17-11 Evaluation of Transit Priority Treatments in Tennessee

Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition

Models of Transportation and Land Use Change: A Guide to the Territory

Modern urban regions are highly complex entities. Despite the difficulty of modeling every relevant aspect of an urban region, researchers have produced a rich variety models dealing with inter-related processes of urban change. The most popular types of models have been those dealing with the relationship between transportation network growth and changes in land use and the location of economic activity, embodied in the concept of accessibility. This paper reviews some of the more common frameworks for modeling transportation and land use change, illustrating each with some examples of operational models that have been applied to real-world settings.Transport, land use, models, review network growth, induced demand, induced supply

Impact of traffic management on black carbon emissions: a microsimulation study

This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project

Microsimulation of urban land use

The project ILUMASS (Integrated Land-Use Modelling and Transportation System Simulation) aims at embedding a microscopic dynamic simulation model of urban traffic flows into a comprehensive model system incorporating both changes of land use and the resulting changes in transport demand. The land-use component of ILUMASS will be based on the land-use parts of an existing urban simulation model, but is to be microscopic like the transport parts of ILUMASS. Microsimulation modules will include models of demographic development, household formation, firm lifecycles, residential and non-residential construction, labour mobility on the regional labour market and household mobility on the regional housing market. These modules will be closely linked with the models of daily activity patterns and travel and goods movements modelled in the transport parts of ILUMASS developed by other partners of the project team. The design of the land use model takes into account that the collection of individual micro data (i.e. data which because of their micro location can be associated with individual buildings or small groups of buildings) or the retrieval of individual micro data from administrative registers for planning purposes is neither possible nor, for privacy reasons, desirable. The land use model therefore works with synthetic micro data which can be retrieved from generally accessible public data. ILUMASS is a group project of institutes of the universities of Aachen, Bamberg, Dortmund, Cologne and Wuppertal under the co-ordination of the Transport Research Institute of the German Aerospace Centre (DLR). Study region for tests and first applications of the model is the urban region of Dortmund. The common database will be compiled in co-operation with the City of Dortmund. After its completion the integrated model is to be used for assessing the impacts of potential transport and land use policies for the new land use plan of the city. The paper will focus on the land-use parts of the ILUMASS model. It will present the underlying behavioural theories and how they are made operational in the model design, explain how the synthetic population is generated, show first model results and demonstrate the potential usefulness of the model for the planning process.

Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamic

LIFE Project: Implementing a modelling framework for emergency vehicles advanced priority strategies

Given the aging demographics and rapid urbanisation, cities need to be equipped to respond to emergency (eg. 999 calls) more quickly. By 2050, over 25% of the UK’s population will be over 65. This has implications on the overall health services as well as the NHS Trust to cope with anticipated rise in ambulance call outs amidst worsening urban congestion. Ambulance services are required to reach 75% of emergency calls within 8 minutes. For this reason, there is a growing need to develop new and innovative applications for an even more intelligent use of the existing transport system that will support in real-time emergency vehicles to reach life threatening emergency cases quicker. this paper will discuss the methodology and the preliminary results of the modelling framework implementation of a “Life First Emergency Traffic Control” or “LiFE” system, a ITS implementation seeking to identify the best solution to reduce the time to respond to emergency calls, whilst operating a resilient service with a cost and fuelefficient fleet. Results of the application of a microsimulation model to replicate the behaviour of ambulances in urban area and how different reactions of general traffic can impact on the travel time of an ambulance are presented. The proposed microsimulation modelling framework has been developed with the final aim to understand and evaluate the impacts and the best scenarios to improve ambulance (or any Emergency vehicle) response time and gains in cost-saving, whilst assessing mitigation strategies to reduce other impacts such as residual congestion. The work is part of an Innovate UK collaborative funded project, namely Life First Emergency Traffic Control (LiFE) with the aim to develop an innovative application for an intelligent transport system that operates in realtime to enable ambulances to reach life threatening emergency cases quicker by integrating ambulance route finder applications with traffic management systems

An Integrated Agent-Based Microsimulation Model for Hurricane Evacuation in New Orleans

Mass evacuation of urban areas due to hurricanes is a critical problem that requires extensive basic and applied research. Knowing the accurate evacuation time needed for the entire region in advance such that the evacuation order can be issued on a timely basis is crucial for the officials. Microsimulation modeling, which focuses on the characteristics of individual motorists and travel behavior, has been used widely in traffic simulation as it can lead to the most accurate result. However, because detailed driver response modeling and path processing must be incorporated, vehicle-based microscopic models have always been used only to simulate small to medium sized urban areas. Few studies have attempted to address problems associated with mass evacuations using vehicle-based microsimulation at a regional scale. This study develops an integrated two-level approach by separating the entire road network of the study area into two components, highways (i.e., interstate highways and causeways) and local roads. A vehicle-based microsimulation model was used to simulate the highway part of the road traffic, whereas the local part of the road traffic simulation utilized an agent-based model. The integrated microsimulation model was used to simulate hurricane evacuation in New Orleans. Validation results confirm that the proposed model performs well in terms of high model accuracy (i.e., close agreement between the real and simulated traffic patterns) and short model running time. Sufficient evacuation time is a premise to protect people’s life safety when an area is threatened by a deadly disaster. To decrease the network clearance time, this study also examined the effectiveness of three evacuation strategies for disaster evacuation, including a) simultaneous evacuation strategy, b) staged evacuation strategy based on spatial vulnerabilities, and c) staged evacuation strategy based on social vulnerabilities. The simulation results showed that both staged evacuation strategies can decrease the network clearance time over the simultaneous evacuation strategy. Specifically, the spatial vulnerability-based staged evacuation strategy can decrease the overall network clearance time by about four hours, while the social vulnerability-based staged evacuation strategy can decrease the network clearance time by about 2.5 hours

Microsimulating Cross-Border Truck Movements between Ontario and the United States: An Application using Connected Vehicle Technology

The land-border crossings between Canada and the United States facilitate over half of the goods transported between the two countries. Since trucks are the primary mode of transportation for the movement of these goods, studying the traffic flows and the characteristics of border crossings is of paramount importance for decision makers, planners and researchers. The province of Ontario is home to the busiest border crossings in Canada including the Ambassador Bridge in Windsor, Ontario and the Blue Water Bridge in Sarnia, Ontario. GPS data collected from a large sample of trucks shows the route choice characteristics for these border crossings. The same dataset also shows the destination locations for these trucks. This thesis utilizes VISSIM, a microscopic traffic simulator, and its dynamic traffic assignment, an imbedded route choice model, to replicate these route choice conditions. Once the model is validated with the shares of flows from the observed (i.e., reference) datasets, the route choice behavior is analyzed under different delay conditions. The research also analyzed the effects of connected vehicle technology, at different penetration rates, on the efficiency of border crossing operations. As the connected vehicles increased in the traffic stream, it was observed that traffic was more streamlined and would switch to use the Blue Water Bridge during the simulation of an incident on Highway 401. The penetration rate was increased in 20% increments and with 100% penetration, 7% of total truck traffic had switched to Blue Water Bridge to travel to their U.S. destination

DEVELOPMENT OF A STATISTICALLY-BASED METHODOLOGY FOR ANALYZING AUTOMATIC SAFETY TREATMENTS AT ISOLATED HIGH-SPEED SIGNALIZED INTERSECTIONS

Crashes at isolated rural intersections, particularly those involving vehicles traveling perpendicularly to each other, are especially dangerous due to the high speeds involved. Consequently, transportation agencies are interested in reducing the occurrence of this crash type. Many engineering treatments exist to improve safety at isolated, high-speed, signalized intersections. Intuitively, it is critical to know which safety treatments are the most effective for a given set of selection criteria at a particular intersection. Without a well-defined decision making methodology, it is difficult to decide which safety countermeasure, or set of countermeasures, is the best option. Additionally, because of the large number of possible intersection configurations, traffic volumes, and vehicle types, it would be impossible to develop a set of guidelines that could be applied to all signalized intersections. Therefore, a methodology was developed in in this paper whereby common countermeasures could be modeled and analyzed prior to being implemented in the field. Due to the dynamic and stochastic nature of the problem, the choice was made to employ microsimulation tools, such as VISSIM, to analyze the studied countermeasures. A calibrated and validated microsimulation model of a signalized intersection was used to model two common safety countermeasures. The methodology was demonstrated on a test site located just outside of Lincoln, Nebraska. The model was calibrated to the distribution of observed speeds collected at the test site. It was concluded that the methodology could be used for the preliminary analysis of safety treatments based on select safety and operational measures of effectiveness

Doctor of Philosophy

dissertationTraffic congestion is an increasing problem in most urban areas in the United States. One of the sources of this problem is the automobile-oriented development that encourages automobile use and suppresses other transportation modes. A good transit system can satisfy most of the requirements of a transportation system user. A transit system must be efficient, safe, comfortable, and competitive to private cars in order to attract more riders. Transit Signal Priority (TSP) is an operational strategy that facilitates transit vehicles at signalized intersections. It improves transit efficiency and helps transit offer travel times competitive to private cars. A lot of studies conducted in the past 40 years show the major possibilities and benefits of TSP. The goal of this research is to develop a simulation-based methodology for the evaluation and improvement of TSP strategies. The objectives consist of evaluating existing and future TSP systems, and developing field-ready algorithms that provide adaptive ways for achieving different levels of TSP and improving its operation. The focus of the research is on using traffic microsimulation to evaluate and improve TSP, but it also looks into some field-based implementations and evaluations for additional support. The analysis of different TSP strategies is performed on existing and future rapid transit mode implementations, namely Bus Rapid Transit (BRT) and Light Rail Transit (LRT). The results from the presented studies show the major benefits of TSP implementations for transit operations and small disruptions for vehicular traffic. Depending on the selected strategies and level of TSP, the travel time savings for transit can be between 10% and 30%, the reduction in intersection delay can exceed 60%, while running time reliability and headway adherence are greatly improved. These improvements in transit operations can make transit more efficient and competitive to private cars, justifying the TSP implementation. This research offers significant contributions to the state of TSP practice and research. It provides detailed insights into TSP operations, develops methods for its evaluation, and describes algorithms for achieving different levels of TSP. A significant part of the research is dedicated to the use of Software-in-the-Loop (SIL) traffic controllers in microsimulation. Through this research, SIL is proven to be a powerful tool for simulating complex traffic signal operations and TSP