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Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation
Joint Authors
Hu, Hongyu
Su, Wei
Shen, Chuanliang
Zhang, Shan
Gao, Zhenhai
Zhou, Binyu
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-01
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Shen, Chuanliang& Zhang, Shan& Gao, Zhenhai& Zhou, Binyu& Su, Wei& Hu, Hongyu. 2020. Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1181095
Modern Language Association (MLA)
Shen, Chuanliang…[et al.]. Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation. Journal of Advanced Transportation No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1181095
American Medical Association (AMA)
Shen, Chuanliang& Zhang, Shan& Gao, Zhenhai& Zhou, Binyu& Su, Wei& Hu, Hongyu. Study on a Right-Turning Intelligent Vehicle Collision Warning and Avoidance Algorithm Based on Monte Carlo Simulation. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1181095
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181095