No abstract

Taking into consideration the overlapped influences of multiple rail transit stations upon land use characteristics, this study newly develops a multi-objective land use allocation optimization model to decide the land use type and intensity of every undeveloped land block of an urban area. The new model is solved by successively utilizing the non-dominated sorting genetic algorithm and the technique for order performance by similarity to ideal solution to obtain the least biased Pareto-optimal land development scheme. The study area is an urban region around two metro stations in Beijing of China. The influencing scopes of these two stations are overlapped in part, and many of the land blocks in the study area are not yet developed. It is shown that the newly developed land use allocation optimization model is able to rationally achieve multi-objectives in coordination to the most extents for the sustainable urban development in view of the integrated effect of multiple rail transit stations.

This paper introduces a group decision making of intelligent traffic control system based on multi-agent technique, in order to meet the urban traffic management actual demands of China. The model is designed to realize that several urban traffic managers and directors may taking part in decision at the same time based on the group decision theory and the multiagent technique .Moreover, the required functions of the multi-users participating in the conversation and preventing the passive colony from expanding are fully considered by the model. The characteristics of the group decision making such as the diversities among the managers and directors and human-machine organic fusion also have been taken into account. By the applications of this model, we will realize that the urban traffic managers and directors will make decision more scientifically, command more sensitively, react more quickly than before in order to improve the traffic resources using efficiency and service level of road network, decrease air pollution and power consuming, advance the environment, economic and society continuable development.

In order to promote the work of "reduction and control" in public security traffic management, and to clarify the temporal and spatial evolution characteristics of traffic fatalities, this paper is based on the data of road traffic fatalities from 2019 to 2021, with the help of the AutoNavi map open platform to complete the spatial location of accidents. Using the improved density clustering algorithm, the clustering analysis was carried out on the key illegal behavior accidents, using geographic information analysis technology to analyze the spatial distribution characteristics and temporal evolution characteristics of fatal traffic accidents caused by three types of key violations. In the regional distribution of fatal accidents of drunk driving and unlicensed driving, the situation is mainly stable and improving, and the fatal accidents of failing to give way according to regulations are mostly deteriorating; in addition, the construction of the new city in District VII and the construction of the sub-center of the city in District VIII have been carried out steadily, the traffic demand has become increasingly strong, and many types of illegal activities and accidents have shown a worsening trend, and XI and IV districts are mainly stabilizing and improving. The results of the study are helpful for the traffic police department to implement refined management of regional traffic accidents and make corresponding preventive measures.

No abstract