Adaptive Preemption of Traffic for Emergency Vehicles
Vamsi Paruchuri
Abstract
Vamsi Paruchuri
Abstract
Minimizing travel time is critical for the successful operation of emergency vehicles. Preemption can significantly help emergency vehicles reach the intended destination faster. Majority of the current studies focus on minimizing and/or eliminating delays for EVs and do not consider the negative impacts of preemption on urban traffic. One primary negative impact is extended delays for non-EV traffic due to preemption that is addressed in this paper. We propose an Adaptive Preemption of Traffic (APT) system for Emergency Vehicles in an Intelligent Transportation System. We utilize the knowledge of current traffic conditions in the transportation system to adaptively preempt traffic at signals along the path of EVs so as to minimize, if not eliminate stopped delays for EVs while simultaneously minimizing the delays for non-emergency vehicles in the system. Through extensive simulation results, we show substantial reduction in delays for both EVs.
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Minimizing travel time is critical for the successful operation of emergency vehicles. Preemption can significantly help emergency vehicles reach the intended destination faster. Majority of the current studies focus on minimizing and/or eliminating delays for EVs and do not consider the negative impacts of preemption on urban traffic. One primary negative impact is extended delays for non-EV traffic due to preemption that is addressed in this paper. We propose an Adaptive Preemption of Traffic (APT) system for Emergency Vehicles in an Intelligent Transportation System. We utilize the knowledge of current traffic conditions in the transportation system to adaptively preempt traffic at signals along the path of EVs so as to minimize, if not eliminate stopped delays for EVs while simultaneously minimizing the delays for non-emergency vehicles in the system. Through extensive simulation results, we show substantial reduction in delays for both EVs.
Key concepts: Preemption, Emergency vehicle, Computer science, Path (computing), Focus (optics), Intelligent transportation system, Real-time computing, Transport engineering