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In the upcoming decades, connected vehicles will join regular vehicles to appear on roads, and the characteristics of traffic flow will be changed accordingly. To model the heterogeneous traffic mixing regular and connected vehicles, a generic car-following framework is first proposed in this paper. A linear stability condition is theoretically derived, which indicates that the stability of the heterogeneous traffic is closely related to the penetration rate and the spatial distribution of connected vehicles. The generic car-following framework is applied by taking the Intelligent Driver Model as an example, and it is shown that connected vehicles can obviously enhance the stability of traffic flow and improve traffic efficiency in particular when traffic is in congestion. Moreover, a driver assistance strategy based on distributed feedback control is developed for connected vehicles, and the simulation results show that the proposed driver assistance strategy performs satisfactorily in stabilizing traffic as well as improving traffic efficiency.

To mitigate traffic oscillations that usually sustainably propagate upstream, this paper proposes a jam-absorption driving (JAD) strategy in the framework of Newell's car-following theory. The basic idea of the JAD strategy is to guide a vehicle to move slowly before being captured by an oscillation and terminate the slow movement when the vehicle would start to leave the jam if no such slow movement was implemented. To practically implement the idea, a two-step method is proposed to estimate the time–space ending point of the strategy, and a proper vehicle is selected to implement the JAD strategy based on a given expected absorbing speed and current traffic conditions. To test the JAD strategy, two simulated traffic scenarios are constructed based on a realistic data-driven car-following model. The first scenario, which only reproduces one oscillation, directly shows the effectiveness of the JAD idea in preventing wave propagation and capacity drop. The second scenario, which contains a series of traffic oscillations induced by the rubbernecking behavior, validates the proposed JAD strategy in more complicated and realistic conditions. It is indicated that the JAD strategy is able to absorb traffic oscillations; thus, the side effects incurred by the oscillations could be subsequently mitigated. The significance of this paper is to provide us a new idea to mitigate traffic oscillations, i.e., the JAD strategy.

In transportation networks, traditional fixed sensors are used to monitor the operation of transportation systems. However, fixed sensors cannot move once they are installed. In this paper, the motion ability of traffic sensors is introduced to improve the performance of transportation network surveillance. A mobile traffic sensor routing problem is proposed, modeled as a novel vehicle routing problem. A measure of traffic information acquisition benefits is developed and used to gauge the surveillance performance. To solve this mobile-sensor routing problem, a hybrid two-stage heuristic algorithm is designed, which is based on particle swarm optimization and ant colony optimization. Numerical experiments are conducted. The results show that the mobile traffic sensor has a better network surveillance performance than the fixed sensor in most experimental cases.