Combining Tradable Credit Schemes with a New Form of Road Pricing: Producing Liveable Cities and Meeting Decarbonisation Goals

This paper considers how the implementation of a tradable credit scheme (TCS) may be used to reduce road traffic and to contribute to the formation of liveable cities and global climate change commitments. The concept of applying TCS to individual road transport is familiar to transport researchers as a measure to regulate congestion and reduce transport-related emissions. Yet, it is not a strategy currently being considered by policy makers in the UK, despite the electrification of the road vehicle fleet and the associated loss of tax revenue presenting a rare opportunity to alter the economic instruments, which apply to road traffic. We consider how transport researchers can capitalise on this unique moment in transport history to shape transport policy. Our study uses qualitative methods, including a thematic analysis of semi-structured interviews with transport stakeholders and experts, in addition to a literature review and document analysis. Data analysis is inductive, permitting the formation of new ideas about the potential benefits of TCS and the barriers to the application of TCS to real-world policy. Building upon the results of TCS experiments and the results of our analysis, we propose a novel potential form of TCS combined with road pricing to maintain government revenue, which incentivises road users to decrease road vehicle kilometres travelled and reduce pollution and congestion. The proposal contributes to the discussion on the governance of road transport and taxation

Bridging the user equilibrium and the system optimum in static traffic assignment: a review

Solving the road congestion problem is one of the most pressing issues in modern cities since it causes time wasting, pollution, higher industrial costs and huge road maintenance costs. Advances in ITS technologies and the advent of autonomous vehicles are changing mobility dramatically. They enable the implementation of a coordination mechanism, called coordinated traffic assignment, among the sat-nav devices aiming at assigning paths to drivers to eliminate congestion and to reduce the total travel time in traffic networks. Among possible congestion avoidance methods, coordinated traffic assignment is a valuable choice since it does not involve huge investments to expand the road network. Traffic assignments are traditionally devoted to two main perspectives on which the well-known Wardropian principles are inspired: the user equilibrium and the system optimum. User equilibrium is a user-driven traffic assignment in which each user chooses the most convenient path selfishly. It guarantees that fairness among users is respected since, when the equilibrium is reached, all users sharing the same origin and destination will experience the same travel time. The main drawback in a user equilibrium is that the system total travel time is not minimized and, hence, the so-called Price of Anarchy is paid. On the other hand, the system optimum is an efficient system-wide traffic assignment in which drivers are routed on the network in such a way the total travel time is minimized, but users might experience travel times that are higher than the other users travelling from the same origin to the same destination, affecting the compliance. Thus, drawbacks in implementing one of the two assignments can be overcome by hybridizing the two approaches, aiming at bridging users’ fairness to system-wide efficiency. In the last decades, a significant number of attempts have been done to bridge fairness among users and system efficiency in traffic assignments. The survey reviews the state-of-the-art of these trade-off approaches

If, At First, The Idea is Not Absurd, Then There is No Hope For It: Towards 15 MtC in the UK Transport Sector.

This paper examines the possibilities of reducing transport carbon dioxide emissions in the UK by 60 per cent by 2030 using a modified scenario building and backcasting approach. It examines a range of policy measures (behavioural and technological), assessing how they can be effectively combined to achieve the required level of emissions reduction. The intention is to evaluate whether such an ambitious target is feasible, identify the main problems (including the transition costs), and the main decision points over the 30-year time horizon. This paper outlines the first stages of the research, providing: An introduction to futures studies, including a review of forecasting, scenario building and backcasting approaches; An assessment of the UK transport sector's contribution to climate change and global warming, and; Setting targets for 2030, forecasting the business as usual situation for all forms of transport in the UK, and assessing the scale of change in terms of achieving the emissions reductions. The benefits of scenario building and backcasting are that innovative packages of policy measures can be developed to address emissions reduction targets. It allows trend-breaking analysis, by highlighting the policy and planning choices to be made by identifying those key stakeholders that should be included in the process, and by making an assessment of the main decision points that have to be made (the step changes). It also provides a longer-term background against which more detailed analysis can take place.

Integrating Pro-Environmental Behavior with Transportation Network Modeling: User and System Level Strategies, Implementation, and Evaluation

Personal transport is a leading contributor to fossil fuel consumption and greenhouse (GHG) emissions in the U.S. The U.S. Energy Information Administration (EIA) reports that light-duty vehicles (LDV) are responsible for 61\% of all transportation related energy consumption in 2012, which is equivalent to 8.4 million barrels of oil (fossil fuel) per day. The carbon content in fossil fuels is the primary source of GHG emissions that links to the challenge associated with climate change. Evidently, it is high time to develop actionable and innovative strategies to reduce fuel consumption and GHG emissions from the road transportation networks. This dissertation integrates the broader goal of minimizing energy and emissions into the transportation planning process using novel systems modeling approaches. This research aims to find, investigate, and evaluate strategies that minimize carbon-based fuel consumption and emissions for a transportation network. We propose user and system level strategies that can influence travel decisions and can reinforce pro-environmental attitudes of road users. Further, we develop strategies that system operators can implement to optimize traffic operations with emissions minimization goal. To complete the framework we develop an integrated traffic-emissions (EPA-MOVES) simulation framework that can assess the effectiveness of the strategies with computational efficiency and reasonable accuracy. ^ The dissertation begins with exploring the trade-off between emissions and travel time in context of daily travel decisions and its heterogeneous nature. Data are collected from a web-based survey and the trade-off values indicating the average additional travel minutes a person is willing to consider for reducing a lb. of GHG emissions are estimated from random parameter models. Results indicate that different trade-off values for male and female groups. Further, participants from high-income households are found to have higher trade-off values compared with other groups. Next, we propose personal mobility carbon allowance (PMCA) scheme to reduce emissions from personal travel. PMCA is a market-based scheme that allocates carbon credits to users at no cost based on the emissions reduction goal of the system. Users can spend carbon credits for travel and a market place exists where users can buy or sell credits. This dissertation addresses two primary dimensions: the change in travel behavior of the users and the impact at network level in terms of travel time and emissions when PMCA is implemented. To understand this process, a real-time experimental game tool is developed where players are asked to make travel decisions within the carbon budget set by PMCA and they are allowed to trade carbon credits in a market modeled as a double auction game. Random parameter models are estimated to examine the impact of PMCA on short-term travel decisions. Further, to assess the impact at system level, a multi-class dynamic user equilibrium model is formulated that captures the travel behavior under PMCA scheme. The equivalent variational inequality problem is solved using projection method. Results indicate that PMCA scheme is able to reduce GHG emissions from transportation networks. Individuals with high value of travel time (VOTT) are less sensitive to PMCA scheme in context of work trips. High and medium income users are more likely to have non-work trips with lower carbon cost (higher travel time) to save carbon credits for work trips. ^ Next, we focus on the strategies from the perspectives of system operators in transportation networks. Learning based signal control schemes are developed that can reduce emissions from signalized urban networks. The algorithms are implemented and tested in VISSIM micro simulator. Finally, an integrated emissions-traffic simulator framework is outlined that can be used to evaluate the effectiveness of the strategies. The integrated framework uses MOVES2010b as the emissions simulator. To estimate the emissions efficiently we propose a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the link driving schedules for MOVES2010b. Test results using the data from a five-intersection corridor show that HC-DTW technique can significantly reduce emissions estimation time without compromising the accuracy. The benefits are found to be most significant when the level of congestion variation is high. ^ In addition to finding novel strategies for reducing emissions from transportation networks, this dissertation has broader impacts on behavior based energy policy design and transportation network modeling research. The trade-off values can be a useful indicator to identify which policies are most effective to reinforce pro-environmental travel choices. For instance, the model can estimate the distribution of trade-off between emissions and travel time, and provide insights on the effectiveness of policies for New York City if we are able to collect data to construct a representative sample. The probability of route choice decisions vary across population groups and trip contexts. The probability as a function of travel and demographic attributes can be used as behavior rules for agents in an agent-based traffic simulation. Finally, the dynamic user equilibrium based network model provides a general framework for energy policies such carbon tax, tradable permit, and emissions credits system

CARMA: Fair and efficient bottleneck congestion management via non-tradable karma credits

This paper proposes a non-monetary traffic demand management scheme, named CARMA, as a fair solution to the morning commute congestion. We consider heterogeneous commuters traveling through a single bottleneck that differ in both the desired arrival time and Value of Time (VOT). We consider a generalized notion of VOT by allowing it to vary dynamically on each day (e.g., according to trip purpose and urgency), rather than being a static characteristic of each individual. In our CARMA scheme, the bottleneck is divided into a fast lane that is kept in free flow and a slow lane that is subject to congestion. We introduce a non-tradable mobility credit, named karma, that is used by commuters to bid for access to the fast lane. Commuters who get outbid or do not participate in the CARMA scheme instead use the slow lane. At the end of each day, karma collected from the bidders is redistributed, and the process repeats day by day. We model the collective commuter behaviors under CARMA as a Dynamic Population Game (DPG), in which a Stationary Nash Equilibrium (SNE) is guaranteed to exist. Unlike existing monetary schemes, CARMA is demonstrated, both analytically and numerically, to achieve a) an equitable traffic assignment with respect to heterogeneous income classes and b) a strong Pareto improvement in the long-term average travel disutility with respect to no policy intervention. With extensive numerical analysis, we show that CARMA is able to retain the same congestion reduction as an optimal monetary tolling scheme under uniform karma redistribution and even outperform tolling under a well-designed redistribution scheme. We also highlight the privacy-preserving feature of CARMA, i.e., its ability to tailor to the private preferences of commuters without centrally collecting the information

Can personal gasoline permit trading be effective? An investigation into permit demand

© 2016 Elsevier Ltd This study proposes a personal gasoline permit trading scheme to limit the total gasoline consumption, thus reducing its environmental impact. We studied the effectiveness of this scheme by analyzing the permit demand of a gasoline-driven vehicle in transportation sector. A general utility optimization model is formulated and a Cobb-Douglas utility function is further assumed to analyze the response of permit demand to its price changes with the Slutsky decomposition of price effects. The results, when defined in economic terms, indicate that the permit demand of consumers in higher income groups are negatively related to permit price; permit demand are also negatively related to permit price for consumers in medium income groups, but with positive income effect; and the direct relationship between permit demand of lower income groups and the price is defined as a Giffen-good effect. That is, for those low income groups, when the permit price rises their demand for permits would also increase. Then US and Singapore household expenditure data are used to show comparable results of a pilot personal gasoline permit trading scheme. Further, some regulations on critical parameters, such as permit allocation and permit prices in the policy design are proposed to make the scheme feasible in different income groups. Based on these results, implications, limitation and suggestions for future study are discussed

The inclusion of International Aviation in the European Union Emissions Trading System

BibliografiaThe aim of this project is to recognize which economic consequences could have for the European airline operators being subject under the Cap-and-Trade System where CO2 emissions are traded as allowances.El treball establert proposa entendre quins son els efectes de la inclusió de l'aviació internacional dins el sistema europeu ETS. Concretament, es pretén analitzar com podria repercutir en termes econòmics el fet de tractar les emissions de CO2 procedents de l'aviació com a drets d'emissió subjectes al sistema Cap-and-Trade.El trabajo establecido propone entender los efectos de la inclusión de la aviación internacional dentro del sistema europeo ETS. Concretamente, se pretende analizar como podría repercutir en términos económicos el hecho de tratar las emisiones de CO2 procedentes de la aviación como derechos de emisión sujetos al sistema Cap-and- Trade

Taking the low-carbon road: Essays in road transport decarbonization

In this dissertation, I methodically analyze proposed EU policies that fast-track deployment of low-emission transport technologies and decrease the emissions intensity of road transport. I limit the scope of my analysis to light passenger transport and heavy road freight. As instruments for this analysis, I design theoretical models to depict the mechanisms underlying supply and demand and then calibrate the models to illustrate the relative costs of each policy scenario. The main contributions of this dissertation are three- fold. First, it investigates the importance of endogenous technical progress in existing and nascent technologies for achieving a cost-competitive low-emission transport system. Second, it examines the value of policy coordination amongst EU member states by scrutinizing incongruous national emissions targets. Third, it studies the impact of levying a distance tax that covers the external costs of road transport