Modeling driver behavior in work zones: An evaluation of traffic flow impacts in freeway work zones with full lane closures

About twenty percent of the U.S. National Highway System is under construction during the peak summer roadwork season. Fifty percent of all highway congestion is attributed to nonrecurring conditions and work zones are estimated to account for nearly twenty four percent of nonrecurring delay. Work zones account for two percent of roadway crashes and more than 1,000 fatalities per year. The major question on which this research focuses is: How do work zone delineation strategies, intelligent transportation systems (ITS) technologies, and driver behavior impact traffic flow and crash potential in and around work zones? To address this question effectively, one might consider assessing actual traffic situations under local conditions with the aid of a microscopic simulation model. Such simulation tools could be useful to individuals designing work zone deployment plans, developing work zone traffic management concepts, deciding on the use of ITS applications in work zones, and formulating alternate route strategies. In addition, such tools may improve the ability to visualize the impact of delineation and dynamic merge guidance strategies as well as to quantitatively assess the impact on delay and the occurrence of high crash potential situations in and around work zone areas. The underlying objective of this research is to improve the way researchers and practitioners are able to explain and predict traffic conditions and driver behavior as they are impacted by work zone strategies including variable message signs, static signage, tapers, arrow boards, and positive separation. Central to this research was the formulation of an algorithm that improves upon traditional car following theory by incorporating factors such as driver familiarity, adaptability, aggression, and accommodation to the changing road conditions found in work zones. The use of these concepts incorporates two notions: (1) drivers must manage interaction with both the roadway and other drivers; and (2) drivers exhibit varying preferences for early or late merges based on their willingness to respond to upcoming lane restrictions and their inclination to be passive or aggressive in forced merge situations