DocumentCode :
2750882
Title :
Prediction of unintended lane departure based on detection of lane boundary
Author :
Chen, Qingyang ; Sun, Zhenping ; Chen, Tongtong ; Cao, Liu
Author_Institution :
Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2011
fDate :
10-12 July 2011
Firstpage :
65
Lastpage :
70
Abstract :
To address the unintended lane departure problem in nowadays´ vehicle safety, a novel method is proposed in this paper, to predict the tendency of lane departure. The method doesn´t need a lane model to describe the center line of the lane, but just the detected lane boundary points, so can overcome the influence of lane recognition problem and reduce the effect of lane model error, which is very difficult to resolve up to now. Another aspect, as the prediction of the future trajectory is based on a defined steering angle zone, but without the measured steering angle, so the novel method can conquer the disturbance of the measure error of the steering angle, especially at high speed situation. Real vehicle experiments based on the method are carried out on the prototype HONGQI Autonomous Land Vehicle on highway. Results show that the method can provide a stable and accurate alarm, when the vehicle is going to be departure from the lane.
Keywords :
object detection; object recognition; road safety; road vehicles; traffic engineering computing; HONGQI autonomous land vehicle; defined steering angle zone; lane boundary detection; lane model error effect reduction; lane recognition problem; unintended lane departure prediction; Accidents; Predictive models; Roads; Safety; Trajectory; Vehicle dynamics; Vehicles; detected lane boundary points; lane model error; measure error; unintended lane departure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Electronics and Safety (ICVES), 2011 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-0576-2
Type :
conf
DOI :
10.1109/ICVES.2011.5983748
Filename :
5983748
Link To Document :
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