In order to study the heterogeneous traffic environment generated by connected automated vehicles (CAVs) and human-driven vehicles (HDVs), the car-following model and basic graph model of the mixed traffic flows of connected automated vehicles and human-driven vehicles are constructed. Considering driver response time and the communication delay of the connected automated vehicles control system, the three-parameter variation law of traffic flow is summarized to solve the traffic congestion problem in heterogeneous traffic environments. Firstly, the probability of six scenarios in queues of cooperative adaptive cruise control (CACC) vehicles, adaptive cruise control (ACC) vehicles, and human-driven vehicles in heterogeneous traffic environments is analyzed. The car-following model is defined, and the parameters are calibrated, and then a fundamental diagram model of traffic flow balance is derived. On this basis, considering driver response time and the communication delay of the linear controller, a car-following model considering multi-party delay is updated and established, and the heterogeneous traffic flow analysis of the two types of delays in the model is carried out. Finally, the microscopic simulation environment is constructed based on SUMO 1.17.0 (Simulation of Urban Mobility) software. The results show that when the permeability (the proportion of connected automated vehicles in a traffic stream) exceeds 0.6, CAVs account for the main part in the heterogeneous traffic, which has a positive impact on the maximum flow and the optimal density and can effectively improve the maximum capacity of the road. The simulation results show that the updated car-following model is reasonable and accurate in dealing with driver response time and V2V communication delay.

In recent years, intercity carpooling has been vigorously developed in China. Considering the differences between intercity carpooling and intracity carpooling, this paper first defines the intercity carpooling path optimization problem with time window. Based on the balance of interests among passengers, platform, and government, a multi-objective function is constructed to minimize passenger cost, maximize platform revenue, and minimize carbon emission cost, with vehicle capacity, boarding and alighting points, vehicle service, and other constraints. Secondly, in order to further improve the coordination ability and search speed of the operator, this paper uses the particle swarm optimization algorithm to help the operator remember the previous search position and iterative information, and designs the PSO (Particle Swarm Optimization) improved NSGA-II (Non-dominated Sorting Genetic Algorithm) algorithm to solve the multi-objective model. Finally, the feasibility of the model is verified by numerical analysis of Xi’an–Xianyang intercity carpool. The results show that the path of vehicle 1 is 5-8-O-D-16-13, the path of vehicle 2 is 7-3-6-O-D-15-11-14, and the path of vehicle 3 is 2-1-4-O-D-12-10-9. Compared with NSGA-II algorithm, the PSO-NSGA-II algorithm designed in this paper has significant advantages in global search ability and convergence speed.

In order to optimize management systems of traffic accidents, including shifting from `subsequent punishment' to `prior restraint' and changing the `emergency management' to `normality management', a `prior restraint' risk evaluation method was proposed based on the AHP-TOPSIS-RSR, which was the integration of AHP, TOPSIS and RSR innovatively. Then the risk evaluation model of expressway traffic safety was constructed and applied to the risk evaluation of YONGWU expressway traffic safety in China. The result indicates that the evaluated road segment has a high risk grade, which is consistent with the practical condition. The method in this paper can be applied to the safety risk of expressways and determine the risk grade. This moves the state-of-art of traffic accident management forward and provides the scientific basis for expressway traffic safety risk management.

The lack of adequate parking has become the major bottleneck of urban development. The reason for the inaccuracy of the past parking demand forecasting methods is the incomplete consideration of factors at work, which prevents universal applicability, leads to a large prediction error, and so on. Using survey data, parking demand was divided into labor parking demand, which is affected by employment, and commercial parking demand, which is mainly affected by commercial area parking demand and economic development. The paper introduces the concept of regional development factors, and the parking demand forecast takes full account of the economy, society, transportation, and other levels of development affecting parking demand in different regions. We use development factors to modify the trip attraction model and then apply it to two Chinese districts.

Monitoring is important for urban road traffic safety management. Our proposed disaster prevention and mitigation reasonable response projects, , emergency rescue and large equipment transport can produce great social effects. Based on the applications of the simulation software, the status of emergency management and analysis of the emergency management system is discussed and establishes the design framework and processing for the emergency management system of the urban road network, thereby proving the rationality of the methods.

The threat to expressway safety is uncertain and polytrophic. To enhance the pertinence and protective effect of the `prior restraint' measure, the sensitivity of expressway traffic safety risk factors was analyzed. The analysis was based on orthogonal array testing where the object function was the risk efficiency, enabling us to arrange the major and minor relationship of risk factors, and then determine the sensitivity risk factors. Our experiment shows that the major and minor relationship of risk factors based on sensitivity analysis is accurate and in correspondence with the actual traffic conditions on the YONGWU expressway. In addition, safety precautions focused on sensitivity factors have a positive effect on traffic safety. We provide a scientific basis for specific traffic safety risk management through sensitivity analysis.