Assessing the Potential Benefits of IntelliDrive-based Intersection Control Algorithms

Mobile wireless communication technologies enabling vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have recently emerged as the name of IntelliDrive initiative in the United States. Numerous studies on IntelliDrive applications for traffic safety, operations, and management have been conducted successfully. However, applications dedicated to the intersection control systems and their potential benefits have not been fully explored thus far. This dissertation study assessed the potential benefits of two IntelliDrive-based intersection control algorithms: a cooperative vehicle infrastructure system (CVIS)-based control algorithm and a cumulative travel time responsive (CTR) real-time intersection control algorithm.;IntelliDrive is based on wireless communications that do not always guarantee perfect connections in the real world. Thus, this dissertation research investigated the performance of IntelliDrive communication standards by integrating NCTUns, a wireless communications network simulator, for wireless communications and VISSIM for vehicular movements. This dissertation explicitly modeled communications latencies and packet drops and discovered that such drop rates would increase as both the number of (On-Board Equipment) OBEs and the distance between transceivers increase.;Under the IntelliDrive environment enhanced by CVIS and perfect market penetration, this dissertation research proposed a CVIS-based intersection control algorithm that was designed to manipulate vehicles' maneuvers such that cars keep crossing the intersection without collisions with other cars. Comprehensive simulation experiments implemented on a four-way single-lane intersection under varying congestion conditions showed that the CVIS-based control algorithm significantly improved the intersection performance: 99% and 33% of stop delay and total travel time reductions, respectively.;This dissertation research proposed a CTR real-time intersection control algorithm that is deployable in the near future and is feasible under imperfect IntelliDrive market penetrations. The CTR algorithm employs a stochastic state estimation technique utilizing Kalman Filtering to estimate the cumulative travel times under imperfect market penetration rates. Comprehensive simulation experiments performed on a hypothetical isolated intersection showed that given 100% market penetration, the CTR algorithm improved the total delay time and average speed of the intersection by 34% and 36%, respectively. However, the improvements gradually degraded as the market penetration rates decreased, and marginal improvements (i.e., 1.5% of travel time savings) were observed at 30% of market penetration rates.