No abstract

Communication technology has achieved unprecedented development in recent years, and its applications in transportation systems and automobiles are also increasing. During driving, the driver obtains not only traffic information through observation but also more traffic information beyond the visual range through the Internet of Vehicles (IoV). Therefore, to better describe the evolution law of traffic flow in the IoV environment and to provide some theoretical and strategic support for the coming of the autonomous driving era in the future, an extended car-following model accounting for average optimal velocity difference and backward-looking effect based on IoV environment is proposed. The linear analysis and nonlinear analysis of the model are calculated separately, and the neutral stability curve and the coexistence curve together prove the validity of the model. Subsequently, the numerical simulation verified the accuracy of the theoretical analysis and also proved that the extended model can enhance the stability of traffic flow.

The control position for traditional variable speed limits (VSL) is generally fixed. However, when congested traffic flow reaches the variable message sign, the effect of VSL on easing congestion will be reduced. It is, therefore, necessary to dynamically set the location of the variable message sign while implementing dynamic traffic control. Combined with the emerging Internet of Vehicles environment, this paper designs a variable-length cell transmission model to describe the uneven uniformity of traffic and to calculate the speed limits position of dynamic VSL. Then combined with the VSL control, an objective optimization function is established, with the travel time being the object. By numerical analysis and simulation, the sensitivity of the dynamic transmission model is verified under different traffic conditions. The results show that the proposed model can change the length of the cell and better describe the uneven distribution of the crowded tuple. The location of variable message signs can be set dynamically, and it can significantly alleviate the congested area. In addition, the new dynamic variable message sign control method can shorten travel times and improve traffic efficiency.

No abstract

Research of car-following behavior is very important to alleviate traffic congestion and ensure traffic safety. To describe the car-following behavior of connected vehicles and restore the real driving environment, this paper presents an improved car-following model for connected vehicles by considering driver characteristic and speed information of multiple vehicles, which reflects the interaction between adjacent connected vehicles and the influence of driver characteristic on the stability of car-following. The linear stability analysis and nonlinear stability analysis prove that the improved model is effective and can promote the stability of traffic flow more than other models. In addition, the numerical simulations show that the new model performs better in eliminating disturbances than other models. Finally, the parameters of proposed model are calibrated based on NGSIM data. The results show that the new model performs well in car-following process, keeping a safe distance from the leader vehicle without sudden acceleration and deceleration. The new model also can predict the acceleration behavior of the leader vehicle after emergency brake. In summary, the model proposed in this paper can be used as active safety technology to prevent collision accidents, or as a user-defined function or model in the traffic simulation software, or as car-following strategy in driverless algorithms.