Interplay between electricity and transport sectors – Integrating the Swiss car fleet and electricity system

Electric vehicles are seen as a future mobility option to respond to long term energy and environmental problems. The 2050 Swiss energy strategy envisages 30–75% introduction of electric cars by 2050, which is designed to support the goal of decarbonising the energy sector. While the Swiss government has decided to phase out nuclear electricity, deployment of electric cars can affect electricity supply and emission trajectories. Therefore, potential interactions between the electricity and transport sectors must be considered in assessing the future role of electric mobility. We analyse a set of scenarios using the Swiss TIMES energy system model with high temporal resolution. We generate insights into cross-sectoral trade-offs between electricity supply and electrification/decarbonisation of car fleets. E-mobility supports decarbonisation of car fleet even if electricity is supplied from large gas power plants or relatively low cost sources of imported electricity. However, domestic renewable based electricity generation is expected to be too limited to support e-mobility. Stringent abatement targets without centralised gas power plants render e-mobility less attractive, with natural gas hybrids becoming cost effective. Thus the cost effectiveness of electric mobility depends on policy decisions in the electricity sector. The substitution of fossil fuels with electricity in transport has the potential to reduce revenues from fuel taxation. Therefore it is necessary to ensure consistency between electricity sector and transport energy policies.     

Multi-criteria analysis of optimal signal plans using microscopic traffic models

Increasing concerns on environment and natural resources, coupled with increasing demand for transport, put lots of pressure for improved efficiency and performance on transport systems worldwide. New technology nowadays enables fast innovation in transport, but it is the policy for deployment and operation with a systems perspective that often determines success. Smart traffic management has played important roles for continuous development of traffic systems especially in urban areas. There is, however, still lack of effort in current traffic management and planning practice prioritizing policy goals in environment and energy. This paper presents an application of a model-based framework to quantify environmental impacts and fuel efficiency of road traffic, and to evaluate optimal signal plans with respect not only to traffic mobility performance but also other important measures for sustainability. Microscopic traffic simulator is integrated with micro-scale emission model for estimation of emissions and fuel consumption at high resolution. A stochastic optimization engine is implemented to facilitate optimal signal planning for different policy goals, including delay, stop-and-goes, fuel economy etc. In order to enhance the validity of the modeling framework, both traffic and emission models are fine-tuned using data collected in a Chinese city. In addition, two microscopic traffic models are applied, and lead to consistent results for signal optimization. Two control schemes, fixed time and vehicle actuated, are optimized while multiple performance indexes are analyzed and compared for corresponding objectives. Solutions, representing compromise between different policies, are also obtained in the case study by optimizing an integrated performance index.     

Incentivizing alternative fuel vehicles: the influence of transport policies,attitudes and perceptions

This paper aims to evaluate the influence of policies, attitudes and perceptions when incentivizing alternative fuel vehicles. The impact of possible policies such as gasoline taxes increases, purchase price subsidies, tax exemptions, and increases in fuel recharging station availability for alternative fuelled vehicles is evaluated using hybrid choice models. The models also allow assessing the sensitivity of latent variables (i.e., attitudes and perceptions) in the car purchase behaviour. The models are estimated using data from a stated choice survey collected in five Colombian cities. The latent variables are obtained from the rating of statements related to the transport system, environmental concern, vehicle preferences, and technology. The modelling approach includes regression between latent variables. Results show that environmental concern and the support for green transport policies have a positive influence on the intention to purchase alternative fuel vehicles. Meanwhile, people who reveal to be car-dependent prefer to buy standard fuelled vehicles. The analysis among cities shows similar trends in individual behaviour, although there are differences in attribute sensitivities. The policy scenario analysis revealed high sensitivity to capital cost and the need for extensive investments in refuelling stations for alternative fuel vehicles to become attractive. Nevertheless, all policies should not only be directed at infrastructure and vehicles but also be focused on user awareness and acceptance of the alternative fuel vehicles. The analysis suggests that in an environmentally conscious market, people prefer alternative fuels. However, if the transport policies support private transport, the market shares of alternative fuel vehicles will decrease.     

Multi-criteria approach for the selection of alternative options for environmentally sustainable transport system in Delhi

The present study examines the impact of including various qualitative criteria for the selection of alternative transportation options in Delhi. Three alternative transport options viz. 4-stroke 2-wheelers, CNG cars and CNG buses are prioritized based on six different criteria––energy saving potential (energy), emission reduction potential (environment), cost of operation (cost), availability of technology (technology), adaptability of the option (adaptability) and barriers to implementation (barrier). Based on quantitative criteria ‘energy’, ‘environment’ and ‘cost’, CNG car showed more potential in contributing to environmentally sustainable transport system in Delhi followed by 4-stroke 2-wheelers and CNG buses. Qualitative criteria viz. ‘technology’, ‘adaptability’ and ‘barriers’ in prioritization process resulted in higher priority for 4-stroke 2-wheelers followed by CNG bus and CNG car. Integrated quantitative and qualitative criteria gave a contrasting result as compared to that of the conventional quantitative approach and qualitative approach with highest priority for CNG bus followed by 4-stroke 2-wheelers and CNG car. This could explain the reasons for failure of many potential alternative urban transport options.     

Impacts of a multimodal mobility service on travel behavior and preferences: user insights from Munich’s first Mobility Station

The City of Munich, in cooperation with the local public transport provider MVG, is testing a pilot project of a “Mobility Station”, which is a multimodal mobility hub connecting public transport (PT) and new shared mobility services. The project’s goal is to provide sustainable mobility options that allow citizens to be mobile without owning a car. To evaluate the acceptance of the Mobility Station, as well as short and long term effects on mobility behavior, we developed an online user survey in close cooperation with the stakeholders and experts in the field of shared mobility. The results provide insights on the awareness and perception of the Mobility Station among users, their mobility patterns, current degree of multimodality, as well as actual and potential changes on mobility behavior and travel preferences due to the multimodal mobility service. Most users are young, male, and highly educated individuals with access to multiple mobility options. PT plays a central role for daily mobility together with the services they were identified to be customers of. The high share of users that use different mobility services at least once a month indicates some degree of multimodality. Actual and potential changes in mobility behavior towards multimodality were revealed. Some users declared to use other mobility services more often. They appreciate the availability of different mobility options and show interest in other services and intermodal connections indicating that there is still potential to increase multimodal behavior.     

Combining Intermodal Transport With Electric Vehicles: Towards More Sustainable Solutions

Abstract

This paper analyses the feasibility of incorporating electric or hybrid vehicles in intermodal transport for the transportation of containers in the pre- and post haulage (PPH) operation. In Europe, the intermodal transport market is being strongly supported, as it is seen as one of the keystones of a sustainable mobility system policy. The introduction of environmentally friendly electric/hybrid vehicles for the pre- and post haulage operation would mean a further enhancement leading to a more complete ecological intermodal transport chain. PPH operations are usually no longer than 30 km, and, hence, could possibly be handled by electric or hybrid vehicles.

Hybrid electric vehicles (HEV) combine electric and other drive systems, such as internal combustion engines, gas turbines and fuel cells. Hybrid electric vehicles merge the zero pollution and high efficiency benefits of electric traction with the high fuel energy density benefits of an energy source or thermal engine. The use of electrically driven vehicles for goods distribution has already been successfully proven in international demonstration projects, such as ELCIDIS. Transport of intermodal units (such as ISO containers), however, requires electric/hybrid heavy-duty goods vehicles, which are not readily available on the market, but for which the technology exists.

Different possibilities are assessed as to their technical, financial, organizational and environmental feasibility and suitability. This analysis is based on a typical mission for pre-and post haulage operations, such as type of trips, distance, frequency, urban/suburban, etc.     

The transition to zero-emission buses in public transport – The need for institutional innovation

Zero-emission buses (ZEBs) are considered a vital element in the transition to a more sustainable (urban) transport system. Both battery-electric and hydrogen fuel cell buses do however face significant barriers to large-scale implementation. These barriers, e.g. high investment costs and limited driving range, are generally regarded as exogenous technological barriers which are beyond the sphere of influence of actors in the public transport sector. In this paper we question this assumption and therefore we look at the role of institutions in public bus transport. Based on a series of interviews with stakeholders in the Dutch public transport sector we argue that various regulative, normative, and cognitive institutions discourage the use of zero-emission buses in public transport. We conclude with several suggestions for institutional innovation to increase the chances for these buses.     

Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and ‘behaviorally-realistic’ model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. More generally, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies.     

Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach

In this paper, the effects of a inter-urban carsharing program on users’ mode choice behaviour were investigated and modelled through specification, calibration and validation of different modelling approaches founded on the behavioural paradigm of the random utility theory. To this end, switching models conditional on the usually chosen transport mode, unconditional switching models and holding models were investigated and compared. The aim was threefold: (i) to analyse the feasibility of a inter-urban carsharing program; (ii) to investigate the main determinants of the choice behaviour; (iii) to compare different approaches (switching vs. holding; conditional vs. unconditional); (iv) to investigate different modelling solutions within the random utility framework (homoscedastic, heteroscedastic and cross-correlated closed-form solutions). The set of models was calibrated on a stated preferences survey carried out on users commuting within the metropolitan area of Salerno, in particular with regard to the home-to-work trips from/to Salerno (the capital city of the Salerno province) to/from the three main municipalities belonging to the metropolitan area of Salerno. All of the involved municipalities significantly interact each other, the average trip length is about 30 km a day and all are served by public transport. The proposed carsharing program was a one-way service, working alongside public transport, with the possibility of sharing the same car among different users, with free parking slots and free access to the existent restricted traffic areas. Results indicated that the inter-urban carsharing service may be a substitute of the car transport mode, but also it could be a complementary alternative to the transit system in those time periods in which the service is not guaranteed or efficient. Estimation results highlighted that the conditional switching approach is the most effective one, whereas travel monetary cost, access time to carsharing parking slots, gender, age, trip frequency, car availability and the type of trip (home-based) were the most significant attributes. Elasticity results showed that access time to the parking slots predominantly influences choice probability for bus and carpool users; change in carsharing travel costs mainly affects carpool users; change in travel costs of the usually chosen transport mode mainly affects car and carpool users.     

A novel approach for systematically calibrating transport planning model systems

Calibration of a transport planning model system is a complex process. While trial-and-error methods and modelling expertise are still the backbone of calibration of transport models, analytical approaches automating the calibration process can improve the accuracy of the models. Introducing a model to guide modellers in the calibration process of large-scale transport planning model systems is the core of this study, where a systematic model for choosing the most appropriate models and parameters is discussed. The effectiveness of the proposed model is investigated by comparing three scenarios which are built on the Travel/Activity Scheduler for Household Agents model as a large-scale agent-based model system.

     

Model aided policy development for the market penetration of natural gas vehicles in Switzerland

Introduction of alternative fuels in the passenger car fleet is widely discussed in the light of emission reductions. Worldwide experiences show that the market introduction depends on the actions of many stakeholders, like car industry, fuel companies and consumers. The process demands well-timed actions and investments, whilst economic chances and risks are distributed highly unequally. Policy makers set the framework conditions, although the influence of the height and timing of subsidies, tax reductions and other stimulation policies are not well understood yet.The market introduction of alternative fuel vehicles was studied with the example of natural gas cars in Switzerland. Stakeholder analysis and system dynamics modeling techniques were used to characterize the system. Analyses identify difficulties and chances in the market penetration process of natural gas cars. For example, a critical balance between fueling station upgrade investments and natural gas car sales is needed. Further, it is found that large time delays exist between strategic policy actions and frequently used market penetration indicators (e.g. car sales and infrastructure expansion), limiting the ability of policy makers to assess the performance of their strategy. Referring to elements of the Balanced Scorecard approach, a set of five alternative indicators is proposed to better measure the performance of the implemented strategy.     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.     

Clean energy and transport pathways for islands: A stakeholder analysis using Q method

Introducing sustainable ways to use energy and transport resources is of paramount importance for creating pathways to more liveable futures. Islands not interconnected to the main grid offer, because of their typically small size, short point-to-point travel distances that suit better than most landscapes the range limitations of today’s electromobile eco-systems. This makes them a unique test-bed that may assist researchers, businesses and policy-makers in developing a better understanding of the diverse opportunities and challenges that come with supporting electric-drive vehicle (EV) infrastructure investments that actively prioritise renewable energy sources (RES). This paper reports the findings of a Q method study that looks into the attitudes of 44 key stakeholders that have a thorough theoretical and empirical knowledge of the existing power and mobility portfolios in such islandic landscapes. Our analysis identifies and presents three distinct groups of stakeholders with different priorities and visions: the ‘Tech Enthusiasts’, the ‘Transform Transport First Supporters’ and the ‘Fiscal Focus Executives’. All our respondents agree on the need for radically transforming the current transport-energy nexus offering. They identify the importance of integrated and clean solutions and recognise that support of pilot applications is more critical than research and development (R&D). They also expect technological breakthroughs to increase market maturities and reduce renewable energy production costs and feel that end-users are still hesitant to buy EVs and need incentives to do so.     

Restricted car-use and perceived accessibility

In order to plan for, and achieve, a sustainable and accessible transport system, research and policies alike recognize a need to implement and enhance alternative transport options in favor of the private car. Moreover, these sustainable alternatives need to offer sufficient levels of accessibility regardless of where people live or work. We present and discuss an approach for capturing and evaluating perceived accessibility, with the ability to differentiate between individuals. Levels of perceived accessibility are compared before and after a fictive car use restriction, and between residential areas, using data from 2711 residents of Malmö, Sweden. A main conclusion is that levels of perceived accessibility become significantly lower for car users when they are limited in their options for daily travel. The difference is more substantive for frequent car users, who already travel less by sustainable modes today. There are also significant differences in levels of perceived accessibility in the restricted scenario, depending on where individuals live. These novel findings may not come as a surprise, but they emphasize the importance of including and analyzing perceptions of car users when designing accessible and sustainable transport systems. The paper ends with a discussion on how to facilitate the transition from current transport systems to an inclusive and accessible system.     

A new composite decision support framework for strategic and sustainable transport appraisals

This paper concerns the development of a new decision support framework for the appraisal of transport infrastructure projects. In such appraisals there will often be a need for including both conventional transport impacts as well as criteria of a more strategic and/or sustainable character. The proposed framework is based on the use of cost-benefit analysis featuring feasibility risk assessment in combination with multi-criteria decision analysis and is supported by the concept of decision conferencing. The framework is applied for a transport related case study dealing with the complex decision problem of determining the most attractive alternative for a new fixed link between Denmark and Sweden – the so-called HH-connection. Applying the framework to the case study made it possible to address the decision problem from an economic, a strategic, and a sustainable point of view simultaneously. The outcome of the case study demonstrates the decision making framework as a valuable decision support system (DSS), and it is concluded that appraisals of transport projects can be effectively supported by the use of the DSS. Finally, perspectives of the future modelling work are given.     

Accelerating the transformation to a low carbon passenger transport system: The role of car purchase taxes,feebates, road taxes and scrappage incentives in the UK

The transition to a low carbon transport world requires a host of demand and supply policies to be developed and deployed. Pricing and taxation of vehicle ownership plays a major role, as it affects purchasing behavior, overall ownership and use of vehicles. There is a lack in robust assessments of the life cycle energy and environmental effects of a number of key car pricing and taxation instruments, including graded purchase taxes, vehicle excise duties and vehicle scrappage incentives. This paper aims to fill this gap by exploring which type of vehicle taxation accelerates fuel, technology and purchasing behavioral transitions the fastest with (i) most tailpipe and life cycle greenhouse gas emissions savings, (ii) potential revenue neutrality for the Treasury and (iii) no adverse effects on car ownership and use.The UK Transport Carbon Model was developed further and used to assess long term scenarios of low carbon fiscal policies and their effects on transport demand, vehicle stock evolution, life cycle greenhouse gas emissions in the UK. The modeling results suggest that policy choice, design and timing can play crucial roles in meeting multiple policy goals. Both CO₂ grading and tightening of CO₂ limits over time are crucial in achieving the transition to low carbon mobility. Of the policy scenarios investigated here the more ambitious and complex car purchase tax and feebate policies are most effective in accelerating low carbon technology uptake, reducing life cycle greenhouse gas emissions and, if designed carefully, can avoid overburdening consumers with ever more taxation whilst ensuring revenue neutrality. Highly graduated road taxes (or VED) can also be successful in reducing emissions; but while they can provide handy revenue streams to governments that could be recycled in accompanying low carbon measures they are likely to face opposition by the driving population and car lobby groups. Scrappage schemes are found to save little carbon and may even increase emissions on a life cycle basis.The main policy implication of this work is that in order to reduce both direct and indirect greenhouse gas emissions from transport governments should focus on designing incentive schemes with strong up-front price signals that reward ‘low carbon’ and penalize ‘high carbon’. Policy instruments should also be subject to early scrutiny of the longer term impacts on government revenue and pay attention to the need for flanking policies to boost these revenues and maintain the marginal cost of driving.     

Exploring stability and change in transport systems: combining Delphi and system dynamics approaches

Transport is a vast and complex socio-technical system, and despite a clear need to reduce dependence on fossil fuels due to undesirable environmental impacts, it is largely locked into business-as-usual. Systems approaches are a useful way to help make sense of multiple competing influences which may be simultaneously driving change and supporting the status quo. This paper applies qualitative system dynamics modelling to help interpret the results of a Delphi study into global transport transitions, involving 22 international experts in various aspects of transport. The main contribution of the paper is its exploration of the use of system dynamics (SD) modelling to interpret the Delphi findings. SD modelling was used to reveal and elucidate the causal arguments put forward by the expert panel about the factors driving business-as-usual, the factors creating barriers to more sustainable transport systems, and the drivers of change. The SD model is used to explore and expose the key causal patterns at play, and how these interact to both support and hinder change. The resulting model shows the complex, interdependent dynamics involved in supporting the status quo. Even at the relatively high level of analysis reported here, the model is useful in revealing interdependencies between parts of the system, where change in one part may well have knock-on effects elsewhere in the system. In particular the model reveals the strong reinforcing loops that act to minimise the impact of change drivers and thus retain the dominance of automobility. The result is a system that is highly dependent on the continued existence of key reinforcements such as policies that subsidise fossil fuels. From a methodological perspective, the outcomes of the Delphi study provided a rich source of qualitative material which was highly suitable for developing a system dynamics model.     

Estimating the long-term effects of different passenger car technologies on energy/fuel consumption and emissions of greenhouse gases in Europe

Abstract

A stated preference (SP) experiment of car ownership was conducted in Mumbai Metropolitan Region (MMR) of Maharashtra in India. A full factorial experiment was designed to considering various attributes such as travel time, travel cost, projected household income, car loan payment and servicing cost. Data on 357 individuals were collected which resulted in 3213 observations for the calibration of the work trip and recreational trip car ownership models. The car ownership alternatives considered 0, 1 and 2 cars. A multinomial logit framework was used to develop the car ownership model taking the household as a decision unit. The specification and results of the SP car ownership model are discussed. The observed and predicted values matched reasonably when the validity of the SP car ownership model was tested against revealed preference (RP) data. The car ownership models developed in this study exhibit a satisfactory goodness of fit. It is concluded that the SP modelling approach can be successfully used for modelling car ownership decisions of households in developing countries.