城市道路环境下自动驾驶车辆接管绩效分析
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摘要
为了分析城市道路环境下高度自动驾驶中非驾驶相关任务和接管紧迫度对接管绩效的影响,基于驾驶模拟器设计了自动驾驶紧急接管场景并开展驾驶模拟试验,接管请求时间分别设定为3,4,5 s,非驾驶相关任务为读新闻、看视频、玩游戏,自动驾驶车速为50 km·h~(-1),试验中共招募了49名被试(男性30名,女性19名),被试的平均年龄为31.06岁(标准差为7.1岁),驾驶人在自动驾驶阶段始终执行非驾驶相关任务,听到接管请求提示后需要接管车辆的控制权,并实施紧急避让操作。研究结果表明:在紧急接管情况下,接管紧迫度对合成加速度和最小TTC有影响,而对接管时间无影响,与5 s的接管请求时间条件相比,3,4 s的接管请求时间条件下的合成加速度明显增加,而最小TTC则随接管请求时间的减少而降低;非驾驶相关任务对接管时间和最小TTC有影响,而对合成加速度无影响,与无非驾驶相关任务相比,非驾驶相关任务会显著增加接管时间和降低最小TTC;碰撞几乎都发生在3 s和4 s的接管请求时间下,5 s的接管请求时间能够基本保证接管的安全性。
To examine the effect of non-driving-related tasks(NDRTs) and the urgency of the take-over during highly automated driving in urban road environment conditions, critical take-over scenarios during automated driving were designed using a driving simulator, and an experimental study was conducted. Take-over request times were set at 3 s, 4 s, and 5 s, and NDRTs included reading news, watching videos, and playing games. The automated driving speed was 50 km·h~(-1). 49 participants(30 males, 19 females) were recruited for the experiments, and the mean age of the participants was 31.06 years(SD 7.10 years). The participants were asked to engage in NDRTs during the automated driving mode. They were then asked to take back control of the vehicle when a take-over request was given and perform avoidance maneuvers. The results show that, in critical take-over situations, the urgency of the take-over affects the resultant acceleration and minimum time to collision(TTC) but has no effect on take-over time. Moreover, compared to the take-over request time of 5 s, the resultant accelerations with the take-over request times of 3 s and 4 s are significantly higher, whereas the minimum TTC decreases with a shorter take-over request time. NDRTs have an impact on the take-over time and minimum TTC but do not influence the resultant acceleration. In addition, NDRTs can significantly increase the take-over time and decrease the minimum TTC compared to cases when no NDRTs are engaged. Crashes nearly occur when the take-over request times are 3 s and 4 s, and safety can be ensured when the take-over request time is 5 s.
To examine the effect of non-driving-related tasks(NDRTs) and the urgency of the take-over during highly automated driving in urban road environment conditions, critical take-over scenarios during automated driving were designed using a driving simulator, and an experimental study was conducted. Take-over request times were set at 3 s, 4 s, and 5 s, and NDRTs included reading news, watching videos, and playing games. The automated driving speed was 50 km·h~(-1). 49 participants(30 males, 19 females) were recruited for the experiments, and the mean age of the participants was 31.06 years(SD 7.10 years). The participants were asked to engage in NDRTs during the automated driving mode. They were then asked to take back control of the vehicle when a take-over request was given and perform avoidance maneuvers. The results show that, in critical take-over situations, the urgency of the take-over affects the resultant acceleration and minimum time to collision(TTC) but has no effect on take-over time. Moreover, compared to the take-over request time of 5 s, the resultant accelerations with the take-over request times of 3 s and 4 s are significantly higher, whereas the minimum TTC decreases with a shorter take-over request time. NDRTs have an impact on the take-over time and minimum TTC but do not influence the resultant acceleration. In addition, NDRTs can significantly increase the take-over time and decrease the minimum TTC compared to cases when no NDRTs are engaged. Crashes nearly occur when the take-over request times are 3 s and 4 s, and safety can be ensured when the take-over request time is 5 s.
引文
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[4] ZEEB K,BUCHNER A,SCHRAUF M.What Determines the Take-over Time?An Integrated Model Approach of Driver Take-over After Automated Driving [J].Accident Analysis & Prevention,2015,78:212-221.
[5] HAPPEE R,GOLD C,RADLMAYR J,et al.Take-over Performance in Evasive Manoeuvres [J].Accident Analysis & Prevention,2017,106:211.
[6] RADLMAYR J,GOLD C,LORENZ L,et al.How Traffic Situations and Secondary Tasks Affect the Take-over Quality in Highly Automated Driving [J].Proceedings of the Human Factors and Ergonomics Society Annual Meeting,2014,58 (1):2063-2067.
[7] NAUJOKS F,MAI C,NEUKUM A.The Effect of Urgency of Take-over Requests During Highly Automated Driving Under Distraction Conditions [J].Advances in Human Aspects of Transportation,2014,7:431-438.
[8] ZEEB K,BUCHNER A,SCHRAUF M.Is Take-over Time all that Matters?The Impact of Visual-cognitive Load on Driver Take-over Quality After Conditionally Automated Driving [J].Accident Analysis & Prevention,2016,92:230-239.
[9] ERIKSSON A,STANTON N A.Takeover Time in Highly Automated Vehicles:Noncritical Transitions to and from Manual Control [J].Human Factors,2017,59 (4):689-705.
[10] WANDTNER B,SCH?MIG N,SCHMIDT G.Effects of Non-driving Related Task Modalities on Takeover Performance in Highly Automated Driving [J].Human Factors,2018,60 (6):870-881.
[11] 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,2016,39:19-32.
[12] CLARK H,FENG J.Age Differences in the Takeover of Vehicle Control and Engagement in Non-driving-related Activities in Simulated Driving with Conditional Automation [J].Accident Analysis & Prevention,2016,106:468.
[13] 鲁光泉,赵鹏云,王兆杰,等.自动驾驶中视觉次任务对年轻驾驶人接管时间的影响[J].中国公路学报,2018,31(4):165-171.LU Guang-quan,ZHAO Peng-yun,WANG Zhao-jie,et al.Impact of Visual Secondary Task on Young Drivers’ Take-over Time in Automated Driving[J].China Journal of Highway and Transport,2018,31 (4):165-171.
[14] WIEDEMANN K,NAUJOKS F,W?RLE J,et al.Effect of Different Alcohol Levels on Take-over Performance in Conditionally Automated Driving [J].Accident Analysis & Prevention,2018,115:89-97.
[15] 林庆峰,成波,徐少兵,等.基于Logistic回归的危险认知模型与避撞时间模型的对比[J].中国公路学报,2012,25(6):123-128.LIN Qing-feng,CHENG Bo,XU Shao-bing,et al.Comparison of Risk Perception Model Based on Logistic Regression and Time-to-collision Model[J].China Journal of Highway and Transport,2012,25 (6):123-128.
[2] GOLD C,DAMB?CK D,LORENZ L,et al.Take over! How Long Does it Take to Get the Driver Back into the Loop?[J].Proceedings of the Human Factors and Ergonomics Society Annual Meeting,2013,57 (1):1938-1942.
[3] ITO T,TAKATA A,OOSAWA K.Time Required for Take-over from Automated to Manual Driving [J].SAE Paper 2016-01-0158.
[4] ZEEB K,BUCHNER A,SCHRAUF M.What Determines the Take-over Time?An Integrated Model Approach of Driver Take-over After Automated Driving [J].Accident Analysis & Prevention,2015,78:212-221.
[5] HAPPEE R,GOLD C,RADLMAYR J,et al.Take-over Performance in Evasive Manoeuvres [J].Accident Analysis & Prevention,2017,106:211.
[6] RADLMAYR J,GOLD C,LORENZ L,et al.How Traffic Situations and Secondary Tasks Affect the Take-over Quality in Highly Automated Driving [J].Proceedings of the Human Factors and Ergonomics Society Annual Meeting,2014,58 (1):2063-2067.
[7] NAUJOKS F,MAI C,NEUKUM A.The Effect of Urgency of Take-over Requests During Highly Automated Driving Under Distraction Conditions [J].Advances in Human Aspects of Transportation,2014,7:431-438.
[8] ZEEB K,BUCHNER A,SCHRAUF M.Is Take-over Time all that Matters?The Impact of Visual-cognitive Load on Driver Take-over Quality After Conditionally Automated Driving [J].Accident Analysis & Prevention,2016,92:230-239.
[9] ERIKSSON A,STANTON N A.Takeover Time in Highly Automated Vehicles:Noncritical Transitions to and from Manual Control [J].Human Factors,2017,59 (4):689-705.
[10] WANDTNER B,SCH?MIG N,SCHMIDT G.Effects of Non-driving Related Task Modalities on Takeover Performance in Highly Automated Driving [J].Human Factors,2018,60 (6):870-881.
[11] 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,2016,39:19-32.
[12] CLARK H,FENG J.Age Differences in the Takeover of Vehicle Control and Engagement in Non-driving-related Activities in Simulated Driving with Conditional Automation [J].Accident Analysis & Prevention,2016,106:468.
[13] 鲁光泉,赵鹏云,王兆杰,等.自动驾驶中视觉次任务对年轻驾驶人接管时间的影响[J].中国公路学报,2018,31(4):165-171.LU Guang-quan,ZHAO Peng-yun,WANG Zhao-jie,et al.Impact of Visual Secondary Task on Young Drivers’ Take-over Time in Automated Driving[J].China Journal of Highway and Transport,2018,31 (4):165-171.
[14] WIEDEMANN K,NAUJOKS F,W?RLE J,et al.Effect of Different Alcohol Levels on Take-over Performance in Conditionally Automated Driving [J].Accident Analysis & Prevention,2018,115:89-97.
[15] 林庆峰,成波,徐少兵,等.基于Logistic回归的危险认知模型与避撞时间模型的对比[J].中国公路学报,2012,25(6):123-128.LIN Qing-feng,CHENG Bo,XU Shao-bing,et al.Comparison of Risk Perception Model Based on Logistic Regression and Time-to-collision Model[J].China Journal of Highway and Transport,2012,25 (6):123-128.