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Latent class model for car following behavior

机译：汽车跟随行为的潜在类模型

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摘要

Car-following behavior, which describes the behavior of a vehicle while following the vehicle in front of it, has a significant impact on traffic performance, safety, and air pollution. In addition, car-following is an essential component of micro-simulation models. Over the last decade the use of microscopic simulation models as a tool for investigating traffic systems, ITS applications, and emission impacts, is becoming increasingly popular. The paper presents a flexible framework for modeling car-following behavior that relaxes some limitations and assumptions of the most commonly used car following models. The proposed approach recognizes different regimes in driving such as car-following, free-flow, emergency stopping, and incorporates different decisions in each regime, such as acceleration, deceleration, and do-nothing depending on the situation. A case study using NGSIM vehicle trajectory data is used to illustrate the proposed model structure. Statistical tests suggest that the model performs better than previous models.
机译：跟车行为描述了跟随前方车辆时车辆的行为，对行车性能，安全性和空气污染有重大影响。此外，跟随汽车是微观仿真模型的重要组成部分。在过去的十年中，使用微观仿真模型作为研究交通系统，ITS应用和排放影响的工具变得越来越流行。本文提出了一种建模汽车跟随行为的灵活框架，该框架放宽了最常用的汽车跟踪模型的一些限制和假设。所提出的方法认识到驾驶中的不同状况，例如汽车跟随，自由流动，紧急停车，并根据情况在每个状况中合并了不同的决定，例如加速，减速和不执行任何操作。通过使用NGSIM车辆轨迹数据的案例研究来说明所提出的模型结构。统计测试表明，该模型的性能优于以前的模型。

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