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Road congestion in urban environments, especially near signalizedintersections, has been a major cause of significant fuel and time waste.Various solutions have been proposed to solve the problem of increasing idlingtimes and number of stops of vehicles at signalized intersections, ranging frominfrastructure to vehicle-based techniques. However, all the solutionsintroduced to solve the problem have approached the problem from a singlevehicle point of view. This research introduces a game-theoretic cooperativespeed optimization framework to minimize vehicles' idling times and number ofstops at signalized intersections. This framework consists of three modules tocover individual autonomous vehicle speed optimization; conflict recognition;and cooperative speed decision making. A time token allocation algorithm isintroduced through the proposed framework to allow the vehicles to cooperateand agree on certain speed actions such that the average idling times andnumber of stops are minimized. Simulation to test and validate the proposedframework is conducted and results are reported.

Cooperative Autonomous Vehicle Speed Optimization near Signalized Intersections