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首页> 外文会议>COTA international conference of transportation professionals >Freeway Traffic State Estimation and Prediction Based on ETC-Based Path Identification Toll System
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Freeway Traffic State Estimation and Prediction Based on ETC-Based Path Identification Toll System

机译：基于基于ETC的路径识别收费系统的高速公路交通状态估计与预测

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摘要

Electronic toll collection systems are convenient for a freeway toll, and it also provides a new resource for the extraction of freeway traffic state information. This paper analyzed the principle of traffic information collection based on the dedicated short range communication (DSRC) technology based ambiguous path identification toll system. A method of estimating traffic volume of road sections and the average travel time is proposed by processing and fusing the path information and toll data in the system. The average travel time of the link is predicted by using BP artificial neural network. Finally, the field experiments verified the feasibility of the proposed method and analyzed the error of average travel time prediction for freeways based on ETC-based path identification toll system on the test section of Nanjing-Hangzhou Expressway. The average percentage error of prediction results is 9.2%, which indicates satisfactory results.
机译：电子收费系统方便了高速公路的通行费，也为提取高速公路的交通状态信息提供了新的资源。本文分析了基于专用短距离通信（DSRC）技术的模糊路径识别收费系统的交通信息收集原理。通过处理和融合系统中的路径信息和通行费数据，提出了一种估算路段交通量和平均行驶时间的方法。链接的平均旅行时间是使用BP人工神经网络预测的。最后，野外试验验证了该方法的可行性，并在宁杭高速公路试验段基于基于ETC的道路识别收费系统，分析了高速公路平均行驶时间预测的误差。预测结果的平均百分比误差为9.2％，表明结果令人满意。

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