Numerical Simulation of Motor Vehicles’ Courtesy Behavior on Crosswalk Based on Car-Following Model

In observing driver courtesy towards pedestrians at unsignalized crosswalks, a behavioral model was adopted in a simulation based on the GM Car-Following Model. The SIMI Motion Software was used to extract the vehicle operation data from Wenyi South Road and Hanyuan Road in Xi'an City. The parameters of the GM Car-Following Model were calibrated by genetic algorithm. The road simulation environment based on the Car-Following Model was constructed by MATLAB. In the case of no stopping, uniform deceleration avoidance with advance notice, emergency brake avoidance without advance notice, changes such as the displacement of the Car-Following queue, headway, speed, acceleration, and deceleration were analyzed by numerical simulation. The results show that when there is advance notice before the crosswalk, the minimum headway distances of Car1-Car2, Car2-Car3, Car3-Car4 and Car4-Car5 are 7.09 m, 7.38 m, 7.65 m, 7.91 m, and the average rates of change of the headway during deceleration are 0.78 m/s, 0.74 m/s, 0.71 m/s, 0.68 m/s respectively;in the absence of advance notice before the crosswalk, the minimum headway distances of Car1-Car2, Car2-Car3, Car3-Car4 and Car4-Car5 are 7.28 m, 7.75 m, 8.19 m, 8.59 m, and the average rates of change of the headway during deceleration are 1.57 m/s, 1.25 m/s, 1.04 m/s, 0.96 m/s, respectively. Therefore, in order to effectively prevent the occurrence of vehicle rear-end events, it's necessary to set traffic signs and markings on the preceding section of the intersection or road exhibiting behavioral comity.

Simulation optimization for train movement on a single-track railway

Optimizing train movement has a great significance for railway traffic. In this paper, based on the optimal velocity car-following model, we propose a new simulation model for optimizing train movement in railway traffic. Here a kind of single-track railway is considered. Our aim is to reduce the energy consumption of train movement and ensure the train being on time by controlling the velocity curve of train movement. The simulation results indicate that the proposed model is effective for optimizing train movement. In addition, some major characteristics of train movement can be well captured. This method provides a new way to optimize train movement in railway traffic.

Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow

This work focuses on the potential impacts of the autonomous vehicles in a mixed traffic condition represented in traffic simulator Simulation of Urban MObility(SUMO)with real traffic flow.Specifically,real traffic flow and speed data collected in 2002 and 2019 in Gothenburg were used to simulate daily flow variation in SUMO.In order to predict the most likely drawbacks during the transition from a traffic consisting only manually driven vehicles to a traffic consisting only fully-autonomous vehicles,this study focuses on mixed traffic with different percentages of autonomous and manually driven vehicles.To realize this aim,several parameters of the car following and lane change models of autonomous vehicles are investigated in this paper.Along with the fundamental diagram,the number of lane changes and the number of conflicts are analyzed and studied as measures for improving road safety and efficiency.The study highlights that the autonomous vehicles’features that improve safety and efficiency in 100%autonomous and mixed traffic are different,and the ability of autonomous vehicles to switch between mixed and autonomous driving styles,and vice versa depending on the scenario,is necessary.