Cooperative Adaptive Cruise Control and exhaust emission evaluation under heterogeneous connected vehicle network environment in urban city.

With the development of information communication and artificial intelligence, the ICV (intelligent connected vehicle) will inevitably play an important part in future urban transport system. In this paper, we study the car following behaviour under the heterogeneous ICV environment. The time to receive information varies from vehicle to vehicle, since the manual vehicles and autonomous vehicles co-exist on the road. By introducing time-varying lags function, a new car following model is proposed, and the cooperative control strategy of this model is studied. Based on Lyapunov function theory and linear matrix inequality (LMI) approach, the sufficient condition that the existence of the feedback controller is given, which makes the closed-loop system asymptotically stable under mixed traffic flow environment. That is to say, traffic congestion phenomenon under heterogeneous traffic flow can be effectively suppressed, and the feedback controller gain matrix can be obtained via solving linear matrix inequality. Finally, by simulation the method is verified effective in alleviating traffic congestions and reducing fuel consumption and exhaust emissions. It could be a useful reference to Cooperative Vehicle Infrastructure System and Smart City.