自动驾驶车辆中驾驶人的信息需求特征
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摘要
根据中国城市道路的特点,选取6种典型的城市道路场景进行实验,研究不同驾驶场景下自动驾驶车辆驾驶人的信息需求。在参试者实施任务的过程中,使用眼动仪记录其眼球注视点和注视时间,并采用因子分析方法对数据进行分析。结果表明:1)无论驾驶人的注意力是否在监控驾驶任务上,一些重要的信息都必不可少,例如当前行驶速度、制动距离等车辆自身信息,周围路况、车况等汽车周围环境信息,以及辅助系统处理当前场景的能力等辅助系统相关信息;2)紧急危险场景中,驾驶人更需要周围车辆行驶速度、与两侧车辆距离以及车头时距等信息,以便采取换道、制动等措施;3)在行驶缓慢的拥堵场景中,驾驶人更需要道路相关信息,例如交通标志、车道条数等。
According to the characteristics of urban roads in china, this paper selects 6 representative urban road scenarios to study the drivers' information demand when driving autonomous vehicles. The eye fixation area and fixation time are recorded by the eye tracker while participants are on-going the tasks. Then the factor analysis method is used to explore the data, the results show that: 1) Whether the driver's attention is on the driving task or not, the information, including vehicle information(e.g. travel speed, braking distance of vehicle), environmental information(e.g. the road condition, car condition around driver) and autonomous driving system related information(the ability of handling the risky condition) are essential;2) In the scenario of emergency, the information(e.g. travel speed, the distance with other vehicles) are necessary to support drivers to make a decision about braking and changing the lane; 3) In the congestion scenario in which cars move slowly, drivers need more road information(e.g. traffic signs, number of lanes).
According to the characteristics of urban roads in china, this paper selects 6 representative urban road scenarios to study the drivers' information demand when driving autonomous vehicles. The eye fixation area and fixation time are recorded by the eye tracker while participants are on-going the tasks. Then the factor analysis method is used to explore the data, the results show that: 1) Whether the driver's attention is on the driving task or not, the information, including vehicle information(e.g. travel speed, braking distance of vehicle), environmental information(e.g. the road condition, car condition around driver) and autonomous driving system related information(the ability of handling the risky condition) are essential;2) In the scenario of emergency, the information(e.g. travel speed, the distance with other vehicles) are necessary to support drivers to make a decision about braking and changing the lane; 3) In the congestion scenario in which cars move slowly, drivers need more road information(e.g. traffic signs, number of lanes).
引文
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[15]张生,车丽彬,黄俊.对中国大城市交通拥堵问题的认识[J].科技展望,2016(25):309.
[16]吴付威,王畅,马勇,等.城市道路应激交通事件分析[J].公路与汽运,2016(6):41-44+186.
[17]王颖.基于人机交互仿真的驾驶次任务研究[D].北京:清华大学,2009.
[18]Wickens C D,Hollands J G,Banbury S,et al.Engineering Psychology and Human Performance[M].Boston:Pearson Education,2013.
[19]Jamson A H,Merat N,Carsten O MJ,et al.,Behavioural Changes in Drivers Experiencing Highly-Automated Vehicle Control in Varying Traffic Conditions[J].Transportation Research Part C:Emerging Technologies,2013(30):116-125.
[2]National Highway Traffic Safety Administration.Preliminary Statement of Policy Concerning Automated Vehicles[S].Washington DC:National Highway Traffic Safety Administration,2013.
[3]冀杰,李以农,郑玲,等.车辆自动驾驶系统纵向和横向运动综合控制[J].中国公路学报,2010,23(5):119-126.Ji Jie,Li Yinong,Zheng Ling,et al.Integrated Control of Longitudinal and Lateral Motion for Autonomous Vehicle Driving System[J].China Journal of Highway and Transport,2010,23(5):119-126.
[4]郭俊杰.无人驾驶车GPS自主导航系统设计与实现[D].西安:长安大学,2014.
[5]Zeeb K,Buchner A,Schrauf M.Is Take-Over Time All That Matters?The Impact of VisualCognitive Load on Driver Take-Over Quality after Conditionally Automated Driving[J],Accident Analysis&Prevention,2016,92:230-239.
[6]K?rber M,Gold C,Lechner D,et al.The Influence of Age on the Take-Over of Vehicle Control in Highly Automated Driving[J].Transportation Research Part F:Traffic Psychology and Behavior,2016,39:19-32.
[7]Banks V A,Stanton N A.Keep the Driver in Control:Automating Automobiles of the Future[J].Applied Ergonomics,2015,53:389-395.
[8]Merat N,Lee J D.Preface to the Special Section on Human Factors and Automation in Vehicles Designing Highly Automated Vehicles with the Driver in Mind[J].Human Factors:The Journal of the Human Factors and Ergonomics Society,2012,54(5):681-686.
[9]Kazi T,Stanton N A,Walker G H,et al.Designer Driving:Drivers'Conceptual Models and Level of Trust in Adaptive Cruise Control[J].International Journal of Vehicle Design,2007,45(3):339-360.
[10]Martens P,Schieben F,Merat J,et al.Human Factors'Aspects in Automated and Semiautomatic Transport Systems:State of the Art[R].European Commission,City Mobil Deliverable,2008.
[11]Jamson A H,Merat N,Carsten O M J,et al.Behavioural Changes in Drivers Experiencing Highly-Automated Vehicle Control in Varying Traffic Conditions[J].Transportation Research Part C:Emerging Technologies,2013,30:116-125.
[12]Beggiato M,Hartwich F,Schleinitz K,et al.What Would Drivers Like to Know During Automated Driving?Information Needs at Different Levels of Automation[C]//7th Conference on Driver Assistance,Munich,November 25-26,2015.
[13]Martin G,Bi?bort F,Petermann-Stock I,et al.“A Careful Driver Is One Who Looks in Both Directions When He Passes a Red Light”:Increased Demands in Urban Traffic[C].//Hutchison D,Kanade T,Kittler J,et al.Human Interface and the Management of Information.Information and Knowledge in Applications and Services.Berlin:Springer,2014:229-240.
[14]Martin G,Bengler K.Urban Driving:Where to Present What Types of InformationComparison of Head-Down and Head-Up Displays[C]//Yamamoto S,Human Interface and the Management of Information.Information and Knowledge Design.Swizeland:Springer International Publishing,2015:247-257.
[15]张生,车丽彬,黄俊.对中国大城市交通拥堵问题的认识[J].科技展望,2016(25):309.
[16]吴付威,王畅,马勇,等.城市道路应激交通事件分析[J].公路与汽运,2016(6):41-44+186.
[17]王颖.基于人机交互仿真的驾驶次任务研究[D].北京:清华大学,2009.
[18]Wickens C D,Hollands J G,Banbury S,et al.Engineering Psychology and Human Performance[M].Boston:Pearson Education,2013.
[19]Jamson A H,Merat N,Carsten O MJ,et al.,Behavioural Changes in Drivers Experiencing Highly-Automated Vehicle Control in Varying Traffic Conditions[J].Transportation Research Part C:Emerging Technologies,2013(30):116-125.