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Traffic flow estimation on the expressway network using toll ticket data

机译:使用收费数据估算高速公路网络上的交通流量

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摘要

Traffic flow estimation (TFE) is an important task for intelligent transportation systems, especially for expressway system in travel demand management, road conditions monitor etc. Traffic flow is usually detected by fixed sensors, which is neither practical nor economically feasible to cover all expressway component links. Additionally, the existing research usually ignores the effects of drivers' dwell behaviours on TFE. To fill these gaps, this study proposes a TFE method based on toll ticket data (TTD) which records trip information, except the actual route. Meanwhile, dwell time, as a key component of drivers' journeys, will be integrated into the proposed approach. In this study, a Gaussian mixture model for the origin-destination pairs with multiple alternative routes will be formulated. Moreover, expectation-maximisation algorithm is introduced to estimate link traffic flows and dwell time distributions simultaneously. By TTD collected from the Shandong Province Expressway in China, the proposed approach is calibrated and applied to TFE empirically. The results show that the proposed approach has a good performance on TFE with consideration of dwell time.
机译:交通流量估算(TFE)是智能交通系统的一项重要任务,尤其是对于行驶需求管理,道路状况监控器等中的高速公路系统。交通流量通常由固定传感器检测,这对于覆盖高速公路的所有组成部分既不实际也不经济链接。此外,现有研究通常忽略驾驶员的居住行为对TFE的影响。为了填补这些空白,本研究提出了一种基于通行费票数据(TTD)的TFE方法,该方法可以记录除实际路线以外的行程信息。同时,停留时间作为驾驶员出行的重要组成部分,将被整合到提议的方法中。在这项研究中,将为具有多个替代路线的起点-终点对建立一个高斯混合模型。此外,引入了期望最大化算法来同时估计链路流量和驻留时间分布。通过从中国山东省高速公路收集的TTD,对提出的方法进行了校准,并在经验上应用于TFE。结果表明,考虑到停留时间,该方法在TFE上具有良好的性能。

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