详情

Non-connected vehicle detection using connected vehicles - Phase 1 and 2

项目名称：	Non-connected vehicle detection using connected vehicles - Phase 1 and 2
摘要：	Connected vehicle (CV) technologies are entering the realm of deployment. They have the potential to help drivers make safe, reliable and informed decisions, and thereby to enhance network capacity and reduce congestion. During the transition to CV technologies, there will be mixed traffic streams of CVs and non- CVs. While most studies have analyzed the CV car-following behavior in a pure CV environment, there is the need for a comprehensive CV car-following model in general mixed flow environment. Further, to improve the efficiency and reliability of traffic operations under mixed flow environments, there is the need to observe not only CV trajectory data, but also non-CV location/trajectory. This study proposes a mixed flow CV car- following model which will generate realistic CV trajectories in a mixed flow environment. Then, a Hidden Markov Model, which is a probabilistic inference approach, is proposed to identify non-CV locations/trajectories. This methodology will be integrated with a cooperative situational awareness framework.The proposed model will be analyzed using real-world vehicle trajectory data to aid the situational awareness of CVs under low market penetration rates.
状态：	Active
资金：	Total $258,364: $119,859 Purdue CS - $138,505 CCAT
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	Center for Connected and Automated Transportation
执行机构：	Purdue University, Lyles School of Civil Engineering
主要研究人员：	Peeta, Srinivas
开始时间：	20180101
预计完成日期：	20201231
实际结束时间：	0