Speed guidance model considering driver's operating behavior

Sun, Dihua; Gu, Lianqiang; Zhao, Min; Sen-lin, Cheng; Xie, Fei; Yang, Liangyi

doi:10.1109/ccdc.2018.8408274

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…In Xu et al 21 a synergy method is proposed for traffic signal control and speed optimization for automatic driving vehicles, which simultaneously optimizes traffic signal timing and vehicle speed trajectory, significantly improving transport efficiency and fuel economy. Considering the limited obedience 22 of drivers to trajectory planning, the problem of driver's response time delay is studied in Chen and Lazar 23 In Tang et al 24 considering the acceptance threshold, execution level and response time a trajectory planning model is proposed, establishing the relationship between vehicle fuel consumption, exhaust emission and model parameters is studied.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning for autonomous vehicle based on window-constrained Pearl model

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part D:

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Speed guidance is a significant application in driver assistance system or driverless automated system. Considering the traditional Pearl model-based trajectory planning, this paper proposes an improved method based on window constraints to enhance the rationality at intersection positions. To solve the problem, where the slopes of traditional time-distance Pearl curve at the two boundaries generate relatively low values and which is not in accordance with the actual situation, a new window constraint is used to guide the vehicle passing through the intersection at a high speed. Regarding the new window constraints, together with the maximum speed, tolerating accelerated speed constraints, and traffic signal length constraints, a multi-variable and single objective optimization improved nonlinear programing scheme is applied to obtain the most comfort trajectory of passengers for speed guidance. Simulation results show that, the proposed method presents better performance in traveling time and trajectory smoothness compared with the traditional method under different initial vehicle speeds at upstream intersections and signal offset cases.

show abstract

Section: Introductionmentioning

confidence: 99%

Trajectory planning for autonomous vehicle based on window-constrained Pearl model

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part D:

View full text Add to dashboard Cite

show abstract

Speed guidance model considering driver's operating behavior

Cited by 1 publication

References 13 publications

Trajectory planning for autonomous vehicle based on window-constrained Pearl model

Trajectory planning for autonomous vehicle based on window-constrained Pearl model

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