehicle is braked suddenly, decelerated, and not braked, totaling 9 observed variables.
8. The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein a hidden markov model is used to build a correlation model between the driving load of the preceding vehicle and the driving state of the own vehicle.
9. The forward collision warning algorithm considering the prediction of the driving intention of the leading vehicle as claimed in claim 1, wherein the optimal path prediction of the driving intention is performed by using a viterbi algorithm.
10. The forward collision warning algorithm considering the prediction of the driving intention of the preceding vehicle as claimed in claim 1, wherein the headway is more than 3s, no warning is given, the headway is less than 1s, the primary warning is given, the headway is less than 0.6s, and the constant sound warning is given.
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| CN114093187A (en) * | 2021-11-26 | 2022-02-25 | 交通运输部公路科学研究所 | Risk early warning control method for automatic driving vehicle and intelligent network system |
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