Lunhui Xu - IEEE Xplore Author Profile

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Intelligent transportation system is one of the important ways to solve the contradiction between transportation demand and supply in modern society. The implementation of intelligent transportation system projects is not only conducive to improving the safety, production efficiency and benefits of transportation, but also related to the rational use of land resources and energy, the improvement o...Show More
The accurate estimation of pedestrian movement location is one of hot research topics among Intelligent Transportation Systems. In the real-time pedestrian tracking application, the WiFi-based localization method is seriously affected by environmental noise, which results in the large positioning error. Aiming at this issue, this paper first analyzed the localization technologies based on the Rece...Show More
Urban road congestion is increasingly serious, in order to optimize the traffic situation, and improve the efficiency of vehicles, so as to provide service for traveling user. Then analysis four major systems, namely the bus electronic station board system, evaluation system of urban road traffic state, urban traffic guidance system and website demonstration system. Regarding average travel speed,...Show More
The paper built an urban road network model through analysis of urban traffic flow characteristics. The minimizing total travel time of vehicle in the road network was taken as control target, and the dynamic path model was built. The ant colony algorithm was used to find out the optimum path from start point to destination by collecting the real-time traffic information of the road network. Then ...Show More
This paper focuses on traffic flow forecasting which is an essential component in traffic control or route guidance system. A combination forecasting model called GM-GRNN based on GM(1, 1) and GRNN is built for short-term traffic flow time series. The basic theory and features of General Regression Neural Network (GRNN) and its advantages are introduced. The weight of combination model is determin...Show More
This paper proposes a transit-priority signal control method for urban intersection using fuzzy neural techniques. In order to reduce the delay of buses and passengers, a changeable-phase-order method is proposed. The phase with more passengers is preferential to be selected as the next phase by the end of current phase. The green increase time of current phase is inferred by a fuzzy controller wh...Show More
Traditional shortest path algorithm didn't consider the condition of road network, such as no left-turn. This paper restructured the topology of network chart considering the complex traffic regulations, in order to rebuild the model of urban traffic network, and proposed a new optimal path algorithm adapted for urban traffic guidance system based on Dijkstra algorithm. At last, we used Visual Bas...Show More