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Network impacts of a road capacity reduction: Empirical analysis and model predictions

机译：道路通行能力降低对网络的影响：实证分析和模型预测

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In spite of their widespread use in policy design and evaluation, relatively little evidence has been reported on how well traffic equilibrium models predict real network impacts. Here we present what we believe to be the first paper that together analyses the explicit impacts on observed route choice of an actual network intervention and compares this with the before-and-after predictions of a network equilibrium model. The analysis is based on the findings of an empirical study of the travel time and route choice impacts of a road capacity reduction. Time-stamped, partial licence plates were recorded across a series of locations, over a period of days both with and without the capacity reduction, and the data were 'matched' between locations using special-purpose statistical methods. Hypothesis tests were used to identify statistically significant changes in travel times and route choice, between the periods of days with and without the capacity reduction. A traffic network equilibrium model was then independently applied to the same scenarios, and its predictions compared with the empirical findings. From a comparison of route choice patterns, a particularly influential spatial effect was revealed of the parameter specifying the relative values of distance and travel time assumed in the generalised cost equations. When this parameter was 'fitted' to the data without the capacity reduction, the network model broadly predicted the route choice impacts of the capacity reduction, but with other values it was seen to perform poorly. The paper concludes by discussing the wider practical and research implications of the study's findings.
机译：尽管它们在策略设计和评估中得到广泛使用，但有关流量平衡模型如何很好地预测实际网络影响的报道却相对较少。在这里，我们介绍我们认为是第一篇论文，该论文一起分析了实际网络干预对观察到的路由选择的显式影响，并将其与网络均衡模型的前后预测进行了比较。该分析基于对道路通行能力降低的行驶时间和路线选择影响的实证研究结果。在几天之内，无论有无容量减少，都会在一系列地点记录带时间戳的部分牌照，并且使用专用统计方法在地点之间“匹配”数据。假设检验用于确定在有能力减少和没有能力减少的几天之间的旅行时间和路线选择的统计学显着变化。然后，将交通网络平衡模型独立应用于相同的场景，并将其预测与经验结果进行比较。从路线选择模式的比较中，可以看出该参数对空间的影响特别显着，该参数指定了广义成本方程中假设的距离和行驶时间的相对值。当此参数“适合”数据而不减少容量时，网络模型可以广泛预测容量减少对路径选择的影响，但如果使用其他值，则会发现其性能较差。本文最后通过讨论该研究结果的更广泛的实践和研究意义进行了总结。

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