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首页> 外文会议>18th world congress on intelligent transport systems : Featuring its america's annual meeting and exposition >PREDICTION OF TRAVEL TIME TREND ON URBAN EXPRESSWAY USING VEHICLE OCCUPANCY
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PREDICTION OF TRAVEL TIME TREND ON URBAN EXPRESSWAY USING VEHICLE OCCUPANCY

机译：基于车辆占用率的城市高速公路出行时间趋势预测

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A travel time is one of the most important information for drivers. However, a travel timechanges dynamically according to traffic conditions such as traffic congestion and a trafficaccident. It is therefore expected to be provided additional information on travel timeinformation, which shows whether a short future travel time will be increasing or decreasing.In order to predict this travel time trend, we first try to define the travel time trend. Then, weconstruct a prediction model using the Support Vector Machine, which judges the travel timetrend as “Increase”, “Decrease” or “No change” based on traffic congestion length measuredby vehicle occupancies on an urban expressway. As a result of applying the model to real dataof Nagoya Expressway in Aichi, Japan, the travel time trend was predicted accurately.Furthermore, these predicted results are verified whether actual travel time of each driveraccords with the predicted trend. Then, we attempt to predict the difference between thecurrent and the future travel times directly. As a result, the differences can be also predictedaccurately as same as the trend predictions.
机译：出行时间是驾驶员最重要的信息之一。但是，旅行时间 根据交通状况（例如交通拥堵和交通状况）动态变化 意外。因此，预计将提供有关旅行时间的其他信息 信息，表明未来的短途旅行时间会增加还是减少。 为了预测此旅行时间趋势，我们首先尝试定义旅行时间趋势。然后我们 使用支持向量机构建预测模型，该模型可以判断出行车时间 根据测得的交通拥堵长度，趋势为“增加”，“减少”或“不变” 市区高速公路上的车辆占用情况。将模型应用于实际数据的结果 在日本爱知县名古屋高速公路上，可以准确预测出行时间趋势。 此外，这些预测结果可以验证每个驾驶员的实际出行时间是否 符合预测趋势。然后，我们尝试预测 当前和将来的旅行时间。结果，差异也可以预测 准确地与趋势预测相同。

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