Shan Guan

In the process of rapid urbanization and accelerated transformation of urban community public space structures, the optimization of community space structure and the quality of the living environment has attracted the attention of academic circles. Existing research has shown that the well-being of community residents is positively correlated with community social capital. The starting point of this study was howaimed to increase residents’ social capital and enhance their sense of life happiness through a good community space environment design. This paper focuses on the analysis of the spatial perception level of community residents and the correlation between environmental space design elements and social capital and explores the environmental factors that affect the accumulation of social capital of community residents to put forward suggestions for the optimal design of community public spaces. A field survey of 30 communities in Shanghai City was conducted based on relevant theories and practical cases both at home and abroad. The six dimensions of “social cohesion”, “sense of community belonging”, “social participation”, “social network”, “social interaction”, and “neighborhood relationship” are used to assign social capital, and the six dimensions are respectively regressed with residents’ environmental perception of the community and the objective environment of the community. The correlation between the social capital of community residents and the three elements of public space (space, facilities, and social elements) was obtained. According to the public space optimization design strategy of the three elements, public space design principles for improving community social capital are proposed, including the principles of diversification, humanization, suitability, and inclusiveness, and the corresponding suggestions are proposed from three aspects: point space, line space, and surface space.

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.