Collaborative Research: Analysis and Modeling of Traffic Instabilities in Congested Traffic

协作研究：拥堵交通中的交通不稳定分析与建模

• 批准号: 0856699
• 负责人: Soyoung Ahn
• 金额: $ 14.55万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0856699&HistoricalAwards=false
• 关键词: Collaborative; Research; Analysis; Modeling; Traffic

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The primary objectives of this collaborative research study are to 1) better understand the interactive roles played by lane-changing and car-following, 2) quantify their effects on oscillations, and 3) develop a mathematical simulation model that accurately predicts the evolution of oscillations. Traffic oscillations are stop-and-go driving motions that arise in congested traffic. These oscillations propagate against traffic flow and typically grow as they propagate over space. They have long been thought and modeled strictly as a result of instabilities in car-following behavior. However, recent empirical studies have refined this long-accepted belief and suggest that lane-changing maneuvers are primary triggers for oscillations - formations and growths and that car-following effects further impact the growth of oscillations. The effects of lane-changing and car-following have been illustrated qualitatively and are yet to be quantified in detail. Microscopic analyses of individual vehicle behavior of lane-changing and car-following will be performed using high-resolution vehicle trajectory data that are made available by a recent development in data collection and processing techniques. Furthermore, this study will enhance understanding on the effects of heterogeneous traffic due to different vehicle classes and roadway characteristics on the evolutionary behavior of oscillations in space. The empirical findings will provide a framework to develop a simple, parsimonious model with physically meaningful parameters while incorporating the necessary factors. The model will be validated with empirical observation, which will be a rare contribution to the field of traffic theory. The outcome of this research will be a better understanding and a more effective traffic forecasting model of congested traffic.This study addresses one of the key congestion-related problems deeply rooted in urban society. Oscillations have a negative impact on environment and safety, as they increase fuel consumption, emissions and driving discomfort. By providing a better understanding of the phenomena and a model to describe them, this study will likely prompt various researches in traffic flow and management strategies. Furthermore, the results from this study will promote development of better models for safety and environmental impacts which incorporate oscillatory driving. The research activities will be transferred through new courses which the PIs are currently developing as well as conventional venues such as journal publications and conferences. This project will involve two Ph.D. students, one of which is a female student. The PIs will also recruit and mentor an undergraduate student through Arizona State University's Fulton Undergraduate Research Initiative.

该奖项是根据《2009年美国复苏和再投资法案》(Public Law 111-5)资助的。这项合作研究的主要目标是：1)更好地了解变道和跟车所起的交互作用；2)量化它们对振荡的影响；3)开发准确预测振荡演变的数学模拟模型。交通振荡是指在拥堵的交通中出现的走走停停的驾驶运动。这些振荡在交通流量的作用下传播，通常在空间传播时增长。长期以来，人们一直认为它们是由于跟车行为不稳定而被严格建模的。然而，最近的经验研究提炼了这一长期被接受的观点，并表明换道操作是振荡形成和增长的主要触发因素，而跟车效应进一步影响了振荡的增长。换道和跟车的影响已经得到了定性的说明，但还有待于详细的量化。将利用数据收集和处理技术的最新发展提供的高分辨率车辆轨迹数据，对个别车辆的变道和跟车行为进行微观分析。此外，这项研究将加深对不同车辆类别和道路特征导致的不同交通对空间振荡演化行为的影响的理解。经验发现将提供一个框架，以开发一个简单、简约的模型，该模型具有物理上有意义的参数，同时纳入必要的因素。该模型将通过经验观测进行验证，这将是交通理论领域的一项难得的贡献。这项研究的结果将是对拥堵交通的更好的理解和更有效的交通预测模型。本研究针对根植于城市社会的与拥堵相关的关键问题之一。振动对环境和安全有负面影响，因为它们增加了燃油消耗、排放和驾驶不适。通过提供对这些现象的更好的理解和描述它们的模型，这项研究可能会促进交通流和管理策略的各种研究。此外，这项研究的结果将促进开发包含振荡驱动的更好的安全和环境影响模型。研究活动将通过私人投资机构目前正在开发的新课程以及期刊、出版物和会议等传统场所进行转移。这个项目将涉及两名博士生，其中一名是女学生。PI还将通过亚利桑那州立大学的富尔顿本科生研究计划招募和指导一名本科生。