On the Impact of HOT Lane Tolling Strategies on Total Traffic Level

This paper shows how tolling (or pricing) strategies can be used to control the congestion levels of both untolled and high occupancy toll (HOT) lanes. Using a user-equilibrium method, the paper calculates the number of travelers on each route during the peak period and provides a numerical analysis that determines the distribution of travelers for different tolling strategies. It shows that with the right tolling strategy some travelers who initially plan to use the untolled lane during the peak period will change both their routes (i.e., select the HOT lane) and departure times (i.e., depart earlier or later). Using this result, the paper compares static and dynamic pricing strategies and shows that with a dynamic strategy a larger profit can be earned and congestion reduced in the untolled lane

TRANSIMS Implementation for a Small Network and Comparison with Enhanced Four-Step Model

Travel demand forecasting is a major tool to assist decision makers in transportation planning. While the conventional four-step trip-based approach is the dominant method to perform travel demand analysis, behavioral advances have been made in the past decade. This paper proposes and applies an enhancemnt to the four-step travel demand analysis model called Sub-TAZ. Furthermore, as an initial step toward activity-based models, a TRANSIMS Track-1 approach is implemented utilizing a detailed network developed in Sub-TAZ approach. The conventional four-step, Sub-TAZ, and TRANSIMS models were estimated in a small case study for Fort Meade, Maryland, with zonal trip tables. The models were calibrated and validated for the base year (2005), and the forecasted results for the year (2010) were compared to actual ground counts of traffic volume and speed. The study evaluated the forecasting ability of TRANSIMS versus the conventional and enhanced four-step models and provided critical observations concerning strategies for the further implementation of TRANSIMS.BACKGROUND Traffic pattern prediction is necessary for infrastructure improvement, and travel demand modeling provides tools to forecast travel patterns under various conditions. This modeling involves a series of mathematical equations that represent how people make travel choices. Traditional travel demand models use the four-step method, which was introduced in the 1950s and has been used widely in transportation planning. Although the four-step method has been practical in producing aggregate forecasts, it has some shortcomings. For example, in short-range planning networks, existing and newly constructed roads become congested much faster than forecasted (TRB 2007) and the performance of current four-step models is not always satisfactory. Additionally, these models are not behavioral in nature and as a result they are unable to represent the time chosen for travel, travelers’ responses to demand policies (e.g., toll roads, road pricing, and transit vouchers), non-motorize

Integrated Traffic and Communication Performance Evaluation of an Intelligent Vehicle Infrastructure Integration (VII) System for Online Travel Time Prediction

This paper presents a framework for online highway travel time prediction using traffic measurements that are likely to be available from Vehicle Infrastructure Integration (VII) systems, in which vehicle and infrastructure devices communicate to improve mobility and safety. In the proposed intelligent VII system, two artificial intelligence (AI) paradigms, namely Artificial Neural Networks (ANN) and Support Vector Regression (SVR), are used to determine future travel time based on such information as current travel time, VII-enabled vehicles’ flow and density. The development and performance evaluation of the VII-ANN and VII-SVR frameworks, in both of the traffic and communications domains, were conducted, using an integrated simulation platform, for a highway network in Greenville, South Carolina. Specifically, the simulation platform allows for implementing traffic surveillance and management methods in the traffic simulator PARAMICS, and for evaluating different communication protocols and network parameters in the communication network simulator, ns-2. The study’s findings reveal that the designed communications system was capable of supporting the travel time prediction functionality. They also demonstrate that the travel time prediction accuracy of the VII-AI framework was superior to a baseline instantaneous travel time prediction algorithm, with the VII-SVR model slightly outperforming the VII-ANN model. Moreover, the VII-AI framework was shown to be capable of performing reasonably well during non-recurrent congestion scenarios, which traditionally have challenged traffic sensor-based highway travel time prediction methods

Traffic recovery time estimation under different flow regimes in traffic simulation

AbstractIncident occurrence and recovery are critical to the smooth and efficient operations of freeways. Although many studies have been performed on incident detection, clearance, and management, travelers and traffic managers are unable to accurately predict the length of time required for full traffic recovery after an incident occurs. This is because there are no practical studies available to estimate post-incident recovery time. This paper estimates post-incident traffic recovery time along an urban freeway using traffic simulation and compares the simulation results with shockwave theory calculations. The simulation model is calibrated and validated using a freeway segment in Baltimore, MD. The model explores different flow regimes (traffic intensity) and incident duration for different incident severity, and their effects on recovery time. A total of 726 simulations are completed using VISSIM software. Finally, the impact of congestion and incident delay on the highway network is quantified by a regression formula to predict traffic recovery time. The developed regression model predicts post-incident traffic recovery time based on traffic intensity, incident duration, and incident severity (ratio of lanes closure). In addition, three regression models are developed for different flow regimes of near-capacity, moderate, and low-traffic intensity. The model is validated by collected field data on two different urban freeways

Comparison of TRANSIMS' Light Duty Vehicle Emissions with On-Road Emission Measurements

The Transportation Analysis and Simulation System, TRANSIMS, contains a vehicle emissions module that estimates tailpipe emissions for light and heavy-duty vehicles and evaporative emissions for light-duty vehicles. This paper describes and validates the TRANSIMS emission module and compares its emission estimates to on-road emission-measurements and other state-of-the-art emission models. The trend of the emissions estimated in thirteen different runs in each model are compared. The results indicate that the TRANSIMS model provides consistent trends of estimated carbon monoxide (CO) and hydrocarbons (HC) with field data trends and inconsistent trends of estimated nitrogen lxides (NOx). However, the magnitude of the emission estimated in TRANSIMS is closer to the field data than for other models

Want to Make Your Website Better? Ask a Librarian.

Raise your hand if you have served on a committee in your library. If your hand isn’t raised, just give it some time … libraries definitely like committee work. For instance, I recently had the opportunity to work with a committee consisting mostly of librarians. When the committee’s goals were accomplished, my non-librarian coworker commented that “Librarians sure have a lot of opinions.” Since this article is about usability testing, and is written by and for librarians, let’s test his hypothesis. Let’s also test a few other hypotheses about librarians while we’re at it. (Disclaimer: In this article, “librarians” include staff who work in libraries, and has nothing to do with degrees or job classifications.) Washington County Cooperative Library Services (WCCLS) is a Cooperative of 13 member libraries and two special libraries, each uniquely governed and operated. WCCLS is a primary funding source for member libraries, and our WCCLS “Office” provides other support such as daily courier deliveries, cataloging coordination, and e-book collections. The WCCLS website and Extranet are two other ways the WCCLS Office supports member libraries in Washington County. The WCCLS Extranet is a repository of policies, procedures, and committee meeting documents. It also includes training and promotional materials for WCCLS resources, as well as opportunities for sharing ideas