Qing-Jie Kong

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This paper presents a systematic solution to efficiently estimate the traffic state of large-scale urban road networks. We first propose the new approach to construct the exact GIS-T digital map. The exact digital map can lay the solid foundation for the traffic state estimation with the data from Global Positioning System (GPS) probe vehicles. Then, we(More)
This paper presents an information-fusion-based approach to the estimation of urban traffic states. The approach can fuse online data from underground loop detectors and global positioning system (GPS)-equipped probe vehicles to more accurately and completely obtain traffic state estimation than using either of them alone. In this approach, three parts of(More)
In this paper, a GPS/GIS integrated system for urban traffic flow analysis is proposed. Urban GIS-T data are used to construct the GIS map of urban area when the system begins its work. Afterwards, real-time GPS data of probe vehicles are periodically collected to implement the location amendment. And then, location-amended GPS data are dynamically fitted(More)
In this paper, we will introduce a fusion-based system composed of real-time traffic state surveillance. This system can realize the real-time traffic state estimation with over 10,000 bidirectional road sections, all the links of the Shanghai urban road network. The system consists of three modules: SCATS data processing (MS), GPS data processing (MG), and(More)
Current research on traffic flow prediction mainly concentrates on generating accurate prediction results based on intelligent or combined algorithms but ignores the interpretability of the prediction model. In practice, however, the interpretability of the model is equally important for traffic managers to realize which road segment in the road network(More)
Nowadays, probe vehicles equipped with Global Position System (GPS) are an effective way of collecting real-time traffic information. This paper first briefly introduces the Curve-Fitting Estimation Model (CFEM), which is one of the typical methods using GPS data to estimate the traffic flow state. After that, it is detailedly analyzed how many probe(More)
This paper addresses an issue of short-term traffic flow prediction in urban traffic networks with traffic signals in intersections. An effective spatial prediction approach is proposed based on a macroscopic urban traffic network model. In contrast with other time series based or spatio-temporal correlation methods, this research focuses on the substantial(More)
On the basis of previous researches, an improved evidential fusion approach is presented to integrate heterogeneous multi-sensor data in Urban Advanced Traveler Information Systems. The method inherits the advantages of the previous model in terms of the real-time processing feature; meanwhile, its performance is improved by adding a mechanism to evaluate(More)