In this paper, we consider the scheduling of jobs that may be competing for mutually exclusive resources. We model the conflicts between Supported in part by NSF Grant CCR-9309456. Email: irani@ics.uci.edu . y Supported in part by Caltrans Contract 65Q090. Email: vitus@ics.uci.edu . 1 2 S. Irani and V. Leung jobs with a conflict graph, so that all concurrently running jobs must form an independent set in the graph. This model is natural and general enough to have applications in a variety of settings; however, we are motivated by the following two specific applications: traffic intersection control and session scheduling in high speed local area networks with spatial reuse. Our goal is to bound the maximum response time of any job in the system. It has been previously shown [13] that the best competitive ratio achievable by any online algorithm for the maximum response time on interval or bipartite graphs is \Omega\Gamma n), where n is the number of nodes in the conflict graph. As...

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

In this paper, we consider the scheduling of jobs that may be competing for mutually exclusive resources. We model the conflicts between jobs with a conflict graph, so that the set of all concurrently running jobs Supported in part by NSF Grants CCR-9309456 and GER-94-50142. Email: irani@ics.uci.edu . y Supported in part by Caltrans Contract 65Q090. Email: vitus@ics.uci.edu . 1 2 S. Irani and V. Leung must form an independent set in the graph. This model is natural and general enough to have applications in a variety of settings; however, we are motivated by the following two specific applications: traffic intersection control and session scheduling in high speed local area networks with spatial reuse. Our results focus on two special classes of graphs motivated by our applications: bipartite graphs and interval graphs. In all of the upper bounds, we devise algorithms which maintain a set of invariants which bound the accumulation of jobs on cliques (in the case of bipar...

In this paper, we discuss simulation results for the traffic signal control problem. Our algorithms are motivated by theoretical results from Supported in part by Caltrans Contract 65Q090. Email: vitus@ics.uci.edu . y Supported in part by NSF Grant CCR-9309456. Email: irani@ics.uci.edu . 1 2 V. Leung and S. Irani a model for scheduling jobs that may be competing for mutually exclusive resources. The conflicts between jobs are modeled by a conflict graph, so that the set of all concurrently running jobs must form an independent set in the graph. We focus on the problem of minimizing the maximum response time of any job that enters the system. For the specific graph which arises in the traffic intersection control problem, we have shown [14] a simple algorithm which achieves the optimal competitive ratio. We have also studied scheduling with conflicts under probabilistic assumptions about the input. Each node i has a value p i such that a job arrives at node i in any given...

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 ...

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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...

The literature suggests that information can improve the efficiency of road use. This study seeks to establish a model system for exploring the interactions between a transport market and a monopolist market for ATIS. These arise from the mutual interactions between road use and traveller information benefits, in turn affecting system efficiency. We examine the properties of the information market, and the relationship between monopoly information pricing and system efficiency. From model experiments, we find that increasing information penetration will lead to negative effects for the already informed drivers. In addition, monopoly information pricing is not the most attractive option from a system efficiency viewpoint, because of the relatively high price charged by the monopolist. Third, a user or a producer subsidy on the information market can help realise the second-best optimum of road use. Finally, relatively low uncertainty on the road and high information costs limit the monopolist’s profit on the information market, as well as relative system efficiency. While relatively inelastic demand for mobility negatively affects the monopolist’s profit, information is less useful for the system as a whole at both low and high levels of demand elasticitiies. 1.