S. Travis Waller

On the online shortest path problem with limited arc cost dependencies

This paper is concerned with the stochastic shortest path problem with recourse when limited forms of spatial and temporal arc cost dependencies are accounted for. Recourse is defined as the opportunity for a decision maker to reevaluate his or her remaining path when en-route information is available. Formulations with recourse typically provide opportunities for corrective actions when information becomes available; information here is modeled as arc cost dependencies, defined as spatial and temporal. System properties are stated and proved and solution algorithms are developed for limited cases of spatial and temporal arc cost dependencies. The numerical results verify some of the theoretical insights and demonstrate the applicability of the introduced algorithms.

An Internet-based geographic information system that integrates data, models and users for transportation applications

Abstract This paper is concerned with the development of an Internet-based geographic information system (GIS) that brings together spatio-temporal data, models and users in a single efficient framework to be used for a wide range of transportation applications – planning, engineering and operational. The functional requirements of the system are outlined taking into consideration the various enabling technologies, such as Internet tools, large-scale databases and distributed computing systems. Implementation issues as well as the necessary models needed to support the system are briefly discussed.

Integration of Activity-Based Modeling and Dynamic Traffic Assignment

The traditional trip-based approach to transportation modeling has been used for the past 30 years. Because of limitations of traditional planning for short-term policy analysis, researchers have explored alternative paradigms for incorporating more behavioral realism in planning methodologies. On the demand side, activity-based approaches have evolved as an alternative to traditional trip-based transportation demand forecasting. On the supply side, dynamic traffic assignment models have been developed as an alternative to static assignment procedures. Much of the research effort in activity-based approaches (the demand side) and dynamic traffic assignment techniques (the supply side) has been undertaken relatively independently. To maximize benefits from these advanced methodologies, it is essential to combine them through a unified framework. The objective of this paper is to develop a conceptual framework and explore practical integration issues for combining the two streams of research. Technical, computational, and practical issues involved in this demand–supply integration problem are discussed. The framework is general, but specific technical details related to the integration are explored by using CEMDAP for activity-based modeling and VISTA for dynamic traffic assignment modeling. Solution convergence properties of the integrated system, specifically examining different criteria for convergence, different methods of accommodating time of day, and the influence of step size on convergence are studied. The integrated system developed is empirically applied to two sample networks selected from the Dallas–Fort Worth system in Texas.

A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations

: The rise in natural and man-made disasters in recent years has led to an increased interest in emergency evacuation planning. Athough the vast majority of the existing evacuation planning models assumes system optimal (cooperative) behavior, recent research has shown that during large evacuations people tend to exhibit selfish (noncooperative) behavior. This article presents a hybrid bilevel model that balances both behavioral assumptions (in the upper level, shelter assignment occurs in a system optimal fashion, whereas evacuees are free to choose how to reach their assigned shelters in the lower level), hence providing a model that is more in line with the current state-of-the-knowledge of human behavior during disasters. The proposed model is solved using a simulated annealing algorithm. A hypothetical evacuation scenario in Sioux Falls, South Dakota, illustrates the proposed model. We demonstrate that the resulting evacuation strategies can be significantly different from conventional system optimal evacuation plans.

Dynamic Continuous Network Design Problem: Linear Bilevel Programming and Metaheuristic Approaches

A linear bilevel programming model and two analytical solution methods (the K th-best algorithm and mixed integer programming reformulation) for the continuous network design problem are presented on the basis of the multiorigin, single-destination, user-optimal dynamic traffic assignment (UO DTA) problem. From the test problem, it is shown that the bilevel formulation is more desirable than the two known single-level models based respectively on system-optimal and UO DTA. For the multiorigin, multidestination, larger-size problem, three metaheuristics that can produce solutions beyond local optimality are employed: simulated annealing (SA), genetic algorithm (GA), and random search (RS). These metaheuristics share the same functional evaluation: a simulation-based UO DTA that propagates traffic according to Daganzos cell transmission model. From computational results, GA outperforms the others for all three test problems in terms of solution quality, convergence speed, and processor time, whereas SA and...

Automated Intersection Control: Performance of Future Innovation Versus Current Traffic Signal Control

Congestion is one of the biggest challenges faced by the transportation community; congestion accounted for an estimated

Path-Constrained Traffic Assignment: Model and Algorithm

87.2 billion in losses in 2007 alone. Transportation professionals need to go beyond capacity expansion projects and explore novel strategies to mitigate traffic congestion. Automated intersection management is a novel strategy that has the potential to greatly reduce intersection delay and improve safety. Although the implementation of such a system is contingent on the development of automated vehicles, competitions such as the Grand Challenge and Urban Challenge of the Defense Advanced Research Projects Agency have shown that this technology is feasible and will be available. Therefore, the development of the infrastructure and associated control methods required to exploit fully the benefits of such technology at the system level is critical. This research explores one such innovative strategy, an automated intersection control protocol based on a first-come, first-served (FCFS) reservation system. The FCFS reservation system was shown to reduce intersection delay significantly by exploiting the features of autonomous vehicles. Microscopic simulation experimental results showed that the FCFS reservation system significantly outperformed a traditional traffic signal in reducing delay.

Incorporating Environmental Justice Measures into Equilibrium-Based Network Design

This paper presents a mathematical programming model and solution method for the path-constrained traffic assignment problem, in which route choices simultaneously follow the Wardropian equilibrium principle and yield the distance constraint imposed on the path. This problem is motivated by the need for modeling distance-restrained electric vehicles in congested networks, but the resulting model and solution method can be applied to various conditions with similar path-based constraints. The equilibrium conditions of the problem reveal that any path cost in the network is the sum of corresponding link costs and a path-specific out-of-range penalty term. The suggested method, based on the classic Frank–Wolfe algorithm, incorporates an efficient constrained shortest-path algorithm as its subroutine. This algorithm fully exploits the underlying network structure of the problem and is relatively easy to implement. Numerical results from the examples of problems provided show how the equilibrium conditions are reshaped by the path constraint and how the traffic flow patterns are affected by different constraint tightness levels.

Environmental Justice Analysis: Challenges for Metropolitan Transportation Planning

A new variation of the user equilibrium-discrete network design problem (UE-DNDP) is proposed for achieving environmental justice (EJ) or equity among population groups. This research is motivated by the federal requirement that transportation plans using federal money include an evaluation of EJ and that the planning agency mitigate, where feasible, any disproportionate impacts on protected populations (i.e., minority and low-income groups). Eight potential objective functions focused on maximizing equity of congestion and travel time are developed and discussed with regard to their applicability for the upper level of this bilevel problem. On the basis of assumed knowledge of the origin-destination travel matrices by population group, numerical analysis is conducted to assess the performance of each proposed formulation. The lower-level UE problem is solved by using the Frank-Wolfe method, and because of the hard combinatorial nature of EJ-UE-DNDP, a selectorecombinative genetic algorithm is implemented to search the solution space for feasible network improvement strategies efficiently. The results of numerical analysis suggest that Pareto-optimal approaches can be successfully applied and that the most effective formulations minimize the difference between the change in congestion or travel time across population groups due to the selected improvement projects.

Robust Dynamic Continuous Network Design Problem

This research focuses on three major challenges of incorporating environmental justice into metropolitan transportation planning. The data needed are compared with the data currently available on the spatial distributions of race and income, the spatial distributions of trip ends, trip tables, network performance, and cost estimates of improvements. Several conflicting definitions of equity are offered, as are applications for each within the context of environmental justice. The importance of choosing a correct unit of analysis is discussed, with particular emphasis on how the geographic unit of analysis is a poor proxy for the group unit, which is theoretically required, as the analysiss purpose is to compare performance measures across groups. The primary goal of this paper is to explore challenging topics such as these raising questions and concerns. The answers to the questions raised will differ depending on each implementing agencys objectives and resources.