We use a very simple description of human driving behavior to simulate traffic. The regime of maximum vehicle flow in a closed system shows nearcritical behavior, and as a result a sharp decrease of the predictability of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive larger parts of the transportation system towards this regime of maximum flow, we argue that in consequence the traffic system as a whole will be driven closer to criticality, thus making predictions much harder, A simulation of a simplified transportation network supports our argument.

Evaluation of Intelligent Transportation Systems (ITS) at the planning level, as well as various short-term planning projects, require the use of appropriate tools that can capture the dynamic and stochastic interactions between demand and supply. The objective of this thesis is to develop a methodological framework for such applications and implement it in the context of an existing dynamic traffic assignment system, DynaMIT. The methodological framework captures the day-to-day evolution of traffic. Furthermore, it models traveler behavior and network performance, in response to special events and situations such as incidents, weather emergencies, sport events etc. The new planning tool DynaMIT-P, consists of a supply (network performance) simulator, a demand simulator and algorithms that capture their interactions. The

A major strategy of federal ITS initiatives and state departments of transportation is to provide traveler information to motorists through various means, including variable message signs, the internet, telephone services like 511, in-vehicle guidance systems, and TV and radio reports. This is relatively uncontroversial, but its effectiveness is unknown. Drivers receive value from traveler information in several ways, including the ability to save time, but perhaps more importantly, other personal, social, safety, or psychological impacts from certainty. This information can be economically valued. The benefits of reduction in driver uncertainty when information is provided at the beginning of the trip by various means is the main variable we aim to measure in this research, in which we assess user preferences for routes as a function of the presence and accuracy of information, while controlling for other trip and route attributes, such as trip purpose, travel time, distance, number of stops, delay, esthetics, level of commercial development, and individual characteristics. Data is collected in a field experiment in which more than 100 drivers, given real-time travel time information with varying degrees of accuracy, drove four of five alternative routes between a pre-selected OD pair in the Twin Cities

Many IVHS products and user services have been designed to alleviate urban traffic congestion by improving level of service and increasing vehicle throughput.There is concern that such improvements in the efficiency of the transportation system could lead to increases in travel demand and motor vehicle emissions. The cornerstone of arguments against IVHS deployment on the basis of air quality is the notion that increased roadway capacity will result in a new system with equal congestion but more vehicles and emissions.Some IVHS detractors argue that the detrimental effects of induced demand, manifested in increases in the number and length of vehicle trips, may outweigh the potential emission benefits of improved traffic operations and system efficiencies that are brought about by IVHS This argument, however, reflects a misunderstanding of the economic mechanisms leading to changes in the quantity of travel, as well as confusion between demand increases associated with induced traff...

Morning commuters adjust their departure times in response to day-to-day changes in congestion. Advanced Traveler Information Systems (ATIS) may enable motorists to employ fundamentally new strategies when adapting their departure times to fluctuations in congestion. At the same time, new driver strategies will likely give rise to different road network behaviors. This paper explores the mutual feedback between driver strategy and traffic system performance through a simulation model of rush hour commuting. Motorists in this model choose departure times according to three adaptive strategies. When commuters apply adaptive strategies that require ATIS in the present model, outcomes for both individual motorists and the system as a whole are by several measures worse than when drivers use a simple strategy that does not require ATIS. These results largely agree with an earlier study of a nearly identical model of rush-hour commuting. This document is available in HTML on the ...

Selecting the most appropriate traffic control strategy for incident congestion management can have a major impact on the extent and duration of the resulting congestion. This research investigated the effectivenesses of several control strategies on various incident conditions. The selected control strategies representing possible ITS technologies included traffic metering (ATMS), traffic diversion (ATIS), and traffic diversion with signal timing modification (ATIS/ATMS). The analysis was conducted on a hypothetical dense grid sur- face street network. Mid-block incidents of various durations were tested. The results indicated that the ATIS/ATMS based solution can reduce congestion duration up to 27 minutes, with a saving of 261 vehicle- hours of delay. A sensiti...

www.elsevier.com/locate/tra Simultaneous determination of the equilibrium market penetration and compliance rate of advanced traveler information systems

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