COLLABORATIVE RESEARCH: MODELING HUMAN DRIVING BEHAVIOR AND RESPONSE WITH APPLICATIONS TO INTELLIGENT AGENT-BASED TRAFFIC FLOW SIMULATION

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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.