Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation

With the development of intelligent vehicle technology, the demand for advanced driver assistant systems kept increasing. To improve the performance of the active safety systems, we focused on right-turning vehicle’s collision warning and avoidance. We put forward an algorithm based on Monte Carlo s...

Full description

Bibliographic Details
Main Authors: Chuanliang Shen, Shan Zhang, Zhenhai Gao, Binyu Zhou, Wei Su, Hongyu Hu
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2020/9405760
id doaj-c85e6b26e0924016892351efd6b8cf34
record_format Article
spelling doaj-c85e6b26e0924016892351efd6b8cf342020-11-25T03:07:54ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/94057609405760Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo SimulationChuanliang Shen0Shan Zhang1Zhenhai Gao2Binyu Zhou3Wei Su4Hongyu Hu5State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaWith the development of intelligent vehicle technology, the demand for advanced driver assistant systems kept increasing. To improve the performance of the active safety systems, we focused on right-turning vehicle’s collision warning and avoidance. We put forward an algorithm based on Monte Carlo simulation to calculate the collision probability between the right-turning vehicle and another vehicle (or pedestrian) in intersections. We drew collision probability curves which used time-to-collision as the horizontal axis and collision probability as the vertical axis. We established a three-level collision warning system and used software to calculate and simulate the collision probability and warning process. To avoid the collision actively when turning right, a two-stage braking strategy is applied. Taking four right-turning collision conditions as examples, the two-stage braking strategy was applied, analysing and comparing the anteroposterior curve diagram simultaneously to avoid collision actively and reduce collision probability. By comparison, the collision probability 2 s before active collision avoidance was more than 80% and the collision probability may even reach 100% in certain conditions. To improve the active safety performance, the two-stage braking strategy can reduce the collision probability from exceeding 50% to approaching 0% in 2 s and reduce collision probability to less than 5% in 3 s. By changing four initial positions, the collision probability curve calculation algorithm and the two-stage braking strategy are validated and analysed. The results verified the rationality of the collision probability curve calculation algorithm and the two-stage braking strategy.http://dx.doi.org/10.1155/2020/9405760
collection DOAJ
language English
format Article
sources DOAJ
author Chuanliang Shen
Shan Zhang
Zhenhai Gao
Binyu Zhou
Wei Su
Hongyu Hu
spellingShingle Chuanliang Shen
Shan Zhang
Zhenhai Gao
Binyu Zhou
Wei Su
Hongyu Hu
Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
Journal of Advanced Transportation
author_facet Chuanliang Shen
Shan Zhang
Zhenhai Gao
Binyu Zhou
Wei Su
Hongyu Hu
author_sort Chuanliang Shen
title Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
title_short Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
title_full Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
title_fullStr Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
title_full_unstemmed Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
title_sort study on a right-turning intelligent vehicle collision warning and avoidance algorithm based on monte carlo simulation
publisher Hindawi-Wiley
series Journal of Advanced Transportation
issn 0197-6729
2042-3195
publishDate 2020-01-01
description With the development of intelligent vehicle technology, the demand for advanced driver assistant systems kept increasing. To improve the performance of the active safety systems, we focused on right-turning vehicle’s collision warning and avoidance. We put forward an algorithm based on Monte Carlo simulation to calculate the collision probability between the right-turning vehicle and another vehicle (or pedestrian) in intersections. We drew collision probability curves which used time-to-collision as the horizontal axis and collision probability as the vertical axis. We established a three-level collision warning system and used software to calculate and simulate the collision probability and warning process. To avoid the collision actively when turning right, a two-stage braking strategy is applied. Taking four right-turning collision conditions as examples, the two-stage braking strategy was applied, analysing and comparing the anteroposterior curve diagram simultaneously to avoid collision actively and reduce collision probability. By comparison, the collision probability 2 s before active collision avoidance was more than 80% and the collision probability may even reach 100% in certain conditions. To improve the active safety performance, the two-stage braking strategy can reduce the collision probability from exceeding 50% to approaching 0% in 2 s and reduce collision probability to less than 5% in 3 s. By changing four initial positions, the collision probability curve calculation algorithm and the two-stage braking strategy are validated and analysed. The results verified the rationality of the collision probability curve calculation algorithm and the two-stage braking strategy.
url http://dx.doi.org/10.1155/2020/9405760
work_keys_str_mv AT chuanliangshen studyonarightturningintelligentvehiclecollisionwarningandavoidancealgorithmbasedonmontecarlosimulation
AT shanzhang studyonarightturningintelligentvehiclecollisionwarningandavoidancealgorithmbasedonmontecarlosimulation
AT zhenhaigao studyonarightturningintelligentvehiclecollisionwarningandavoidancealgorithmbasedonmontecarlosimulation
AT binyuzhou studyonarightturningintelligentvehiclecollisionwarningandavoidancealgorithmbasedonmontecarlosimulation
AT weisu studyonarightturningintelligentvehiclecollisionwarningandavoidancealgorithmbasedonmontecarlosimulation
AT hongyuhu studyonarightturningintelligentvehiclecollisionwarningandavoidancealgorithmbasedonmontecarlosimulation
_version_ 1715298236830318592