首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到10条相似文献,搜索用时 156 毫秒
1.
OBJECTIVE: The present study developed and tested a model of car following by human drivers. BACKGROUND: Previous models of car following are based on 3-D parameters such as lead vehicle speed and distance information, which are not directly available to a driver. In the present paper we present the driving by visual angle (DVA) model, which is based on the visual information (visual angle and rate of change of visual angle) available to the driver. METHOD: Two experiments in a driving simulator examined car-following performance in response to speed variations of a lead vehicle defined by a sum of sine wave oscillations and ramp acceleration functions. In addition, the model was applied to six driving events using real world-driving data. RESULTS: The model provided a good fit to car-following performance in the driving simulation studies as well as in real-world driving performance. A comparison with the advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN) model, which is based on 3-D parameters, suggests that the DVA was more predictive of driver behavior in matching lead vehicle speed and distance headway. CONCLUSION: Car-following behavior can be modeled using only visual information to the driver and can produce performance more predictive of driver performance than models based on 3-D (speed or distance) information. APPLICATION: The DVA model has applications to several traffic safety issues, including automated driving systems and traffic flow models.  相似文献   

2.
建立虚拟交通环境的多智能体结构,分析车辆智能体的驾驶行为分层模型以及感知、决策和操作等过程。采用模糊专家系统建立车辆智能体的驾驶行为模型。为模拟现实中的驾驶员行为特性,加入驾驶员因子,使驾驶模拟器的虚拟交通环境更符合现实。运用OpenGVS产生和显示实时交互的虚拟驾驶场景。结果表明该模型能体现实际驾驶行为的多样性、随机性和模糊性。该模型通用有效,它使驾驶模拟器的虚拟交通场景更真实满意。  相似文献   

3.
《Ergonomics》2012,55(6):447-462
A sequence of driving tasks has been carried out in a driving simulator. The initial tests represented lane tracking along a serpentine roadway and were employed to verify the operation of the simulator and the ability of a computer algorithm to fit linear driver models to experimental data. A second series of tests involved an obstacle avoidance manoeuvre in both a car and a truck. These latter simulator runs were augmented by field trials in an automobile during which driver eye point-of-regard data were recorded. Eye point-of-regard results from both simulator and field trials were compared and employed in formulating a simple driver model for the obstacle avoidance manoeuvre. The results from a preliminary fitting of this model to the experimental data are reported. It was found that a single linear model of the driver's dynamic characteristics can be used to represent adequately all of the driver response data measured in the present study.  相似文献   

4.
随着公交车和出租车的数量不断增加,司机在开车时的不规范驾驶动作造成很多交通事故。为了有效降低这种交通事故发生的可能性,设计了一个基于深度学习的不规范驾驶行为智能识别系统。本系统将摄像头安装在车内并实时采集司机驾驶状态的图像,控制器与后台电脑服务器远程连接,服务器通过网络通信接收司机图像并通过深度学习对采集的司机图像进行识别并处理,再把处理的结果传给控制器。这样司机在开车时发生喝水、打电话、玩手机等7种危险动作行为时,就可以通过控制器及时对司机进行智能安全语音提示,后台也可以实时监督和警示司机。  相似文献   

5.
利用机器视觉对驾驶人面部器官状态进行监测和分析处理是安全辅助驾驶领域内的研究热点之一。首先介绍了驾驶人驾驶行为监测及预警系统的原理和结构,然后讨论了系统中驾驶人眼睛定位的技术要点。通过人类眼睛虹膜对不同波长的红外光吸收能力的不同,利用特制的红外光源获取到驾驶人面部的两种红外反射图像,利用图像处理算法进行处理从而获得驾驶人的眼睛位置,从而为下一步的眼睛状态及信息提取打下了良好的基础。实践证明,算法的实时性高,效果非常理想。  相似文献   

6.
This paper deals with a driving simulator with a multibody vehicle model. Driving simulators require a real-time calculation of vehicle dynamics in response to driver’s inputs, such as a steering maneuver or a brake pedal operation. The authors realized a real-time calculation with a multibody vehicle model by approximating the calculation of constraint equations, and developed a driving simulator with 6-axes motion system. Drivers can feel the multibody analysis results through body sensory information such as the acceleration produced by the motion system and the visual information generated by computer graphics with the developed MBS simulator system. In this paper, a closed-loop test of a human-automobile system was investigated with the developed MBS driving simulator. In this evaluation, the driving simulator system and driver’s behavior were included in a multibody dynamics analysis, so it consists of a hardware- and human-in-the-loop simulation. It was observed from test results that the driving behavior was changed according to the parameters of the multibody vehicle model.  相似文献   

7.
针对目前汽车造型设计过程中A立柱视野评估缺乏从设计师视角主动参与的使能工具,提出基于增强现实技术的汽车A立柱评估方法.首先建立了汽车内饰评估的增强现实软硬件环境,将虚拟汽车模型准确、实时地叠加到真实的驾驶环境中;其次建立了虚拟视锥体几何模型,设计了用户左右眼视锥的标定方法以及基于视线碰撞检测的A柱盲区角计算方法,并分析了标定误差对盲区角计算精度的影响,结果表明标定方法可靠.最后采用某型轿车模型进行应用验证,通过跟踪用户人眼位置驱动虚拟视锥体,实现不同驾姿下的A立柱盲区角的快速计算,主观地评估A立柱对前方视野的影响.结果表明,该方法操作简单有效,为汽车视野A立柱评估提供了一个新型工具.  相似文献   

8.
针对远光灯交汇会影响汽车驾驶员的视觉注意力,导致汽车驾驶员夜间行驶安全难以得到保障的问题,研究基于机器视觉及深度学习的ADB汽车大灯的外界环境检测方法。 通过机器视觉的CCD相机采集ADB汽车大灯外界环境图像数据,利用数据筛选方法剔除采集到的图像数据中干扰光源数据,依据路况特征差异,划定ADB汽车大灯外界环境检测目标区域后,通过深度学习算法检测外界环境目标车灯光源,结合扩展卡尔曼预测各目标车灯光源轨迹,当车辆前方有车灯光源经过时,ADB系统及时调整汽车远光灯对应区域灯珠亮度,减少在高速行驶时因远光灯交汇对汽车驾驶员的视觉影响,保障汽车安全行驶。实验结果表明,该方法可有效剔除各类干扰光源,准确检测目标车灯光源,且目标车灯光源轨迹预测结果与真实结果非常接近,可精准完成ADB汽车大灯的外界环境检测。  相似文献   

9.
The study of human behavior during driving is of primary importance for improving the driver??s security. In this study, we propose a hierarchical driver_vehicle_environment fuzzy system to analyze driver??s behavior under stress conditions on a road. We include climate, road and car conditions in fuzzy modeling. For obtaining fuzzy rules, experts?? opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. The number of fuzzy rules is optimized by Particle Swarm Optimization (PSO) algorithm. Also the frequency of pressing on brake and gas pedals and the number of car??s direction changes are used to determine the driver??s behavior under different conditions. Three different positions are considered for driving and decision making; one position in driving lane and two positions in opposite lane. A fuzzy model called Model 1 is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. The behaviors of different drivers under two stress conditions are investigated. Also we obtained two other models based on fuzzy rules called Model 2 and Model 3 by using Sugeno fuzzy inference. Model 2 has two linguistic terms and Model 3 has four linguistic terms for estimating the time distances with other cars. The results of three models are compared. The comparative studies have shown that simulation results are in good agreement with the real world situations.  相似文献   

10.
ABSTRACT

This article presents a qualitative driving simulator study designed to understand the experience of giving up control to automated processes in semiautonomous driving systems. The study employed an experience prototyping methodology, with 12 drivers (4 female) completing 2 sessions in a high-fidelity driving simulator. Condition A simulated a normally functioning car, while Condition B simulated a semiautonomous system that monitors driver behavior and takes evasive action when danger is detected. The simulator experience was used to ground wider discussion of automation and the experience of driving, which was explored through a semistructured interview. Results identify design challenges for autonomous driving systems; the loss of user agency and confidence, and handling the change between manual and automated control. Opportunities were identified; in augmenting rather than removing human abilities, and in providing new learning opportunities for drivers.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号