Abstract
Connected and automated vehicles (CAVs) can bring energy, mobility, and safety benefits to transportation. Energy savings can be achieved by solving a mathematical optimization problem for a lookahead horizon using previewed traffic information enabled by connectivity. However, it is challenging to predict shortterm traffic, especially for mixed-traffic scenarios, where both connected and unconnected vehicles are on the road.
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