Commercial Operations

A probabilistic benefit-cost model was developed to determine the value associated with collecting traffic data. In partnership with the City of Saskatoon, a probabilistic model was developed to evaluate the Benefit Cost Ratio of knowing the weights of the vehicles on the City’s road network. It is well documented that overloaded trucks significantly damage the road network. By knowing the weights of these vehicles, initial traffic projections for design and planning can be more accurate and proactive preventative measures can be performed, thereby reducing costly rehabilitation. Furthermore, enforcement can be targeted to focus on those vehicles that are potentially overweight and allow legal trucks to proceed unimpeded.

This paper outlines the preliminary results of the probabilistic benefit-cost modeling for the City of Saskatoon and identifies potential methods for financing a progressive data collection program using Public-Private Partnerships.

International Road Dynamics Inc.

Presented at the ITS America Annual Conference and Exposition, May 19-22, 2003 Minneapolis, Minnesota

In this paper, the authors continue the discussion of the TFC system evaluation framework and plan developed by Collura and Plotnikov (2001) and address the issues of: (a) TFC system alternatives available on the market in the U.S. and (b) TFC system performance measures to compare alternative systems in terms of their operating costs.

The authors conclude that while there are a number of independent factors affecting the composition, functions, and performance of a TFC system, the type of payment media, fare media, TFC equipment, and mode of transit are four major factors associated with TFC system performance in terms of operating costs. The authors also suggest that cost effectiveness and labor-intensiveness metrics would be useful evaluation measures to assess the operating costs of existing and new TFC systems. Finally, the authors present statistical data on selected heavy rail systems in the U.S. to illustrate the use of the framework and evaluation measures and to support the notions that cost-effectiveness and labor-intensiveness may vary considerably among heavy rail TFC systems and that this variation is due, in part, to the TFC technology including the type of fare media.

Virginia Tech Transportation Institute

Presented at the ITS America Annual Conference and Exposition, April 29 –May 2, 2002 Long Beach, California

This paper presents a quick overview of four microscopic traffic simulation models and evaluates their performances using a case study of modeling a coordinated signal system. Four models used are CORSIM, Paramics, SIMTRAFFIC, and VISSIM. In order to provide reference performance measures for various traffic signal settings including pretimed and actuated, SYNCHRO program is utilized.

Keywords: Traffic Simulation, Microscopic Simulation, Signalized Intersections, Evaluation, Performance measure, SIMTRAFFIC, CORSIM, VISSIM, and Paramics

University of Virginia

Ajou University

Presented at the ITS America Annual Conference and Exposition, May 19-22, 2003 Minneapolis, Minnesota

FleetForward is an operational test designed to demonstrate the impact of real-time traffic information on commercial vehicle operations, such as dispatching and routing. While real-time data is an important element of transportation condition information, its availability in the operational test also highlights the need for forecasted information. One specific need in FleetForward is the ability to forecast the duration of a current traffic incident.

This paper describes research focused upon forecasting incident duration using nonparametric regression. This forecasting technique is data-driven, as it searches a database to find a neighborhood of past incidents similar to the current incident. The data source for developing this model was the Information Exchange Network (IEN) of the I-95 Corridor Coalition. The general conclusion of this paper is that the quality and scope of the data in the incident database is a major factor in the performance of a forecasting model.

University of Virginia: Smart Travel Laboratory - Department of Civil Engineering

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

This paper describes recently completed research investigating corridor travel time mean and variance estimation. Simultaneous travel time data were collected along two corridors from several sources including instrumented test vehicles, commercial vehicles, and an ITS data source. The ITS data source included automatic vehicle identification (AVI) in Houston, Texas and inductance loop detectors in San Antonio, Texas spaced every 0.5 mile (0.8 kilometer).

This paper identifies several important findings. First, ITS travel time data sources, such as AVI in Houston, were found to provide a very cost-effective data collection method. They also provide accurate travel time mean estimates while providing more confidence in the travel time estimate. Second, commercial vehicles were found to have longer travel times than those reported by the ITS data sources. This demonstrates that it may be reasonable to provide travel time maps and information in real-time specifically; for commercial vehicles for just-in-time or fleet operations. Third, the difficulty of using spot-speed measurements (i.e., estimates from loop detectors) for corridor travel time estimates is also identified. Finally, the correlation between adjacent links along a corridor was investigated. It was found that the covariance is generally non-zero and positive with the Houston AVI data. This indicates that the link variances cannot simply be summed to calculate corridor variance.

Texas Transportation Institute

Texas A&M University - Department of Civil Engineering

Presented at the ITS America Annual Conference and Exposition, April 29 –May 2, 2002 Long Beach, California