Luliang Tang

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—In this paper, a bottom–up vehicle emission model is proposed to estimate real-time CO 2 emissions using intelligent transportation system (ITS) technologies. In the proposed model, traffic data that were collected by ITS are fully utilized to estimate detailed vehicle technology data (e.g., vehicle type) and driving pattern data (e.g., speed,(More)
—The efficiency and accuracy of road network data in the latest electronic maps cannot satisfy the current demands of their application's needs. The present paper proposes a new method to use floating car data to detect and update changes in the road network. An experiment was carried out with actual data to test and verify the feasibility of the novel(More)
In this paper, we propose a novel approach for mining lane-level road network information from low-precision vehicle GPS trajectories (MLIT), which includes the number and turn rules of traffic lanes based on naï ve Bayesian classification. First, the proposed method (MLIT) uses an adaptive density optimization method to remove outliers from the raw GPS(More)
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