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Modeling travel time under ATIS using mixed linear models

机译：使用混合线性模型在ATIS下建模旅行时间

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The objective of this paper is to model travel time when drivers are equipped with pre-trip and/or en-route real-time traffic information/advice. A travel simulator with a realistic network and real historical congestion levels was used as a data collection tool. The network included 40 links and 25 nodes. This paper presents models of the origin-to-destination travel time and en-route short-term route (link) travel time under five different types and levels of advanced traveler information systems (ATIS). Mixed linear models with the repeated observation's technique were used in both models. Different covariance structures (including the independent case) were developed and compared. The effect of correlation was found significant in both models. The trip travel time analysis showed that as the level of information increases (adding en-route to the pre-trip and advice to the advice-free information), the average travel time decreases. The model estimates show that providing pre-trip and en-route traffic information with advice could result in significant savings in the overall travel time. The en-route short-term (link) travel time analysis showed that the en-route short-term (link) information has a good chance of being used and followed. The short-term qualitative information is more likely to be used than quantitative information. Learning and being familiar with the system that provides the information decreases en-route short-term delay.
机译：本文的目的是当驾驶员配备有预旅行和/或在途实时交通信息/建议时，对旅行时间进行建模。具有现实网络和实际历史拥堵程度的旅行模拟器被用作数据收集工具。该网络包括40个链接和25个节点。本文介绍了五种不同类型和级别的高级旅行者信息系统（ATIS）下的起点到目的地旅行时间和途中短期路线（链接）旅行时间的模型。在两个模型中都使用了具有重复观测技术的混合线性模型。开发并比较了不同的协方差结构（包括独立案例）。发现在两个模型中相关性的影响均显着。行程时间分析显示，随着信息水平的提高（在行程前添加路线，在无建议的信息中添加建议），平均行程时间会减少。该模型估算表明，在提供出行前和途中交通信息以及建议的情况下，可以大大节省总体出行时间。途中短期（链接）旅行时间分析表明，途中短期（链接）信息很有可能被使用和遵循。短期定性信息比定量信息更可能被使用。学习和熟悉提供信息的系统可减少途中的短期延迟。

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