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Cyber-Physical Integration To Connect Vehicles For Transformed Transportation Safety And Efficiency, Daiheng Ni, Hong Liu Liu, Wei Ding, Yuanchang Xie, Honggang Wang, Hossein Pishro-Nik, Qian Yu
Cyber-Physical Integration To Connect Vehicles For Transformed Transportation Safety And Efficiency, Daiheng Ni, Hong Liu Liu, Wei Ding, Yuanchang Xie, Honggang Wang, Hossein Pishro-Nik, Qian Yu
Daiheng Ni
In this paper, we explore a distributed cyber-physical solution using connected vehicle technology (CVtech) to substantially mitigate transportation systems' safety and efficiency problems. Future vehicles, by communicating with other vehicles (V-V), roadside infrastructures (V-R), and personal com-munication devices (V-P), will adapt to the external regional environment and consequently avoid collisions and congestion. We proposes to seamlessly int e-grate networked and embedded sensing, computational intelligence, and real - time communication (cyber) into transportation infrastructure including veh i- cles and roadsides (physical) to facilitate self - organization and system coordin a- tion. Specifically, this research addresses two specific t hemes: Foundations by …
Driver Dynamics And The Longitudinal Control Model (Paper # 12-0235), Gabriel Leiner, Chaoqun Jia, Daiheng Ni, John D. Leonard
Driver Dynamics And The Longitudinal Control Model (Paper # 12-0235), Gabriel Leiner, Chaoqun Jia, Daiheng Ni, John D. Leonard
Daiheng Ni
Driver psychology is one of the most difficult phenomena to model in the realm of traffic flow theory because mathematics often cannot ca pture the human factors involved with driving a car. Over the past several decades, many models have attempted to m odel driver aggressiveness with varied results. The recently proposed Longitudinal Contro l Model (LCM) makes such attempt, and this paper offers evidence of the LCM's usefulness in modeling road dynamics by analyzing decel eration rates that are commonly associated with various levels of aggression displayed by drivers. The paper is roughly divided into three sections, one outlining …
Driver Traffic Speed Variance Modeling With Application In Travel Time Variability Estimation (Paper # 12-2618), Haizhong Wang, Zhixia Li, David S. Hurwitz, Daiheng Ni
Driver Traffic Speed Variance Modeling With Application In Travel Time Variability Estimation (Paper # 12-2618), Haizhong Wang, Zhixia Li, David S. Hurwitz, Daiheng Ni
Daiheng Ni
Traffic speed variance is defined as a measure of the dispersion of space mean speeds among drivers. Empirical speed-density observations exhibit a structured traffic speed vari-ance which has been found to be associated to the road accident rate, the fatality rate, and travel time variability. The objective of this paper is to propose a generalized traffic speed variance function to describe this structured variance and identify its potential applications. In nature, the proposed speed variance function is a response of the speed-density curve with two additional parameters. A series of logistic speed-density curve with varying parameters is used in the …
Vehicle Longitudinal Control And Traffic Stream Modeling (Paper # 12-0156), Daiheng Ni, John D. Leonard, Gabriel Leiner, Chaoqun Jia
Vehicle Longitudinal Control And Traffic Stream Modeling (Paper # 12-0156), Daiheng Ni, John D. Leonard, Gabriel Leiner, Chaoqun Jia
Daiheng Ni
A simple yet efficient traffic flow model, in particular one that describes vehicle longitudinal operational control and further characterizes traffic flow fundamental diagram, is always of great interest to many. Though many models have been proposed in the past, each with their own advantages, research in this area is far from conclusive. This paper contributes a new model, i.e., the longitudinal control model (LCM), to the arsenal with a unique set of properties. The model is suited for a variety of transportation applications, among which a concrete example is provided herein.