2018

Federico Librino, Istituto di Informatica e Telematica del CNR
Maria Elena Renda, Massachusetts Institute of Technology (MIT)
Giovanni Resta, Istituto di Informatica e Telematica del CNR
Paolo Santi, Massachusetts Institute of Technology (MIT)
Fabio Duarte, Massachusetts Institute of Technology (MIT)
Carlo Ratti, Massachusetts Institute of Technology (MIT)
Jinhua Zhao, Massachusetts Institute of Technology (MIT)

Shared mobility is widely recognized for its contribution in reducing carbon footprint, traffic congestion, parking needs and transportation-related costs in urban and suburban areas. In this context, the use of carpooling in home-work commute is particularly appealing for its potential of lessening the number of cars and kilometers traveled, consequently reducing major causes of traffic in cities. Accordingly, most of the carpooling algorithms are optimized for reducing total travel time, cost, and other transportation-related metrics. In this paper, we analyze the benefits of carpooling from a new angle, posing it as a possible means for favoring social integration in the city by matching carpoolers taking into account some of their social characteristics. Building upon a recently introduced network-based approach to model ride-sharing opportunities, we define two social-related carpooling problems: how to maximize the number of rides shared between people belonging to different social groups, and how to maximize the amount of time people spend together along the ride. For each of the problems, we provide corresponding optimal and computationally efficient solutions. We then demonstrate our approach on two data sets collected in the city of Pisa, Italy, and Cambridge, US, and quantify the potential social benefits of carpooling, and how they can be traded off with traditional transportation-related metrics. When collectively considered, the models, algorithms, and results presented in this paper broaden the perspective from which carpooling problems are typically analyzed to encompass multiple disciplines including urban planning, public policy, and social sciences.

Bruce Appleyard, San Diego State University
William Riggs, University of San Francisco

From the beginning of modern planning, graphic images and concept diagrams have been used to convey ideas and frame approaches. This paper develops a conceptual performance measure framework for integrating transportation and land use policy and planning with regard to driverless cars or autonomous vehicles (AVs). Building on seminal work on evaluating transit performance, this model places a premium on service effectiveness and street livability “doing the right things”, over service efficiency, “doing things right”, which can be achieved most sustainably through fewer cars, traveling at slower speeds, and over shorter trips. This paper outlines how this model might apply to certain street transects and what that means for specific urban policies with a goal of achieving sustainability, livability, and equity in future cities.

Based on an optimal scenario, this paper provides specific policy recommendations and a list of candidate performance measures that can be used with this conceptual framework to help guide us toward transportation and land use integration policies and approaches for a future with driverless cars that is more livable, sustainable, and equitable.

Wei-Shiuen Ng, International Transport Forum

Cities are growing differently across the world, even within the same region, and presenting different transportation trends and challenges. Existing transportation services and travel behavior are some of the key variables shaping future transportation trends and carbon emissions projections. This study uses five developing cities in Southeast Asia to illustrate how different policy scenarios can help cities achieve more sustainable transportation development. Cities in Southeast Asia encompass distinctive characteristics, such as the wide range of transportation alternatives, often in the form of informal transit, and although they are not growing as rapidly as Chinese or Indian cities, their levels of transportation emissions have been increasing consistently. This study examines how different policies and measures will affect transportation mode choice and carbon emissions through the construction of mode choice models and the application of three policy scenarios. Carbon emissions can be reduced by as much as 93 percent in 2050 if cities implement a combination of land use planning changes, public transportation development and economic policies for a modal shift to more energy efficient mode choices. Such policies and measures will therefore be able to contribute to city level climate goals or national climate targets.

Louise Reardon, University of Birmingham
Greg Marsden, University of Leeds

Climate change has long been identified as a ‘wicked problem’. It has been argued that such ‘wicked’ problems require a move away from ‘command and control’ linear policy thinking where the problem is broken down into components, to instead a ‘whole systems approach’ which embraces non-linear and organic thinking…where the primacy of the whole is acknowledged. The argument of this paper is that to date the UK has failed to address the climate change challenge in the transport sector due to its siloed linear, command and control policy approach, which has focused on the supply-side of the climate change challenge at the expense of the demand side. The UK’s approach has primarily focused on decarbonisation of the vehicle fleet without addressing more fundamental questions about how much mobility there is, how this mobility is generated, and how much mobility should be catered for (the demand side). The demand side is however crucial, as the scale of the decarbonisation challenge, and in turn the impact on climate change, is bounded by the level of demand and how it is configured. We identify the need instead, for a whole systems approach to thinking about climate change and mobility, which highlights the need for a more nuanced policy approach, through two UK based case studies; liberalisation of air travel, and concessionary bus travel. The case studies highlight the importance of government actions in shaping aspects of demand and, through examination of how these policies unfold over time, the recursive relationship between the promotion of demand and the increased challenge of managing it – and supplying for it.

Marie-Eve Will, Technical University of Denmark
Yannick Cornet, University of Zilina
Talat Munshi, Technical University of Denmark

The space needed by various urban passenger transport modes varies greatly depending on the size and the speed of vehicles. Available studies on this topic have shown that public transport and non-motorized transport can be up to 20 times more space-efficient than the typical car. This is particularly relevant in urban context where space is a constrained resource. Yet space use is rarely assessed explicitly in the transport planning practice, the connection between the low carbon transport planning agenda , and there exists no standard method for quantifying the use of space in complex urban settings like that of developing cities. This study builds on the space-time concept to propose a method for quantifying and comparing the circulation space, parking space and ecological space between modes. The method is showcased by evaluating a Low-carbon Comprehensive Mobility Plan (LCMP) scenarios against a business-as-usual (BAU) scenario in the city of Rajkot, India. Based on a multi-modal transport model elaborated for the design of the LCMP, the indicator assesses the overall space-time used by each mode category, both for parking and travelling. The indicator shows that significantly less space is used by transport in the LCMP than in the BAU scenario, which provides evidence that could contribute to alleviating chronic congestion expected from a car- and motorcycle-based transport development only. This research participates in creating an assessment framework for low carbon transport development that would include spatial efficiency concerns.

Guineng Chen, Organisation for Economic Co-operation and Development (OECD)
Vincent Benezech, International Transport Forum

This study aims to present long-term scenarios on domestic non-urban passenger mobility and related CO₂ emissions up to 2050 at the global level. It uses a new model developed at the International Transport Forum’s (ITF). Results from the baseline scenario show that, between 2015 and 2050, non-urban travel demand may nearly triple by 2050, with CO₂ emissions from the sector doubling. The mode share of private cars will continue to increase, contributing to more than 70% of the total CO₂ emission from the sector. We also introduce a low-carbon scenario, aiming at reducing the carbon-intensity of travel through fuel efficiency improvements, increased use of alternative fuel and incentives for mode shift. The results show the significant impact such measures can have in addressing the expected growth in emissions. They also highlight the preponderant role of vehicle technology as a mitigation measure, even though improving rail and bus services is also needed to further reduce the carbon footprint of non-urban mobility.

Tolga Ercan, Connected Wise LLC
Nowreen Keya, University of Central Florida
Nuri Cihat Onat, Istanbul Sehir University
Omer Tatari, University of Central Florida
Naveen Eluru, University of Central Florida

Heavy dependence on personal vehicle usage in the U.S. has made the transportation sector one of the greatest contributors to air pollutant emissions the associated human health concerns. The transportation mode choices of urban commuters play a key role in the evaluation and management of these threats. This study investigates the impacts of autonomous vehicles (AVs) on transportation mode choice and on applicable trends in transportation-related externalities, carbon emissions, and air pollution for the year 2050. To this end, in addition to testing various market penetration scenarios for AVs, this study will analyze common policy applications such as limiting lane-mile increases on roadways (i.e. limiting the expansion projects) and introducing carbon-tax policies to vehicle owners from the year 2025 onward. Demographic parameters and five transportation mode choices for 929 metro/micropolitan areas of the U.S. are processed in simulations of a fractional split multinomial model. A system dynamics modeling approach is integrated in this study with discrete-event model outcomes as part of a novel hybrid simulation model. The results show that policies such as line-mile increases and carbon taxes have a negligible reduction effect on transportation-related sustainability impacts. On the other hand, the introduction of AVs into the U.S. transportation has significant potential to reduce annual CO₂ emissions compared to any combination of lane-mile and carbon-tax policy scenarios by the year 2050.

Ji Luo, University of California, Riverside
Kanok Boriboonsomsin, University of California, Riverside
Matthew Barth, University of California, Riverside

Active transportation modes such as walking and biking are key elements of sustainable transportation. In order to promote bicycling as an alternative form of transportation, a holistic approach to improving the quality of the biking experience is needed. In most areas, bicycle routes are a subset of vehicle routes where often new bicycle infrastructure is created by adding bicycle lane(s) to existing rights-of-way. The planning of bicycle routes typically takes into consideration available right-of-way, existing roadway infrastructure, vehicular traffic volume, safety concerns, and the built environment, among other things. Exposure to traffic-related air pollution, on the other hand, is rarely considered. Indeed, bicyclists are the most vulnerable to the harmful air pollution due to their direct exposure to vehicular exhaust and increased breathing rate during biking.

This paper presents a method for incorporating exposure to traffic-related air pollution as another consideration in the bicycle route planning process. The method involves creating a streamlined process for estimating the level of near-road air pollution concentration and developing a bicycle route planning tool that allows planners and engineers to compare the exposure of bicyclists to traffic-related air pollution among different bicycle route options. In addition, this paper demonstrates how to apply the method in two case studies in the City of Riverside, California. Through these case studies, it is shown that considering exposure to traffic-related air pollution can change the outcome of bicycle route planning.

Uri Avin, National Center for Smart Growth
Alice Grossman, American Association for the Advancement of Science
Alexander Bond, Office of the Secretary of Transportation (OST)
Sheldon Edner, George Mason University
Rich Denbow, Cambridge Systematics
Kimberly Fisher, National Center for Smart Growth
Derek Lombardi, Delaware Valley Regional Planning Commission

The HUD funding of the Sustainable Communities Initiative (SCI), between 2010 and 2012, awarded over $165 million to 74 applicants to pursue sustainability planning in new ways at the regional scale. The SCI grants were the first Federal dedicated comprehensive planning discretionary grant program since the 1960s. By design, the program sought to broaden the typical stakeholders in such efforts – MPOs and Councils of Government – so as to include NGOs and others. The program also sought to broaden the typical highway-centric agendas of such efforts by emphasizing equity, housing, and environmental quality and relating these issues to multimodal transportation. These interdisciplinary and collaborative requirements for the program’s competitive Regional Planning grants, ranging from $225,000 to $ 5,000,000, ushered in a new wave of Regional Sustainable Development Plans. In 2010, 45 awards were made to regional entities. Their work was completed by the end of 2013 and it is the focus of this paper. This study is the first to assess the transportation planning impacts of the trailblazing Federal Sustainable Communities Initiative (SCI). This project aims to answer the question of if and how the SCI program has transformed metropolitan transportation planning. Answering this question helps policy makers and practitioners shape practical outcomes in the transportation planning field, such as the way in which Long Range Transportation Plans (LRTPs) and Transportation Improvement Programs (TIPs) are developed.

Ioannis Tsouros, University of the Aegean
Amalia Polydoropoulou, University of the Aegean

The transport sector is accountable for almost one fourth of the global carbon emissions. Without bold, persistent and diverse mitigation measures, emissions from transportation are going to increase at a faster rate and remain a threat to the environment and humanity. Sustainable transportation is an answer for this threat. This paper is concerned with the concept, design, and implementation of an interactive sustainable transport evaluation tool. The development of the final product, the green transport policy platform, should assist policy-makers and urban planners to evaluate green policy measures in a more thorough and sophisticated way. The platform is tested and put into practice in real-life situation and scenario in the Greek island of Chios. The platform runs on a series of econometric models which are divided into three different tiers. Initially, the everyday life tier, which models departure and arrival times and tour structure based on the latent trait of location specific lifestyle; the active transport measures assessment tier, which uses a five-module transport simulation model to assess the impact of active transport promotion measures and a hybrid choice model which measures the future vehicle purchase choices concerning alternative fuel vehicles and the effect of latent variables such as the symbolic use of vehicles or the positive stance towards the environment on the choice.

Maria Fernanda Viveros, Universidad de Concepcion
Juan Carrasco, Universidad de Concepcion
Alejandro Tudela, Universidad de Concepcion

The relationship between well-being and transport has been mainly discussed in theoretical and qualitative terms. The objective of this paper is to provide empirical evidence through a quantitative analysis of people’s well-being, measured by subjective well-being, and the transport disadvantage, considering mobility variables and self-reported access limitations or barriers.

 

Using data collected from 241 people from four neighborhoods in Concepción, Chile, structural equation models were estimated, showing the existence of relationships between the generated variables and well-being was empirically demonstrated. The analysis included as key dimensions not only the people’s travel behavior, but also their knowledge and experience in non- mandatory activities, as well as their satisfaction with life as a cognitive component of wellbeing. The analyses from the models suggest that access barriers to non-mandatory activities had almost no direct correlation with the different components of wellbeing, with the exception of transport and activity costs, but only for low-income people. This result reinforces previous findings in the literature regarding the importance of social exclusion as a mediating variable between the relationship of transportation disadvantage and well-being.

Kathrin Kuehne, Leibniz University, Hannover
Suman Mitra, University of California, Irvine
Jean-Daniel Saphores, Institution of Transportation Studies

One approach to making transportation more sustainable is to transition away from a car-oriented society. Unfortunately, our understanding of the factors that prompt households to voluntarily forgo their motor vehicles is limited. The 2008 Mobility in Germany (MiD) and the 2012 California Household Travel Survey (CHTS) provide an opportunity to start filling this gap. We estimate Generalized Structural Equation Models (GSEM) to tease out what built environment and socio-economic variables impact the likelihood that a household is carless (voluntarily or not) in Germany and in California. Our results show that in both Germany and California, households who reside in denser neighborhoods, closer to transit stations, who have a lower income or fewer children, are more likely to be voluntarily carless than to be motorized. However, households with more education are more likely to be voluntarily carless in Germany, whereas the reverse is true in California. Moreover, employment density and public transit have a higher impact on voluntary carlessness in Germany than in California. Our results also show that different socio-economic groups have substantially different residential location preferences in Germany and in California. These differences may be explained by cultural preferences, historical differences in land use and transportation policies, and by the higher cost of owning a motor vehicle in Germany.

Dick Ettema, Universiteit Utrecht
Zidan Mao

Face-to-face interactions with social contacts are important for individuals’ well-being. Car use facilitates integration of social interactions in workers’ daily activity patterns, but is discouraged in order to reduce congestion and environmental damage. Against this background, this paper intends to investigate how individuals’ modality styles affect commuters’ face-to-face interaction with their family members, friends and colleagues. One week diary data collected in Beijing is used for the analysis, which shows that commuters spend more time on solo activities or with colleagues out-of-base on commute days, while they spend more time with family members and friends on the non-commute days. Multivariate Tobit regression models of joint activity time show that the interactions with friends are positively correlated with the interactions with family members and also with colleagues on the commute days, while no significant relation is found among the interactions on non-commute days. Social interaction with different companions and also solo activities are significantly constrained by the work duration. On commute days, solo activities and interactions with colleagues are less influenced by modality styles, although monomodal car users have more interaction with family members and friends than other modality groups. However, this advantage disappears on the non-commute days. With less time constraints imposed by work and commuting, multimodal travelers have more interaction out-of-base with family members and friends.

Gordon Bauer, University of California, Berkeley
Jeffery Greenblatt, Lawrence Berkeley National Laboratory
Brian Gerke, Lawrence Berkeley National Laboratory

Shared automated electric vehicles (SAEVs) hold great promise to improve inner-city accessibility while drastically reducing greenhouse gas emissions from transportation. Using taxi trip data from New York City, we develop an agent-based model to predict the requirements of a fleet of SAEVs operating on Manhattan Island with respect to both the distribution of charging stations and battery range. We also develop a cost model to estimate the cost per mile of providing service, and employ extensive sensitivity analysis to test the robustness of our predictions. We estimate that costs will be lowest with a battery range of 70-120 miles, and 2,500-3,000 Level 2 charging stations spread across 300-500 locations. We estimate that the cost of service provided by such an SAEV fleet will be $0.37-$0.54/mi—an order of magnitude lower than that of present-day Manhattan taxis, and also lower than a fleet composed of any currently available hybrid or internal combustion engine vehicle (ICEV). Such a fleet would reduce emissions by 67% over a fleet of ICEVs, and by 44% over a fleet of hybrid vehicles. These results suggest that electric vehicles can provide the lowest-cost service, and that the largest barrier to operating such a fleet will not be battery range, for which currently available electric vehicle models more than suffice, but the abundance of charging stations.