APPLYING DATA FUSION TECHNIQUES TO TRAVELER INFORMATION SERVICES IN HIGHWAY NETWORK

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概要

• 論文の詳細を見る

• Data fusion techniques are applied to traveler information services and used to build an accident duration estimation function. The accident duration is estimated at the initial occasion of an accident. The data fusion procedure clusters the values of each factor into a small number of intervals and effectively smoothes the data noise to the model. In most experiments, the mean absolute percentage errors of the estimated outputs are under 25%, indicating an acceptable forecasting effect. Through the factor sensitivity analysis, time of day, number of vehicles & vehicle type involved in accidents, and geometry have high significance in conducting the accident duration models. The results confirm that the data fusion techniques are practical and reliable for developing traveler information systems. This study is granted by National Science Council, Taiwan, under the project number NSC93-2218-E-006-094. It shows very promising practical applicability of the proposed models in the Intelligent Transportation Systems context.

著者

• LEE Ying

  Department of Hospitality Management, Ming Dao University

• LEE Ying

  Department of Transportation and Communication Management Science National Cheng Kung University

• WEI Chien-Hung

  Department of Transportation and Communication Management Science National Cheng Kung University

関連論文

• MULTI-DEMSIONAL INTERGRATED TRANSPORT POLICIES OPTIMIZATION BASED ON GENETIC ALGORITHM AND REVISION REPORT
• APPLYING DATA FUSION TECHNIQUES TO TRAVELER INFORMATION SERVICES IN HIGHWAY NETWORK
• DESIGN OF DYNAMIC NEURAL NETWORKS TO FORECAST SHORT-TERM RAILWAY PASSENGER DEMAND
• DATA FUSION AND FEATURE COMPOSITION APPROACH TO SEQUENTIAL ACCIDENT DURATION FORECASTING

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