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Abstract: A mixed integer linear programming (MILP) model was proposed to optimize the spatial-temporal resources at intersections under the environment of mixed traffic flow with connected and autonomous vehicles (CAVs) and human-driven vehicles. The objective of the model is to maximize the intersection capacity, and the constraints mainly include those regarding lane channelization, flow distribution and signal timing settings. The lane channelization and signal timing scheme at intersections were optimized with different CAV driving behavior settings and different CAV penetration rates by taking a typical four-lane intersection as an example. Results show that the optimal channelization and signal timing scheme need to be adjusted with the change of CAV penetration rate and CAV car following behavior. The increase of the CAV penetration rate and the decrease of CAV headway are both beneficial to the improvement of the intersection capacity. The increase in the intersection capacity is slightly larger when the headway of CAV is not affected by the type of vehicles ahead.
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