Multi-criteria impacts assessment for ranking highway projects in Northwest Spain

This paper presents a multi-criteria model to rank highway projects by predicting their combined potential impact on regional population, economy, environment, territory and mobility. A detailed study of initial conditions enable the selection of functional units of study and the identification of homogenous units within the region, playing a relevant role into the process. Ranking is based on the achievement of both efficiency and cohesion objectives at a regional level. The model is tested by analyzing the Spanish Transport Infrastructure Master Plan (PEIT) for the non-central area of Northwest Spain. Application of impact assessment shows that the construction of infrastructures has selective effects in the area according to the homogenous groups. Potential development was boosted in one of the zone groups, whereas in others, at best, there was a reduction in their regressive tendency. Finally, the model is a dynamic support tool that could be adapted to several planning policies only when the ranking criterion is well-justified.     

Agent-based modelling for assessing hybrid and electric cars deployment policies in Luxembourg and Lorraine

Electric mobility is often presented as a way to tackle the environmental issues associated with individual mobility, provided that electric vehicles are adopted by drivers on a mass scale. In this paper, we propose an agent-based model (ABM) aiming at modelling the deployment of these vehicles. ABM is particularly indicated when modelling complex systems whose final results are the combination of the interactions between individuals and their environment and when the agents have partial information to take their decisions. We selected Luxembourg and its French neighbouring region, Lorraine, as the case study for our model, to test Luxembourg’s ambitious objective of deploying 40,000 electric vehicles by the year 2020. Model results show that the number of battery powered electric vehicles in Luxembourg (including vehicles from Lorraine’s commuters crossing the border every day) could be between 2000 and 21,000. A high number of commercial vehicles in Luxembourg, as well as an unlikely deployment in the neighbouring Belgium and Germany would therefore be required to meet the deployment objective. However, the deployment of plug-in hybrid vehicles could reach 60,000 cars by the end of 2020. To achieve this number, the deployment of charging points seems to be the more effective policy, along with actions aiming at increasing public awareness and acceptance of electric vehicles. The interest in using the ABM also lies in the identification of the main individuals’ characteristics affecting the deployment of electric vehicles (household size, commuting distances, etc.), which further support the setting of public policies.     

Methodologies to monetize the variations in load factor and GHG emissions per passenger-mile of airlines

Global GHG emissions from air travel are currently at 3% and it could increase to 15% of the total GHG emissions by 2050. To curb the growth of GHG emissions from air travel, the U.S. Federal Aviation Administration (FAA) has created a policy to achieve carbon neutral growth by 2020 relative to the 2005 baseline. If the airline industry is to both grow and meet the objectives set by this policy, new and innovative aircraft designs, operational efficiencies, and widespread use of alternate fuels are required. To accomplish this would require large research and development investment. The federal government and state governments have passed legislations that provide tax breaks and other incentives to encourage investments in new technologies. One such tax policies is cap and trade system. This had partial success in reducing GHG emissions in certain industries but was not successful in the airline industry. This paper presents alternate methods to raise capital to invest in GHG emissions reduction projects in the airline sector. The four methodologies presented here monetizes the GHG emissions resulting from differences in load factor (ratio of number of passengers to number of seats) and GHG emissions per passenger-mile among different airlines, among different flight sectors, etc. to raise the capital. Based on 2012 air travel data, these methodologies could raise more than $300 million dollars annually to invest in GHG emissions reduction projects.     

A Stated preference freight mode choice model

Transport policy aims to assist the transport system to work more efficiently and effectively. An understanding of the reasons why people choose to move freight in a certain manner is critical to the development of appropriate policies. This article outlines a data collection approach and the development of a disaggregate mode choice model applicable to the analysis of freight shipper decision making. It focuses on the choice between rail and road in Java, Indonesia. The model indicates that safety, reliability and responsiveness are major attributes influencing rail/road freight mode choice. Transport policies aimed at improving these dimensions should increase the attractiveness of rail transport.     

Agent-based model of maritime traffic in piracy-affected waters

Contemporary maritime piracy presents a significant threat to global shipping industry, with annual costs estimated at up to US$7bn. To counter the threat, policymakers, shipping operators and navy commanders need new data-driven decision-support tools that will allow them to plan and execute counter-piracy operations most effectively. So far, the provision of such tools has been limited. In cooperation with maritime domain stakeholders, we have therefore developed AgentC, a data-driven agent-based simulation model of maritime traffic that explicitly models pirate activity and piracy countermeasures. Modeling the behavior and interactions of thousands of individually simulated vessels, the model is capable of capturing the complex dynamics of the maritime transportation system threatened by maritime piracy and allows assessing the potential of a range of piracy countermeasures. We demonstrate the what-if analysis capabilities of the model on a real-world case study of designing a new transit corridor system in the Indian Ocean. The simulation results reveal that the positive past experience with the transit corridor in the narrow Gulf of Aden does not directly translate to the vast and open waters of the Indian Ocean and that additional factors have to be considered when designing corridor systems. The agent-based simulation development and calibration process used for building the presented model is general and can be used for developing simulation models of other maritime transportation phenomena.     

Protecting Estuaries and Coastal Wetlands through State Coastal Zone Management Programs

This article, one part of the National Coastal Zone Management Effectiveness Study, evaluates the effectiveness of state coastal management programs in protecting estuaries and coastal wetlands. State programs were evaluated in a four-step, indicatorbased process to estimate (1) the relative importance of the issue; (2) the potential effectiveness of programs based on the policies, processes, and tools used; (3) outcome effectiveness based on on-the-ground indicators; and (4) overall performance, where outcome effectiveness was compared to issue importance and potential effectiveness. State evaluations were synthesized to provide a national perspective on CZM contributions and effectiveness in estuary and wetland protection. Although on-the-ground outcome data were sparse, they were sufficient to determine at least probable levels of effectiveness for about one-third of the states. Of these states, 80% were performing at expected or higher levels, considering how important the issue was in their state, and the scope and strength of the policies, processes, and tools they had deployed. Monitoring and record keeping, freshwater wetland management, and the use of nonregulatory restoration in coastal management were common program weaknesses. The evaluation approach and indicators used here are recommended as a starting point for designing a national monitoring and performance evaluation system addressing this CZM objective.     

必要费率在经济船型论证和方案比选中的应用

必要费率是港口工程多方案项目经济比选方法之一。本文通过经济船型论证,介绍了必要运费率的计算过程,进而计算出综合必要费率并进行方案经济比选,从经济角度方面推荐合理的建设方案。     

Transport infrastructure costs in low-carbon pathways

The rate and manner in which transport infrastructure (e.g. roads, railway tracks, airports) is deployed, will play an important role in determining energy demand, greenhouse gas emissions and the economic impact of the transport sector. This paper describes an exercise where the costs of infrastructure deployment for the transport sector have been incorporated into the IMACLIM-R Global E3 IAM. In addition to adding these costs, the modelling of the criteria for the deployment of infrastructure for roads has also been improved. It is found that this model recalibration results in a more accurate baseline as compared to historically observed data (2001–2013) for investments in energy demand, road infrastructure, and passenger kilometers travelled. Regarding macroeconomic effects, it is found that the imposition of a carbon emission trajectory to 2100 cause GDP to decrease relative to the newly calibrated baseline – this is a standard IAM result. However, when the deployment of infrastructure for roads and air travel is further constrained, the GDP loss is less than with a fixed carbon emission trajectory only. This is because early restriction of infrastructure for roads and air travel allows an expansion of public transport infrastructure which is adequate to meet low-carbon transport service demand whereas when less public transport infrastructure is available, more costly mitigation investments must be made in other parts of the economy. This suggests that restricting infrastructure deployment as a complementary policy to carbon pricing, lowers the cost of mitigation.     

Policy measures to promote electric mobility – A global perspective

Research that addresses policy measures to increase the adoption of electric vehicles (EVs) has discussed government regulations such as California’s Zero Emission Vehicle (ZEV) or penalties on petroleum-based fuels. Relatively few articles have addressed policy measures designed to increase the adoption of EVs by incentives to influence car buyers’ voluntary behavior. This article examines the effects of such policy measures. Two of these attributes are monetary measures, two others are traffic regulations, and the other three are related to investments in charging infrastructure. Consumer preferences were assessed using a choice-based conjoint analysis on an individual basis by applying the hierarchical Bayes method. In addition, the Kano method was used to elicit consumer satisfaction. This not only enabled the identification of preferences but also why preferences were based on either features that were “must-haves” or on attributes that were not expected but were highly attractive and, thus, led to high satisfaction. The results of surveys conducted in 20 countries in 5 continents showed that the installation of a charging network on freeways is an absolute necessity. This was completely independent from the average mileage driven per day. High cash grants were appreciated as attractive; however, combinations of lower grants with charging facilities resulted in similar preference shares in market simulations for each country. The results may serve as initial guidance for policymakers and practitioners in improving their incentive programs for electric mobility.     

Empirical distributions of vehicle use and fuel efficiency across space: Implications of asymmetry for measuring policy incidence

Concerns about local air pollution and climate change have prompted all levels of government to consider a variety of policies to reduce vehicle dependence and fuel consumption, as the transportation sector is one of the largest sources of local and global emissions. Because many of the policy options under consideration are market-based (e.g., gasoline tax, carbon tax), it is important to consider how the impacts would vary across space and affect different subpopulations. Evaluating incidence is relevant for both the expected costs and benefits of a particular policy, however detailed data on vehicle-miles traveled (VMT) and fuel consumption allowing for the distributions of these variables to be estimated at a fine geographic scale is rarely available. This paper uses a unique dataset with more than 20 million vehicles in California to derive estimates of VMT and fuel consumption in order to examine the spatial distribution of impacts for an increase in the price of gasoline as well as the consequences of using different statistics for policy evaluation. Results show that VMT and fuel consumption distributions are not symmetrically distributed and vary significantly within transportation planning regions. To understand the potential implications of this asymmetry, we do a back of the envelope comparison using the mean and mode of the VMT or fuel consumption distribution for policy analysis. We find that assuming a symmetric distribution can lead to a divergence of 20–40% from the estimates based on the empirical distribution. Our results, therefore, introduce caution in interpreting the incidence of policies targeting the transportation sector based on averages.