首页|Investigators from Tongji University Target Intelligent Transport Systems (Coope rative Decision Making for Connected Automated Vehicles In Multiple Driving Scen arios)
Investigators from Tongji University Target Intelligent Transport Systems (Coope rative Decision Making for Connected Automated Vehicles In Multiple Driving Scen arios)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Transportat ion - Intelligent Transport Systems. According to news reporting out of Shanghai, People’s Republic of China, by NewsRx editors, research stated, “To improve the application range of decision-making systems for connected automated vehicles, this paper proposes a cooperative decision-making approach for multiple driving scenarios based on the combination of multi-agent reinforcement learning with c entralized planning. Specifically, the authors derived driving tasks from drivingscenarios and computed the policy functions for different driving scenarios as linear combinations of policy functions for a set of specific driving tasks.”
ShanghaiPeople’s Republic of ChinaAsiaIntelligent Transport SystemsTransportationTongji University
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