CAREER: Collision Prediction and Vehicular Control Using an Episode-Based Modeling Framework

教师早期职业发展（CAREER）计划奖的目的是探索预测高速公路车辆碰撞的机制，并指定碰撞前和碰撞后的机动，以提高交通流动性和安全性。本研究利用经济学、心理学、工程学等领域的概念，来说明交通系统评估的绩效指标。为了实现研究目标，加速和变道驾驶行为导致高速公路车-车碰撞将被建模。将采用基于随机情节的框架，其中驾驶体验由一系列情节表示。在每个情节中，驾驶员加速/减速以最大化他/她的偏好，这由主观效用函数表示。该函数捕获危险行为和碰撞。一旦发生碰撞，将使用另一个表示车辆动力学的函数来捕获车辆碰撞后的运动。将驾驶员的偏好沿着与车辆动力学相结合的最终模型将使用通过仪表车辆、3D驾驶模拟器和虚拟实验室环境收集的数据进行实时校准。将开发一种模拟工具来测试不同的碰撞前和碰撞后机动，这些机动可能会导致更安全和更有效的高速公路交通网络。如果成功，这项研究将有助于开发不同的被动和主动驾驶辅助系统。这些系统的目标是提高驾驶员的响应能力，并提供更安全的驾驶环境，特别是为年轻驾驶员提供更安全的驾驶环境。因此，大华盛顿都会区的高中生和大学生将参与数据收集和教育活动。将举办交通安全讲习班。这些讲习班将利用虚拟互动三维环境，同时与包括国家儿童博物馆在内的地方机构合作。

The objective of the Faculty Early Career Development (CAREER) program award is to explore mechanisms for predicting freeway vehicle-to-vehicle collisions and specifying the pre and post-collision maneuvers to improve traffic mobility and safety. This research utilizes concepts from the fields of economics, psychology, and engineering to specify performance measures for traffic system evaluation. In order to realize the research objective, the acceleration and lane-changing driving behaviors that lead to freeway vehicle-to-vehicle collisions will be modeled. A stochastic episode-based framework will be adopted where the driving experience is represented by a series of episodes. Within each episode, a driver accelerates/decelerates in order to maximize his/her preferences and this is represented by a subjective utility function. This function captures risky behavior and collisions. Once collisions occur, another function representing vehicle dynamics will be used to capture the vehicular post-collision movements. The resulting model that integrates the driver's preferences along with vehicle dynamics will be calibrated in real-time using data collected through an instrumented vehicle, a 3-D driving simulator, and a virtual laboratory environment. A simulation tool will be developed to test different pre and post-collision maneuvers that potentially lead to safer and more efficient freeway traffic networks.If successful, the research will help in the development of different passive and active driving assistance systems. The objective of these systems will be to increase driver's responsiveness and to provide a safer driving environment especially for younger drivers. For this reason, high-school and university students in the Greater Washington Metropolitan Area will be involved in the data-collection and educational activities. Traffic safety workshops will be organized. A virtual interactive 3-D environment will be utilized in these workshops while collaborating with local agencies including the National Children's Museum.