Overcoming the barriers to implementing urban road user charging schemes

Urban road user charging offers the potential to achieve significant improvements in urban transport, but is notoriously difficult to implement. Cities need guidance on the range of factors to be considered in planning and implementing such schemes. This paper summarises the results of a 3 year programme which has collated evidence on the issues of most concern to cities. A state of the art report has provided evidence on 14 themes, ranging from objectives and design to implementation and evaluation. A set of 16 case studies has reviewed experience in design and implementation across Europe. The paper summarises their findings, provides references to more detailed information, presents the resulting policy recommendations to European, national and local government, and outlines the areas in which further research is needed

AN INTEGRATED SCORE-BASED TRAFFIC LAW ENFORCEMENT AND NETWORK MANAGEMENT IN CONNECTED VEHICLE ENVIRONMENT

The increasing number of traffic accidents and the associated traffic congestion have prompted the development of innovative technologies to curb such problems. This dissertation introduces a novel Score-Based Traffic Law Enforcement and Network Management System (SLEM), which leverages connected vehicle (CV) and telematics technologies. SLEM assigns a score to each driver which reflects her/his driving performance and compliance with traffic laws over a predefined period of time. The proposed system adopts a rewarding mechanism that rewards high-performance drivers and penalizes low-performance drivers who fail to obey traffic laws. The reward mechanism is in the form of a route guidance strategy that restricts low-score drivers from accessing certain roadway sections and time periods that are strategically selected in order to shift the network traffic distribution pattern from the undesirable user equilibrium (UE) pattern to the system optimal (SO) pattern. Hence, it not only incentivizes drivers to improve their driving performance, but it also provides a mechanism to manage network congestion in which high-score drivers experience less congestion and a higher level of safety at the expense of low-performing drivers. This dissertation is divided into twofold. iv First, a nationwide survey study was conducted to measure public acceptance of the SLEM system. Another survey targeted a focused group of traffic operation and safety professionals. Based on the results of these surveys, a set of logistic regression models was developed to examine the sensitivity of public acceptance to policy and behavioral variables. The results showed that about 65 percent of the public and about 60.0 percent of professionals who participated in this study support the real-world implementation of SLEM. Second, we present a modeling framework for the optimal design of SLEM’s routing strategy, which is described in the form of a score threshold for each route. Under SLEM’s routing strategy, drivers are allowed to use a particular route only if their driving scores satisfy the score threshold assigned to that route. The problem is formulated as a bi-level mathematical program in which the upper-level problem minimizes total network travel time, while the lower-level problem captures drivers’ route choice behavior under SLEM. An efficient solution methodology developed for the problem is presented. The solution methodology adopts a heuristic-based approach that determines the score thresholds that minimize the difference between the traffic distribution pattern under SLEM’s routing strategy and the SO pattern. The framework was applied to the network of the US-75 Corridor in Dallas, Texas, and a set of simulation-based experiments was conducted to evaluate the network performance given different driver populations, score class aggregation levels, recurrent and non-recurrent congestion scenarios, and driver compliance rates

Congestion Relief: Assessing the Case for Road Tolls in Canada

Experience with road pricing generally — and congestion pricing specifically — is growing around the world. Research and planning in Canada should begin now on road pricing for heavily congested highways and streets.road pricing, traffic congestion

The Critical Role of Public Charging Infrastructure

Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change

Steering urban growth: governance, policy and finance

We live in an urban age. Over half the world’s population now lives in urban areas, while the urban population is expected to reach 60% by 2030. At the same time, the importance of cities for national economic growth and climate change continues to increase. Three groups of cities will be particularly important for the global economy and climate: Emerging Cities, Global Megacities and Mature Cities. When combined, these 468 cities are projected to contribute over 60% of global GDP growth and over half of global energy-related emissions growth between 2012 and 2030 under business as usual. However, not all countries and cities will benefit from the potential economic gains of urban growth under business as usual. The winners and losers of urban expansion will depend on the policy decisions that national and sub-national governments make over the next few years. Evidence suggests that urban growth that is poorly managed by governments can lead to a range of economic, social and environmental costs, such as traffic congestion, inefficient public transport, air pollution with associated health impacts, and inadequate infrastructure for basic services such as energy, water and waste

The Use of Transferable Permits in the Transport Sector

This report focuses on the potential use of domestic transferable permit (TPs) systems in the transport sector, in order to address the issue of mobility needs management and especially the reductions of airborne pollution and greenhouse gas emissions. Firstly the context of the transport sector is briefly reviewed, the main arguments for or against the use of TPs in the sector are analysed and relevant areas are identified. Secondly four case studies of past, present or possible future permits systems are presented and evaluated. The main conclusions are: TPs applied to mobile sources are technically feasible at acceptable financial costs for protecting sensitive geographic areas. TPs schemes applied to automakers for unit vehicle emissions are also viable. Clarity, simplicity in target and pragmatism in scheme design help for their success. Regarding the broader GHG issue end-user TPs would currently involve significant administrative costs when compared with fuel tax system. Given the social resistance encountered by increase in fuel taxes in several countries, end-user TPs with free allocation may intrinsically have potential greater effectiveness and acceptance and should be thoroughly evaluated case-by-case as an alternative.Domestic transferable permits ; Emissions reduction ; Mobile sources ; Transport Sector

Optimizing Transportation Systems with Information Provision, Personalized Incentives and Driver Cooperation

Poor performance of the transportation systems has many detrimental effects such as higher travel times, increased travel costs, higher energy consumption, and greenhouse gas emissions, etc. This thesis optimizes the transportation systems by addressing the traffic congestion problem and climate change impact resulting from the inefficient operation of these systems. I first focus on the key player of the transportation systems e.g., human being/traveler, and model travelers\u27 route choice behavior with real-time information. In this study, I define looking-ahead behavior in route choice as a traveler\u27s taking into account future diversion possibilities enabled by real-time information in a network with random travel times. Subjects participated in route-choice experiments in a driving simulator as well a PC-based environment. Three types of maps in increasing levels of complexity and information availability are used. Aggregate data analysis shows that network complexity negatively affects subjects\u27 ratio of choosing the risky route given an experiment environment. Higher cognitive load in the driving simulator results in a higher level of risk aversion than in the PC-based environment for the simplest map. I specify and estimate a mixed logit model with two latent classes, looking-ahead and myopic, taking into account the panel effect. The estimated latent class membership function suggests that some subjects can look ahead while others are myopic in making their route choices, and drivers learn to look ahead over time. The experiment environment plays a role in the risk attitude of myopic subjects. A bias against information is found for subjects who look ahead, however, is not significant among myopic subjects. I then shift my focus to influencing the travel patterns of individual travelers to reduce the energy and environmental impacts of the transportation sector. I present the system optimization (SO) framework of Tripod, an integrated bi-level transportation management system aimed at maximizing energy savings of the multi-modal transportation systems. From the user\u27s perspective, Tripod is a smartphone app, accessed before performing trips. The app proposes a series of alternatives each with an amount of tokens which the user can later redeem for goods or services. The role of SO is to compute the optimized set of tokens associated to the available alternatives, in order to minimize the system-wide energy consumption, under a limited token budget. I present a method to solve this complex optimization problem and describe the system architecture, the multimodal simulation-based optimization model and the heuristic method for the on-line computation of the optimized token allocation. I then present the framework with the simulation results. Finally, I optimize the systems travel time by addressing the equity issue of congestion pricing. I propose an alternative approach to an equitable and Pareto-improving transportation systems based on cooperation among travelers assisted by defector penalty. Theoretical analysis shows the existence condition of the cooperative scheme for heterogeneous value of time (VOT) of travelers. I formulate a mathematical programming problem for the optimal cooperative scheme problem in a general network with Pareto-improving constraints and practical considerations on the length the cooperation cycle. I then conduct computational tests on a simple network and evaluate the solutions in terms of efficiency improvement (total system travel time) and equitability (Gini index)