Safe Distance Model for Control of Vehicle Emergency Collision Avoidance

被引：0

作者：

Wang S.Z. ^{[1
]}

Xu W. ^{[1
]}

机构：

[1] Guangdong Polytechnic Normal University, Guangdong, Guangzhou

来源：

International Journal of Vehicle Structures and Systems | 2021年 / 13卷 / 05期

关键词：

Driving style; Emergency collision avoidance; Safety distance model; Visual reality vehicle simulation platform;

D O I：

10.4273/ijvss.13.5.10

中图分类号：

学科分类号：

摘要：

The vehicle needs to be able to assist the driver in realizing the control strategy of emergency collision avoidance to ensure the safety of car drivers during driving. This article introduces the basic principles of vehicle emergency collision avoidance using time to collision (TTC) and Berkeley safety distance models. In addition, the Berkeley model was improved so that it could be adjusted for different driving styles. On the simulation platform, simulation experiments were carried out on the driving conditions of the front vehicle at a standstill state, at a constant speed and at a deceleration state. The performance of three collision avoidance strategies were analysed. The results showed that the extroverted driver had the fastest response speed, followed by the moderate driver and the introverted driver; no matter what the working condition, the increase in the driving speed of the driver could reduce the distance between the vehicle and the vehicle in front when the vehicle stopped due to braking, increasing the risk of rear-end collision; no matter what the working condition, the anti-collision strategy that adopted the improved Berkeley model could effectively adapt to different driving styles, keeping a stable distance from the front vehicle when stopping due to braking and the distance between the vehicles was larger than the other two collision avoidance strategies. © 2021. MechAero Foundation for Technical Research & Education Excellence.

引用

页码：598 / 603

页数：5

共 15 条

[1]

Yang L., Zhang X., Gong J., Liu J., The Research of car-following model based on real-time maximum deceleration, Math. Probl. Engg, 6, pp. 1-9, (2015)

[2]

Zamzamzadeh M., Saifizul A.A., Ramli R., Soong M.F., Heavy vehicle multi-body dynamic simulations to estimate skidding distance, Balt. J. Road Bridge Engg, 13, 1, pp. 23-33, (2018)

[3]

Song X., Li X., Zhang W., Key parameters estimation and adaptive warning strategy for rear-end collision of vehicle, Math. Probl. Engg, 3, pp. 1-20, (2015)

[4]

Yang W., Zhang X., Lei Q., Cheng X., Research on longitudinal active collision avoidance of autonomous emergency braking pedestrian system (AEB-P), Sensors, 19, 21, (2019)

[5]

Lee H.K., Shin S.G., Kwon D.S., Design of emergency braking algorithm for pedestrian protection based on multi-sensor fusion, Int. J. Autom. Tech, 18, 6, pp. 1067-1076, (2017)

[6]

Yang W., Liu J., Zhou K., Zhang Z.W., Qu X., An automatic emergency braking model considering driver's intention recognition of the front vehicle, J. Adv. Transport, pp. 1-15, (2020)

[7]

Chen M., Zhan X., Zhang X., Pan W., Localization based autonomous vehicle rear end collision avoidance by emergency steering, IET Intell. Trans. Sy, 13, 7, pp. 1078-1087, (2019)

[8]

Bruere Y., Influence of slip on the stopping distance of a train of the “metro” type under emergency braking, Rev. Gen. Chem. Fer, 274, pp. 18-27, (2017)

[9]

Jiang L., Ji J., Ren Y., Wang H., Huang Y., Risk modeling and quantification of a platoon in mixed traffic based on the mass-spring-damper model, J. Adv. Transport, 12, pp. 1-12, (2020)

[10]

Zhang H., Han X., Li R., Qin S., Ding G., Yan K., A new conceptual design method to support rapid and effective mapping from product design specification to concept design, Int. J. Adv. Manuf. Tech, 87, 5, pp. 2375-2389, (2016)

← 1 2 →