2021

Konstantinos Gkiotsalitis (k.gkiotsalitis@utwente.nl), University of Twente

Coordinating the schedules of feeder and collector public transit lines can reduce the door-to-door travel times of passengers. With advances in smart mobility, mobility-as-a-service (MaaS) schemes allow passengers to book a combined ticket for all their trip legs. This detailed information about the origins and destinations of door-to-door trips offers the opportunity to coordinate the schedules of public transport lines to reduce the door-to-door passenger travel times. In this study, we model the coordination problem of feeder and collector lines by explicitly considering the regularity of the feeder lines and the transfer times of passengers. The coordination problem is modeled as a nonlinear non-convex problem and reformulated to an easy-to-solve convex optimization problem. We test the performance of our approach in a case study with feeder and collector lines in Singapore showing an improvement potential of 5-10% in door-to-door passenger travel times.

Virginie Boutueil, Ecole des Ponts ParisTech
Luc Nemett, Ecole des Ponts ParisTech
Thomas Quillerier, Ecole des Ponts ParisTech

Mobility systems in metropolitan areas in both the Global North and the Global South have entered an era of rapid change in the early 2010s under the influence of mobile information and communication technologies (ICTs), and ICT-based shared mobility platforms have been filling some of the gaps in transport supply left by historical modes of transport (i.e., private cars, public transit and for-hire services). Based on a worldwide systematic census of shared mobility digital platforms, this paper documents the diversity of travel modes provided by such platforms, then discusses existing classifications of shared mobility modes, and analyzes the trends in geographic expansion and competition among platforms around the world. Future research avenues in the field of shared mobility are discussed in an effort to break away from prior focus of the scientific literature on the Global North. The census brings out three original findings. The rise of shared mobility digital platforms is a worldwide phenomenon transcending the distinction between the Global North and the Global South. The metropolitan areas of large emerging countries have become clusters for innovation and competition among platforms and should be made the focus of further research. Three types of shared mobility digital platforms are identified based on geographic reach (local, regional or global). Shared mobility travel modes emerging in the Global South are identified and added to existing classifications.  Future research avenues on shared mobility are identified, e.g. as regards competition between platforms worldwide. Keywords: Shared Mobility, Digital Platforms, Classification, Worldwide Census, Geographic Patterns

Cassidy Crossland, University of Tennessee, Knoxville
Candace Brakewood, University of Tennessee, Knoxville

The introduction of the Mobility as a Service (MaaS) concept in recent years has led to trials of MaaS around the world. This concept provides bundles of transportation services which people can purchase instead of individual modes. In many areas of the United States, shared transportation modes are operated and purchased separately. The 2017 National Household Travel Survey provided responses on five shared transportation modes: bikeshare, carshare, online delivery services, rideshare, and public transit. The goal of this paper is to evaluate potential shared transportation bundles that could be marketed for MaaS in the United States. Every two, three, four, and five shared transportation bundle combinations were created to find which transportation bundles would be best suited for the models. For each transportation bundle, three binary logit models were run: one for those who live in urban areas, one for those who live in rural areas, and one nationwide. In total, 36 models were estimated and 12 models were selected for this paper. While most of the models had similar trends, such as each bundle being used by those with fewer vehicles, there were key differences between urban and rural areas for each bundle, including gender and income level. By understanding who uses which modes of transportation, MaaS plans can be marketed toward the groups most likely to use them.

Ioanna Pagoni (ipagoni@aegean.gr), University of the Aegean
Athena Tsirimpa, University of the Aegean
Ioannis Tsouros, University of the Aegean
Amalia Polydoropoulou, University of the Aegean

Mobility as a Service (MaaS) is an emerging mobility concept, in which bundled mobility products are offered by a MaaS provider to meet customers’ needs and to deliver personalized and enhanced travel experience. This paper presents an integrated approach to design and price MaaS products that address customers’ preferences while considering the MaaS provider’s decision making. This is achieved by developing a discrete choice model and a profit maximization algorithm to investigate the demand and the supply respectively. The MaaS products are designed and priced for a private MaaS provider which is assumed to act as broker in the region of Greater Manchester. Different types of products are designed to meet diversifying preferences of customers. Based on our results, the MaaS provider could earn some profits but might not achieve to maximize them. In addition, price differentiation could be a potential pricing strategy for the MaaS provider to offer the same MaaS products to people belonging in different age groups. Our analysis reveals that, in most cases, Millennials and Generation Z are willing to pay more for buying MaaS products especially if the latter include innovative mobility services such as bike- and car sharing.

Eunjeong Ko, Korea Advanced Institute of Science and Technology (KAIST)
Hyungjoo Kim, Advanced Institute of Convergence Technology
Jinwoo Lee, Korea Advanced Institute of Science and Technology (KAIST)

Shared mobility is a service that allows users to share various transportation modes and use them freely, with reservations when necessary. It started with vehicle-oriented car-sharing and ride-sharing. Currently, it operates on a wide range, including personal mobility devices such as electric bicycles and scooters. The purpose of this study is to derive a direction for providing future shared mobility services through analysis of factors affecting use of current users and prospective users. The survey targeted 753 citizens living in Gyeonggi Province, Korea. The survey period was from February 12, 2020 to February 26, 2020. In this study, usage status was analyzed and logistic regression analysis was used to build a model according to the factors affecting the use of shared mobility. The analysis results showed that gender, car ownership, and education, among variables reflecting demographic characteristics, had significant effects on intention to use shared mobility. Moreover, we found that some factors, including mainly used transportation modes, ownership of shared mobility device, past experience in similar services, satisfaction, and distance from the home to the nearest bus stop are also statistically influential. The analysis results are expected to lay the foundation for the introduction of shared mobility services and can be used as data for planning smart mobility services in the future.

Haoning Xi, University of New South Wales
Wei Liu, University of New South Wales
David Rey (d.rey@unsw.edu.au), University of New South Wales
S. Waller, University of New South Wales
Philip Kilby, DATA61

Mobility as a Service (MaaS) has recently attracted substantial attention from researchers, industry, and the public sectors. However, the concept of MaaS is still evolving. This study highlights the service nature of MaaS and proposes a system of MaaS inspired by Computing as a Service (CaaS), where travelers can buy mobility resources. In particular, we propose an incentive-compatible  auction-based online mechanism design framework to efficiently and effectively allocate mobility resources and service bundle plans. We also tailor a heuristic primal-dual online algorithm for the proposed online mechanism. We then develop an offline social welfare optimization model and quantify the social welfare loss from the online algorithm against the offline model. Moreover, we design a rolling horizon-based online algorithm (RHA) framework, which executes the offline algorithm in an online fashion to improve the social welfare obtained by online algorithms while guaranteeing polynomial computation time complexity. Numerical studies are conducted to illustrate the proposed mechanism, models, and algorithms.

Gyugeun Yoon, New York University
Srushti Rath, New York University
Joseph Chow (joseph.chow@nyu.edu), New York University
Patrick Scalise, Stantec

With advances in emerging technologies, options for operating public transit services have broadened from conventional fixed route service through semi-flexible service to on-demand microtransit. Guidelines for deciding between these services remain limited. This study provides two contributions. First, a synthesis of the key literature and recent developments to paint a picture of trade-offs between strategic planning and operational control for this range of three classes of operations. They are further expanded from isolated to multimodal operations in a Mobility-as-a-Service context, considering issues like passenger first/last mile problem, real time control, interoperability, data privacy, and institutional barriers to effective governance. The passenger first/last mile problem is formally defined. Second, an open source simulation tool is constructed that can compare state-of-the-practice methods for evaluating between the different types of public transit operations using the B63 bus route in Brooklyn, NY, as a case study. Public links to the simulation tool and data set are provided.

Lampros Yfantis (lampros.yfantis.17@ucl.ac.uk), University College London
Emmanouil Chaniotakis, University College London
Francisco Perez Dominguez, Danmarks Tekniske Universitet
Thomas Rasmussen, Danmarks Tekniske Universitet
Maria Kamargianni, University College London
Carlos Lima Azevedo, Danmarks Tekniske Universitet

Latest technological advancements and the rise of the sharing economy have led to the emergence of the Mobility as a Service (MaaS) concept. In MaaS systems, service integrators, i.e.,  MaaS Operators, integrate traditional and new mobility services and offer to users seamless travel experience through multimodal journey planning, integrated payment, booking and ticketing services. The variety of available mobility services in MaaS systems, their inherent service attribute dynamics and the different factors that MaaS users consider for their trip choices render efficient and optimal multimodal trip planning a vital problem for MaaS Operators. In contrast to existing work, in this paper, we formalize the fully dynamic, multimodal and multicriteria path set computation problem in MaaS systems considering simultaneously all the aforementioned system's particularities. Specifically, a new generalized dynamic multimodal and multi-attribute network model is proposed, which enables the realistic replication of different mobility services' structural characteristics as well as modelling a range of static and dynamic service attributes. We further propose a new dynamic and multicriteria shortest path algorithm for Pareto path set computation in MaaS systems along with heuristics that speed up the multicriteria search. We, finally, test and evaluate our modelling and algorithmic framework in a prototypical multimodal network. Initial results indicate that our approach enables the computation of diverse optimal and realistic unimodal and multimodal trips in reasonable computation time, setting the ground for further exploration into practical large-scale implementations.

Mohamed El-Agroudy, VHB
Hatem Abou-Senna, University of Central Florida
Essam Radwan, University of Central Florida

Bus transit systems have long been theorized to have the greatest potential to stimulate sustainable growth in low-density cities. However, empirical evidence continuously demonstrates that transit investment is not a magic bullet, and desirable outcomes are not guaranteed, or even likely. Mobility-as-a-Service (MaaS) presents a new approach: the digital consolidation of users, multi-modal operators, and public-private managing entities to provide totally comprehensive, integrated trip-making services. Review of the literature highlights shortcomings in traditional transportation planning by examining challenges of transit integration and weaknesses in traditional capacity analyses. To enhance the practice of multi-modal planning, the following experiment evaluates various performance measures and inter-modal interactions on I-Drive in Orlando, Florida via D and I-Optimal experimental designs in a simulated MaaS network. Alternative scenarios are developed comparing varied modal shares across five travel modes: personal vehicles, transit, ride-hailing (or rideshare), micro-mobility, and walking. The modal effects are analyzed to highlight the strengths and weakness of each mode under a variety of congestion conditions. While transit enjoys the lowest impact per person, rideshare demonstrates adverse effects across all measures. Based on the novel interactions of transit and rideshare with directional demand, strategies are outlined for optimizing rideshare-transit integration to reduce route travel-time, queuing, and overall network delay. The performance impacts of curbside facilities are also discussed for improved multi-modal integration at the street-level. These findings are applied to propose a framework for effective planning and implementation of mobility services in low density cities, focused on operations, regional connectivity, and curbside management.

Rezwana Rafiq (rrafiq@uci.edu), University of California, Irvine
Michael G McNally, University of California, Irvine

Public transit often offers less flexibility and mobility than a private car in chaining non-work activities with work due to its temporal and spatial constraints. However, it is a sustainable mode of transport that can reduce automobile dependency and can provide environmental, economic, and societal benefits. Its widespread adoption is arguably dependent on its ability to offer effective chaining of trips particularly when it is utilized in a work commute. Unfortunately, little is known about trip chaining behavior of transit commuters in the US. This study tries to reduce this gap and proposes a tour choice model for transit commuters. The model, constructed using SEM, characterizes transit commuters based on the complexity of work tours and enables to assess the impact of socio-demographic characteristics, built environment, and activity-travel variables on the likelihood of a transit commuter choosing a particular type of work tour. Based on data from the 2017 National Household Travel Survey, the study results suggest that married men with no children and high vehicle ownership living in low-density areas tend to make simple work tours., whereas non-millennial women with children are more likely to make complex work tours. Last, Caucasian millennial men of high income and high education living in denser areas are more likely to make complex tours with work-based sub-tours. The findings of this study will help transit agencies and planning organizations to identify the transit commuters who have complex travel needs, thus helping them to formulate policies ensuring better work non-work linkages.

Xiaotong Guo, Massachusetts Institute of Technology (MIT)
Hongmou Zhang (hongmou@mit.edu), Singapore-MIT Alliance for Research and Technology
Peyman Noursalehi, Massachusetts Institute of Technology (MIT)
Jinhua Zhao, Massachusetts Institute of Technology (MIT)

In mobility sharing markets, there are two conflicting principles: 1) the healthy competition between platforms, such as Uber and Lyft, and 2) economies of network scale, which leads to higher chances for trips to be matched, and thus higher efficiency. The status quo mobility sharing markets are either monopolistic or largely segmented with significant efficiency loss. In this paper, we first introduce a unified theoretical framework to describe the structure of shared mobility market, and then use it to propose four market structure designs to dissolve the market segmentation to different extents. Using a formal analysis framework, we analyze the following aspects of the two status quo and four proposed market structures: demand and supply information collection, service delivery and payment flow. For each proposed market, detailed mechanisms are introduced and feasibility for market realization is also discussed.