National Center for Metropolitan Transportation Research
(METRANS) at USC/CSU Long Beach

Main campuses:
University of Southern California Long Beach State University

Funding:
Federal - $500,000/year
State - $500,000/year

Approximation Algorithms for Bidding in Combinatorial Auctions for the Procurement of Transportation Service Contracts

Our research develops computationally tractable approximation methods for estimating values and constructing bids and identifies ways that smaller carriers can work to receive the benefits available to larger carriers. The health of many US industries is dependent upon the health of the trucking industry and the ability of trucking companies to honor their contracts. In addition, developing tools that will improve the overall efficiency of trucking operations has significant environmental and quality of life impacts for non-commercial vehicle operators.

The research will be published in several journal articles, presented at conferences and a non-technical summary of the research will be developed for submission to ACCESS Magazine.

Development of An Artificial Intelligence Based Traffic Simulation Model Using the Discrete Element Method

An artificial intelligence based discrete element method for traffic simulation is proposed. The novel form of the inter-element interaction laws would allow extraction of key parameters in driver behavior. The effect of changes in certain transportation policies could also be determined as part of the analysis. By using the proposed model, it may be possible to identify changes in driver behavior and public policy that would facilitate increased effective capacity of the existing traffic infrastructure. With this approach, it may be possible to increase the efficiency of the current roads and freeways through policy, strategy, and driver education. Such an approach to improved infrastructure utilization could be cheaply implemented and easily modified for changes in the economic and urban environment.

Transportation system management.

Identification and Measurement of Freeway Congestion

The proposed research will develop a methodology to identify and measure total, recurrent, and non-recurrent congestion delay on urban freeways. The methodology will be applicable to urban freeways that are instrumented with loop detectors or other surveillance systems. The proposed methodology calculates the average and the probability distribution of congestion delays by cause (recurrent, incident related, weather and other factors). The methodology also will quantify the congestion impacts on travel time and travel time variability. The proposed work is based on recent research by the investigator. The findings to-date indicate that reliable measurement of congestion should provide measures of uncertainty in congestion. In application on two real-life corridors, incident-related delay is found to be between 13 to 30 percent of the total congestion delay during peak periods.

This study will contribute to a better understanding of the freeway congestion and its contributing factors based on real-world study corridors.

Improved Developer Models for the Sacramento Region

Urban models have advanced greatly in the last 20 years. Recent models represent the floor space developer explicitly, increasing the behavioral validity of the land markets in the models. We believe, however, that there is a need to separately represent the developers of large projects on the urban edge, as these projects can strongly affect subsequent development patterns. We propose to estimate and test such a model, to be used within an advanced urban model for the Sacramento region. We will estimate and test a developer model for large projects on the urban edge and implement it within the PECAS urban model.

This model will improve the validity of urban models, by explicitly representing large real estate developments on the urban edge.

Improved Modeling of Network Transportation Flows, Including Land Use-Transportation Interactions: A Research Collaboration Between USC (METRANS) and Caltrans District 7 (Office of Advance Planning)

This research project will consist primarily of a technical audit of current practices and some District work products. The project will also introduce land use/transportation and level-of-service feedbacks into the standard four-step transportation model

This project will audit current practices of some District work products and introduce land use/transportation and level-of-service feedbacks into the standard four-step transportation model.

Robust Investment Decisions for Highway Capacity Expansions

In this project we consider the problem of deciding which project to execute, i.e. where to add new HOV lanes in the Los Angeles highway system, taking into account the existing uncertainty in the data that is present in the problem. The problem is modeled assuming there is a fixed budget and trying to minimize the total travel time or average travel time throughout the system. The solution to this problem depends on the assumed origin-destination flows, which are estimates of the true unknown origin-destination flows. In addition this information evolves over time, thus creating the need to find a solution that is not significantly affected by changes in this data. We propose to study and develop a technique to obtain a robust solution to this problem. A robust solution is feasible and close to optimal for all plausible data instances of the problem.

Better tools for capital investment decisions.

Capacity provision and pricing in road transport networks in an imperfectly competitive economy

This project will assess the impact of accounting for imperfect competition on the economic prescriptions for road infrastructure pricing and its provision. The motivation is that the assumption of perfect competition is not realistic. It also is at odds with developments in mainstream economics, where imperfect competition models become the rule rather than the exception, precisely because of their higher degree of realism.

The theoretical models with numerical applications will be described in at least one paper. The benefits are that data sources and model specifications are explored, which should be useful in assessing if and how large-scale econometric work should be carried out.

A Novel Approach to Routing and Dispatching Trucks Based on Partial Information in a Dynamic Environment.

Our research will develop new theory and methodologies within an area that has received little attention. The research will benefit an industry that is vital to the economy. The project will impact the trucking industry by developing techniques to support efficient routing of systems opportunity between the two ends of the spectrum.

Better freight transportation routing techniques.