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Researchers have attempted to compute a fuel-optimal vehicle trajectory by receiving traffic signal phasing and timing information. This problem, however, is complex when microscopic models are used to compute the objective function. This paper suggests use of a multi-stage dynamic programming tool that not only provides outputs that are closer to optimum, but are also computationally much faster...
Eco-Cooperative Adaptive Cruise Control (ECACC) systems are a type of Cooperative Adaptive Cruise Control (CACC) that compute the most fuel-efficient (or near-fuel efficient) vehicle trajectory using available information regarding roadway characteristics, set-speed, upcoming signal changes and interaction with other vehicles. ECACC leverages information transfer between vehicles and infrastructure...
Recently several artificial intelligence labs have suggested the use of fully equipped vehicles with the capability of sensing the surrounding environment to enhance roadway safety. As a result, it is anticipated in the future that many vehicles will be autonomous and thus there is a need to optimize the movement of these vehicles. This paper presents a new tool for optimizing the movements of autonomous...
The research presented in this paper develops a framework to enhance vehicle fuel consumption efficiency while approaching a signalized intersection through the provision of signal phase and timing information that may be available through vehicle-to-infrastructure communication. While past research uses simplified objective functions to optimize fuel consumption and/or emissions caused by signalized...
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