Collaborative Research: Modeling Human Driving Behavior and Response with Applications to Intelligent Agent-Based Traffic Flow Simulation

合作研究：利用基于智能代理的交通流模拟对人类驾驶行为和响应进行建模

• 批准号: 0527508
• 负责人: Lu Sun
• 金额: --
• 依托单位: Catholic University of America
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0527508&HistoricalAwards=false
• 关键词: Collaborative; Research; Modeling; Human; Driving

Human decision-making in everyday vehicular traffic situations determines in large measure the properties of the traffic stream and the resulting quality of traffic service, which affect the reliability, safety and efficiency of transportation systems and the quality of urban life. This project puts forward a comprehensive, multidisciplinary research approach to characterize and model human cognitive driving behavior and subsequent response in traffic flow systems. Specifically, the dynamics of driver behavior, taken at the individual level and as part of a group, evolving over time and space will be systematically studied as a complex system. By developing behavior-based models of human decision-making in traffic situations and integrating the behavior models in computer simulation systems, the study addresses fundamental questions in traffic science and promises to improve prevailing understanding of traffic flow phenomena as well as the fidelity and reliability of the current state of the art of traffic flow simulation. The outcome of the project will reveal the interrelationship between microscopic elements of driver behavior (e.g. reaction times and other time lags, over-reaction, risk averse and risk seeking behaviors in car following and lane changing) and macroscopic traffic flow phenomena through analytical investigation and simulation, validated by field observation. The subject of the investigation entails considerable economic and social significance, with wide application in human cognitive science, as well as in traffic operations and management. The project also provides an excellent and unique opportunity for student exposure to cross-disciplinary research and helps build a diverse scientific workforce.

人类在日常车辆交通情况下的决策在很大程度上决定了交通流的特性以及由此产生的交通服务质量，从而影响交通系统的可靠性、安全性和效率以及城市生活质量。 该项目提出了一种全面的、多学科的研究方法来表征和建模人类认知驾驶行为以及交通流系统中的后续响应。具体来说，驾驶员行为的动态，从个人层面和作为群体的一部分，随着时间和空间的变化，将作为一个复杂的系统进行系统研究。通过开发交通状况下人类决策的基于行为的模型，并将行为模型集成到计算机模拟系统中，该研究解决了交通科学中的基本问题，并有望提高对交通流现象的普遍理解以及交通流的保真度和可靠性。交通流模拟的当前技术水平。该项目的成果将通过分析调查和分析，揭示驾驶员行为的微观要素（例如跟车和变道中的反应时间和其他时间滞后、过度反应、风险规避和风险寻求行为）与宏观交通流现象之间的相互关系。模拟，通过现场观察验证。该研究课题具有重要的经济和社会意义，在人类认知科学以及交通运营和管理中具有广泛的应用。该项目还为学生接触跨学科研究提供了绝佳且独特的机会，并有助于建立一支多元化的科学队伍。