Project Final Publishable Report

PROJECT FINAL PUBLISHABLE REPORT

Grant Agreement number: 300674

Project acronym: MOPED

Project title: Mobility Optimization: Permits for Emissions from Driving

Funding Scheme: FP7-MC-IIF

Period covered: From 28/03/2013to 28/03/2015

Name of the scientific representative of the project's co-ordinator[1], Title and Organisation:

Dr. Susan Grant-Muller, Senior Lecturer, University of Leeds

Tel: +44 113 343 6618

Fax:

E-mail:

Project website address: (none)

1. Executive summary

Road congestion and vehicle emissions have increasing negative impacts on society, environment and economy as a whole. A large body of evidences suggest that the current trends are not sustainable without effective travel demand management. Without new policies, all countries will have to confront a series of traffic congestion and air pollution problems caused principally by the unrestricted use of private cars. In the MOPED project, we have focused on the tradable credits scheme (TCS), researching the potential of this scheme in managing the demand for travel and reducing congestion and emissions. We have compared TCS with road pricing measures and investigated some combined measures to improve transport network mobility.

Most research to date has focused on the use of TCS to manage the related problem of air pollution, but it is clear there is potential to design a scheme for traffic congestion management. We have firstly investigated the evidence and past research on tradable credit schemes and then have focused on their role in road traffic congestion management. We have examined how the travel mode and travel pattern of travelers are influenced by a given tradable credits scheme. An analysis framework has been proposed to investigate the effects of a basic tradable credits scheme. Using a simulation analysis and case study from the Beijing municipality, we have demonstrated that a tradable credits scheme can achieve a target for reducing the expected number of car trips. The research demonstrates that a tradable credits scheme will have an effect on travelers’ mode choice. However, it is likely to have only a minor effect on the overall travel pattern in terms of OD movements.

Using a linear expenditure system (LES) approach, we have investigated the influences of a tradable credits scheme on the pattern of daily trips measured in kilometres. Generally, we assumed that an individuals’ travel consists of a car mode and a non-car mode. The effects of the tradable credits scheme were considered from a microeconomic perspective and using a scenario simulation study for the municipality of Beijing. Whilst other research has shown that travellers trade their credits and are generally inclined to non-car mode, the implementation of the tradable credits scheme demonstrated here is that travellers are likely to restrain their use of both car and non-car travel modes. Furthermore, both car and non-car mode trips are shown to be price inelastic, whilst the cross-price elasticity for different districts demonstrates a complementary relationship between car and bus modes.

We have investigated the influence of a TCS on travel demand and vehicle emissions, based on the vehicle miles travelled (VMT). With a microeconomic quantitative analysis scheme, a constant elasticity of substitution function was used to model the annual mileage for different travel purposes. An illustration is given for the effects of a TCS on emission mitigation based on historical data for Great Britain. A scenario analysis has demonstrated that a tradable credits scheme can achieve a target for reducing the number of private trips. Besides shifting private car trips to public modes, there is also evidence of individuals choosing not to take some trips. The research illustrates that a TCS could have similar effects to a road pricing scheme and that a TCS could bring emission changes arising from changes in VMT.

This project has opened many avenues for further study, created long term collaborations and a mutually beneficial cooperation between Europe and China and strengthened existing relationships. The need for innovative information and communication technologies to implement TCS in the long term should bring potential public private partnerships in support of industrial competitiveness, provide a sustainable transport development patterns, respond to the mobility needs of citizens and support transport policy development.

1. Summary of project context and objectives

The MC-IIF project, MOPED aims to establish road traffic network models to investigate alternative TCS, their impacts, advantages of different types of schemes, socio-economic implications and to develop efficient algorithms to solve the proposed models.

MOPEDhas focused on the following project context and objectives:

a)An equilibrium route choice model considering the effects of intersections

b)A single traffic bottleneck model with a TCS strategy

c)Traffic congestion and its impacts on GHG emission

d)A network traffic flow model based on TCS and algorithms design

e)A social and spatial equities analysis of the TCS based network model

f)Design of tradable credits schemes within the context of the transport network

The details of each objective are summarised below:

a)Equilibrium route choice model considering the effects of intersections

Traveler behavior is core to urban transportation system modeling, and the network equilibrium model is one of the important modelling approaches (Xu and Gao, 2009). The effect of intersections on travel costs on traffic flow patterns is obvious in urban road networks. Although these may be modeled using mesoscopic models such as Simulation and Assignment of Traffic in Urban Road Networks (SATURN, treatment of intersections in traffic assignment models is less than satisfactory. In this study, we will focus on the embedding the route choice model into a set of realistic link cost functions and implementing the model on real world networks.The exact location of the case studies to investigate this are necessarily determined by the availability of the necessary data for the case studies andthere is potential to compare differences based on travel in typical cities in different countries. Relatedcase studies for the mass-transit network of Beijing are given in Xu et al. (2010), whilst for congestion in Scotland, see Grant-Muller and Laird (2006).

Related studies have been published in “Transport Research Part A”, “Transport Research Part E”, and have been submitted to “Applied Mathematical Modelling”, “Transpormetrica B”

b)Single traffic bottleneck model with TCS strategy

We consider the commuting congestion on a highway with a single bottleneck between a residential area and a workplace, and investigate the effects of various TCSs to alleviate the queue behind the bottleneck. Since the bottleneck is finite, each commuter is confronted with a trade-off between travel cost relating to queue length and schedule delay cost of arriving early or late at work. The travel cost experienced by a commuter will be determined by his/her departure time from home and the charges within theTCS. We will assume heterogeneous commuters rationally decide their departure times over a time horizon from a residential area, based on the principle of minimizing the cost of private travel. Also we assume that different commuters have different marginal disutility parameters for their travel costs and schedule delay times, as well as a preferred work start times. Using queuing theory, we will develop a departure time choice model which leads to an equilibrium of costs for all commuters.

Related studies have been published in “Transport Reviews”, and have been submitted to “Transportation”.

c)Traffic congestion and its impacts on GHG emissions

Traffic congestion is considered here as “slow speeds caused by heavy traffic and/or narrow roadways due to construction, incidents, or too few lanes for the demand” (The 2005 Urban Mobility Report, available online at: /tamu.edu). At the practical level of measuring congestion, approaches are classed as travel time (or speed) based measures, volume based measures, area based measures and summary indices (or more complex model outputs) (Grant-Muller and Laird, 2006). In this study, we will examine GHG emissions as a function of traffic congestion. Using the velocity patterns of vehicles operating under different levels of congestion (for example, the levels of congestion can be categorized by the “level-of-service (LOS) in Highway Capacity Manual 2000”), the energy and emission impacts of traffic congestion can be estimated. For example, on a freeway, a driver typically wants to drive at relatively high speed with very few changes to their speed; however, as more and more vehicles join the flow, average traffic speed tends to be reduced and individual vehicle velocity patterns tend to exhibit fluctuating speeds. Depending on the trip pattern, GHG emissions can vary significantly. We will also illustrate this using information from existing databases.

Related studies have been published in “Transport Reviews”, “TRB annual meeting”, and have been submitted to “Transportmetrica A”.

d)A network traffic flow model based on TCS and design of algorithms

The purpose ofimplementingTCS for urban transport demand management is twofold: to limit the increase in vehicle-kilometers travelled (VKT), particularly during peak periods, and to limit atmospheric pollutant emissions from vehicles. In this study, we will construct TCSs to tackle congestion and emissions and optimize the network traffic flow patterns. The specifications include the design of the TCS distribution scheme, charging scheme, and the period of validity and payment obligations. Furthermore, the “border effects” in the TCS, for example, the management of occasional users and anticipated unforeseen behaviors which might undermine the effectiveness of the program, will also be studied. Efficient algorithms will be designed based on existing findings (Xu, Chen and Gao, 2011; Xu and Gao, 2010; Xu, Chen and Gao, 2008; Xu, Bar-Gera and Gao, 2008).

Related studies have been published in “Transport Reviews”, “TRB annual meeting”, and have been submitted to “Transportation Research Part E”, “Transportation Research Part C”.

e)Social and spatial equities analysis of the TCS based network model

The socially inequitable issues in fixed congestion pricing have often been used as an argument to justify the political unacceptability and have been debated extensively in many literatures (Yang and Huang, 2011; Thomopoulos, Grant-Muller, and Tight, 2007, 2009). We will study social equity with respect to unequivocally distributional impacts between the multiple users (for example, users from different income groups) under different TCSs. Spatial equity issues arise when the changes in generalized travel costs for drivers traveling between different OD pairs may be significantly different when TCSs are charged on some selected links. Therefore, the potential distributional impact of a TCS needs to be evaluated. We will further deal the social and spatial equities in the TCS based network model with explicit considerations of the various social groups (according to income) and the various (particularly the least well served) geographical zones. The long term research need is to generate a TCS which reduces the total travel cost and ensures there are no significant equity implications.

Related studies have been published in “Transport Policy”, “TRB annual meeting”, “International Journal of Sustainable Development & World Ecology”, “Computers & Operations Research”, and have submitted to “Case Studies on Transport Policy”.

f)The design of TCSs in a transport network

This part of the research aims to describe different types of TCSs and assess their feasibility, effectiveness and legitimacy. Attention is firstly paid to a similar system that is already in use, the so-called emission rights (e.g., European Union Emission Trading Scheme). Crucial to the project is the design of a practically implementable system that holds all qualities from the theoretical model. In this study, this theoretical model of a tradable permit system in the transport sector is elaborated, the design elements include: (1) Cap and trade: overall cap or emissions and congestion levels required by the system; (2) Trade unit: the unit to be traded based on trip or vehicle kilometers of travel; (3) Allocation aspects: different allocation types including grandfathering, auctioning, free or updating, OD based, uniform distribution; (3) Geographical distribution: scale of implementation (part area of Beijing, and typical cities in UK); (4) Target group: type of travelers covered by the trading programme to which allowances are allocated (e.g., based on VOTs); (5) Transaction costs: including the costs of establishing TCS and the transaction cost; (6) Technology: the technology details required to implement TCS; (7) Implementation path: the timetable of actual introduction of the TCS, including the period of validity; (8) Monitoring and enforcement: the level of tracking, checks, coping with occasional users, and the level of penalties with non-compliance of the system. Furthermore, the design of the TCS will accord the principles include effectiveness, economic efficiency, equity and social and political acceptability.

Related studies have been submitted to “Transportation Research Part E”, “Transportation Research Part C”, and WCTR 2016.

Main S&T results

The main S&T results are concluded as follows:

1. The role of tradable credits schemes in road traffic congestion management

Environment economists are familiar with TCSs, particularly in relation to pollution control and climate changes where they are used in practice. However it appears that researchers in transport economics view the potential of tradable credit schemes in road traffic congestion management rather more favourably than environmental economists. There are many problems and challenges yet to be resolved in using tradable credit schemes for road traffic congestion mitigation. Specific examples include the need for more detailed attention to the design of tradable credit schemes, including the definition of road links, zones, detailed times of the day, week and year with vast numbers of agents in a complex urban context, the issue of traffic leakages onto the secondary road network, monitoring and enforcement, data protection issues, public acceptability and more.

We have discussed some key issues in using tradable credit schemes for road traffic congestion management within the scope of transport economic theory, as shown in the following Table 1.

Table 1. Key points of tradable credit schemes for traffic congestion management

Design Feature / Potential approach / Remarks
Allocation of credits / How / Free of charge (e.g., uniform; OD specific, etc.); charge
Who / Eligible recipients of free credits / E.g., all taxpayers, or all qualified travellers /commuters
How many / Cap by government / The lack of enough relevant information may be an issue.
Applicability field / Regional, national
Duration of the credits / Time scale, e.g., a week, a month, a year. / There is a risk of additional trips being made to use up credits
Charging unit / Trip, VKT, or others
Monitoring and enforcement / With technologies that already exist and work
Trading / A full market or not / Potential black market for sale and purchase
Compatibility / Potential interactions with other instruments / E.g., interactions with other taxes on vehicle use, parking charges, command-and-control policies, PT instruments, physical restrictions to vehicle use, technology.
Transaction costs / See Table 3 of Grant-Muller and Xu (2014) / Transaction costs are largely dependent on system design and do not prohibit the use of tradable credits in the road transport sector with careful design.

We also review some recent research on this topic and have shown in Table 2. As a result the study promotes further understanding of these problems and indications on how to approach them.

Table 2. Studies of tradable credits for road traffic congestion management

Road traffic congestion / State-of-art studies / Remarks
Mobility management / Yang and Wang, 2011; Wang et al., 2012; Nie, 2012; Wang, Gao, Xu, 2013; He et al., 2013; Wang et al., 2014; Wu and Yin, 2012; Shirmohammadi et al., 2013; Crals, 2005; Raux, 2007; Buitelaar et al., 2007; Xu and Gao, 2011; Kalmanje and Kockelman, 2004; Kockelman and Kalmanje, 2005; Gulipalli, Kalmanje, Kockelman, 2008; Gulipalli and Kockelman, 2008; Kockelman and Lemp, 2011 / Includes:

• traffic pattern studies under different assumptions;
• Price behaviour of credits at market equilibrium under different assumptions;
• The effects of tradable credit schemes on travel behavior under different demand assumptions for mobility management

Parking management / Zhang et al., 2011 / An initial approach to tradable credits in parking management
Bottleneck management / Akamatsu, 2007; Tian et al., 2013; Nie and Yin, 2013; Nie, 2013; Xiao et al., 2013 / Based on a bottleneck model and extension

This is a novel review of tradable credit schemes (a specific type of economic measure), focused specifically on their potential for road traffic congestion management. Other approaches currently include infrastructure provision/land use measures; PT instruments; physical restrictions on vehicle use, economic instruments, technology and ICT measures. The research questions for the review were 1) whether the state-of-the-art in the literature suggests that tradable credit schemes could be feasibly introduced to mitigate congestion, and 2) whether a tradable credit scheme could have advantages over other instruments. These schemes have been used as a sophisticated incentive-based method in different fields, but are relatively new for congestion management. The discussion of tradable credit schemes within the scope of transport economic theory indicates the feasibility of using these schemes for road traffic congestion mitigation, an initial transaction cost analysis, likely impacts and potential interactions with other policy instruments. The study summarises recent literature from the perspectives of mobility management, parking management and bottleneck management. The review demonstrates that a state-of-the-art tradable credit scheme could be feasibly introduced and could have some advantages over other instruments in mitigating congestion, particularly concerning efficiency and distribution of costs and benefits.

This study has been published in “Transport Reviews”, see Grant-Muller and Xu (2014).

1. The impacts of a tradable credits scheme on urban mobility: a simulation analysis based on a linear expenditure system and application in Beijing

TCS has become familiar to environment economists as a pollution control measure. This is in contrast to the case for many transport economists and transport management practitioners, for whom it appears as new and unfamiliar approach. Despite that, researchers in transport economics can see the potential of a tradable credits scheme for road traffic mobility management, although it is clear that many theoretical and application related issues remain undeveloped. In this study, we have discussed how a tradable credits scheme affects travelers’ mode choice based on a simulation framework. This framework connects individual travel mode choice behavior and travel pattern characteristics in a regional/city traffic network, as shown in the following Figure 1.