模拟赛车手在复杂赛道上的轨迹/速度决策行为
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- 英文论文题名：Modeling Racing Driver's Target “Trajectory–Speed” Decision Making for Automated Driving on Complex Circuits
- 论文作者：徐进 ; 束海波 ; 邵毅明
- 英文论文作者：Xu Jin ; Shu Haibo ; Shao Yiming ; College of Traffic and Transportation ; Chongqing Jiaotong University ; Chongqing Key Laboratory of Transportation Engineering ; School of Mechanotronics & Vehicle Engineering ; Chongqing Jiaotong University
- 年：2016
- 作者机构：重庆交通大学交通运输学院;交通运输工程重庆市重点实验室;重庆交通大学机电与车辆工程学院;
- 论文关键词：无人驾驶 ; 赛道 ; 赛车手 ; 轨迹决策 ; 速度决策 ; 目标轨迹 ; 目标速度 ; 驾驶仿真
- 英文论文关键词：Automated Driving ; Circuit ; Race Driver ; Trajectory Decision Making ; Speed Decision Making ; Target Trajectory ; Target Speed ; Driving Simulation
- 会议召开时间：2016-11-16
- 会议录名称：第十一届中国智能交通年会大会论文集
- 语种：中文
- 分类号：U491.25
- 学会代码：ZJTX
- 会议名称：第十一届中国智能交通年会
- 会议地点：中国重庆
- 主办单位：中国智能交通协会
- 学会名称：中国智能交通协会
- 页数：9
- 文件大小：1245k
- 原文格式：D
- 会议级别：全国
摘要
轨迹/速度是汽车驾驶行为的重要环节,但现有模型的研究对象几乎都是针对城市道路和一般公路,无法适用于具有特殊性的赛道驾驶行为模拟。为此,本文根据真实世界的汽车驾驶过程和特点,提出了"前视断面选点"的轨迹计算策略,然后在其基础上构建了能够描述赛车手轨迹—速度选择模式的目标函数,根据赛道行驶环境和赛车性能设计了约束条件表达式,并给出了"期望轨迹—期望速度"联合求解的滚动时域算法,最后,以一条公路赛道为仿真实例对提出的模型进行检验,结果表明本文的决策模型能够得到满足预期的计算结果,并与真实赛道上的赛车轨迹和速度具有较高的符合度。
The selection of target trajectory and speed is a crucial factor in automobile driving behavior.However,almost all the research objects of existing driver models are developed for driving on city streets and general highways but not applicable to driving simulation on circuits,in particular.Therefore,according to practical automobile driving processes and characteristics in the real world,this paper proposed a trajectory calculation strategy,which we named as "selecting trajectory point on a preview cross section." According to this strategy,an objective function was established to describe the different selection patterns of "trajectory and speed" of a race driver.Constraint expressions were then designed on the basis of the circuit-driving environment and race-car performance.A rolling-horizon algorithm for simultaneous solving,i.e.," target trajectory–target speed," was proposed.Eventually,validation of the proposed model was conducted using a road track as a simulation example,and the results indicated that the anticipated computational results could be obtained using the proposed decision-making model and algorithm.The result also showed a fairly good agreement with the trajectory and speed of a race car on a practical circuit.
The selection of target trajectory and speed is a crucial factor in automobile driving behavior.However,almost all the research objects of existing driver models are developed for driving on city streets and general highways but not applicable to driving simulation on circuits,in particular.Therefore,according to practical automobile driving processes and characteristics in the real world,this paper proposed a trajectory calculation strategy,which we named as "selecting trajectory point on a preview cross section." According to this strategy,an objective function was established to describe the different selection patterns of "trajectory and speed" of a race driver.Constraint expressions were then designed on the basis of the circuit-driving environment and race-car performance.A rolling-horizon algorithm for simultaneous solving,i.e.," target trajectory–target speed," was proposed.Eventually,validation of the proposed model was conducted using a road track as a simulation example,and the results indicated that the anticipated computational results could be obtained using the proposed decision-making model and algorithm.The result also showed a fairly good agreement with the trajectory and speed of a race car on a practical circuit.
引文
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[2]Reinalter W,Tieber W.A passenger car driver model for higher lateral accelerations[J].Vehicle System Dynamics.2007,45(12):1117-1129.
[3]Mac Adam CC.Application of an optimal preview control for simulation of closed-loop automobile driving[J].IEEE Transactions on Systems,Man,and Cybernetics.1981,11(6):393-399.
[4]Guo K,Cheng Y,Ding H.Analytical method for modeling driver in vehicle directional control[J].Vehicle System Dynamics.2004,41(Sup):401-410.
[5]Guo K,Ding H,Zhang J,Lu J,Wang R.Development of a longitudinal and lateral driver model for autonomous vehicle control[J].International Journal of Vehicle Design,2004,36(1):50-65.
[6]Günther P.Modeling Human Vehicle Driving by Model Predictive Online Optimization[J].Vehicle System Dynamics.2001,35(1):19-53.
[7]Mac Adam,CC,Johnson GE.Application of elementary neural networks and preview sensors for representing driver steering control behaviour[J].Vehicle System Dynamics.1996,25(1):3-30.
[8]Manfred P,Johannes E.Driver models in automobile dynamics application[J].Vehicle System Dynamics.2007,45(7):699-741.
[9]Gao Z H,Jiang LY.Optimal Preview Trajectory Decision Model of Lane-keeping System with Driver Behavior Simulation and Artificial Potential Field[C].In Proc.IEEE Intelligent Vehicles Symposium.2009:797-801.
[10]Florent Lamiraux FB.Trajectory Deformation applied to Kinodynamic Motion Planning for a Realistic Car Model[C].In Proc.Proceedings of the 2006 IEEE International Conference on Robotics and Automation,ICRA 2006,Orlando,USA.2006:487-492.
[11]Kuwata Y,Fiore G,Frazzoli E.Real-time Motion Planning with Applications to Autonomous Urban Driving[J].IEEE transactions on control systems technology.2009,17(5):1105-1118.
[12]Lauffenburgera J,Basseta M,Coffinb F,Gissinger G.L.Driver-aid system using path-planning for lateral vehicle control[J].Control Engineering Practice.2003,11(2):217-231.
[13]Li L,Wang FY.An integrated design framework for driver/passenger-oriented trajectory planning[C].in Proc.Intelligent Transportation Systems2003Proceedings,IEEE.2003:1764-1769.
[14]Villagra J,Milanés V,Pérez J,Godoy J.Smooth path and speed planning for an automated public transport vehicle[J].Robotics and Autonomous Systems.2012,60(2):252-265.
[15]Sharp R S,Casanova D,Symonds P.A mathematical model for driver steering control,with design,tuning and performance results[J].Vehicle System Dynamics.2000,33(5):289-326.
[16]Sharp RS,Valtetsiotis V.Optimal preview car steering control[J].Vehicle System Dynamics.2001,35(Sup):101-117.