An optimal hierarchical framework of the trajectory following by convex optimisation for highly automated driving vehicles

被引:40
作者
Cao, Haotian [1 ,2 ]
Zhao, Song [3 ]
Song, Xiaolin [1 ]
Bao, Shan [2 ]
Li, Mingjun [1 ]
Huang, Zhi [1 ]
Hu, Chuan [4 ]
机构
[1] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China
[2] Univ Michigan, Transportat Res Inst, Human Factors Grp, Ann Arbor, MI 48109 USA
[3] Optimal CAE Inc, Plymouth, MI USA
[4] Univ Texas Austin, Dept Mech Engn, Austin, TX 78712 USA
基金
美国国家科学基金会;
关键词
Trajectory planning; convex optimisation; linearised MPC; nonlinear vehicle dynamics; automated driving; OPTIMAL PREVIEW CONTROL; POTENTIAL APPLICATION; LONGITUDINAL CONTROL; MATHEMATICAL-MODEL; STEERING CONTROL; AVOIDANCE; STRATEGY; SIMULATION; DESIGN;
D O I
10.1080/00423114.2018.1497185
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper presents a hierarchical trajectory following framework for SAE-level 2/3 automatic driving by convex optimisation, which aims for daily common driving manoeuvres with low traffics on the highway, such as free driving, adaptively following and overtaking. More specifically, it includes several combined functionalities of lane keeping, adaptive following, active obstacle avoidance and speed adaptation. The trajectory-planning module would generate the optimal path and speed profiles for the structure road (e.g. highway) with different geometric shapes, by using the natural cubic spline and convex optimisation approach. While modules of trajectory following or adaptive following are realised by a linearised time-varying model predictive control method. It is expected that the proposed framework could improve the driving safety, as well as the driving efficiency and driving comforts simultaneously. Thus, typical scenarios are designed to verify the effectiveness of the proposed trajectory following framework. Simulation results demonstrate that it could successfully deal with daily manoeuvres on a straight or curved highway without human driver's interventions.
引用
收藏
页码:1287 / 1317
页数:31
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