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Accurate and timely traffic flow information is important for the successful deployment of intelligent transportation systems. Over the last few years, traffic data have been exploding, and we have truly entered the era of big data for transportation. Existing traffic flow prediction methods mainly use shallow traffic prediction models and are still(More)
Based on the big-data collected from Space-Air-Ground, i.e. Space means satellite, Air means helicopter, the key technologies of novel ITS (Intelligent Transportation System) are investigated, including data acquisition sensor, dynamic data transmission, massive data storage, multi-source data fusion, massive data mining and analysis, etc. On this basis,(More)
Traffic data is a fundamental component for applications and researches in transportation systems. However, real traffic data collected from loop detectors or other channels often include missing data which affects the relative applications and researches. This paper proposes an approach based on deep learning to impute the missing traffic data. The(More)
Reducing travel time of emergency vehicles (EVs) has a potential in significant savings of life and property. Integrating modern intelligent transportation system (ITS) with EV signal preemption seems to be a solution. But existing EV signal preemption systems often break the current signal coordination and impact a lot on the normal traffic streams. In(More)
With the acceleration of China's urbanization, more and more unexpected disasters in big cities make a severe challenge to city emergency traffic management. Under this background, we present a heuristic implementation of urban emergency traffic evacuation in this paper. Firstly, we refer to a popular evacuation demand generation model to generate the(More)
It has been recognized by many researchers that accurate bus travel time prediction is critical for successful deployment of traffic signal priority (TSP) systems. Although there exist a lot of studies on travel time prediction for Advanced Traveler Information Systems (ATIS), this problem for TSP purpose is a little different and the amount of literature(More)
Natural or man-made disasters can cause huge losses of human life and property. One of the effective and widely used response and mitigation strategies for these disasters is traffic evacuation. Evacuation destination choice is critical in evacuation traffic planning and management. In this paper, we propose a partially random destination allocation(More)
Boundary Layer Ingestion (BLI) effects are the new and special issues caused by the in-depth integration of airframe and propulsion system. Based on a mathematical model of the distributed propulsion system and a sliced CFD model of SAX-40, this paper presents a detailed numerical research on the BLI effects of distributed propulsion configuration. The(More)
This paper presents a systematic research on the supercirculation effects of Distributed Propulsion Configuration, based on a mathematical model of the distributed propulsion system and a sliced CFD model of SAX-40. Multiple factors which can affect supercirculation effects such as the deflection angle of thrust, Boundary Layer Ingestion effects, jet flow(More)
Transit signal priority (TSP) is the most effective method to improve the operational efficiency of public transports. This paper presents an adaptive dynamic TSP control method of public traffic, by adjusting the signal time to give buses passing priority at intersections, which can take into account not only the dynamic time of bus's reaching the(More)