Abstract

The transport sector is witnessing unprecedented levels of disruption. Privately owned cars that operate on internal combustion engines have been the dominant modes of passenger transport for much of the last century. However, recent advances in transport technologies and services, such as the development of autonomous vehicles, the emergence of shared mobility services, and the commercialization of alternative fuel vehicle technologies, promise to revolutionise how humans travel. The implications are profound: some have predicted the end of private car dependent Western societies, others have portended greater suburbanization than has ever been observed before. If transport systems are to fulfil current and future needs of different subpopulations, and satisfy short and long-term societal objectives, it is imperative that we comprehend the many factors that shape individual behaviour. This chapter introduces the technologies and services most likely to disrupt prevailing practices in the transport sector. We review past studies that have examined current and future demand for these new technologies and services, and their likely short and long-term impacts on extant mobility patterns. We conclude with a summary of what these new technologies and services might mean for the future of mobility.

Abstract

Shared mobility—the shared use of a vehicle, bicycle, or other mode—is an innovative transportation strategy that enables users to gain short-term access to transportation modes on an “as-needed” basis. Shared mobility includes various forms of carsharing, bikesharing, ridesharing, on-demand ride services, and microtransit. Additionally, smartphone and mobile “apps” aggregate and optimize these mobility services and are critical to many shared mobility modes. Courier network services connect couriers using their personal vehicles or bicycles with freight and seek to disrupt the existing package and food delivery industry. The emergence of automated vehicles into shared mobility could further transform the passenger and freight transportation system, with greater emphasis on shared mobility. This chapter describes the different models that have emerged in the shared mobility space and reviews research that has quantified the environmental, social, and transportation-related impacts of these services. The authors also project future trends as automated vehicles begin to emerge.

Abstract

The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportation’s MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment.

Abstract

This report explored the key barriers to the provision of thesesharing economy mobility services to highlight the actions thatcan be taken by policy makers and other organisations tosupport their availability. The study involved two stages: aliterature review investigating the current state of knowledgeboth domestically and internationally; and in-depth interviewswith experts from organisations such as service providers,lobby groups and policymakers. The objective was to learntheir perceptions on shared mobility service provision barriersand expected developments on increasing the use of sharedmobility services.The analysis found that the Australia cities have similar sharedmobility issues that are evident in other places around theworld, for example, the paucity of suitable parkingspaces/numbers and locations for shared mobility facilities,and the need for smart technology that elicits information formeeting travel demands.The study found a number of barriers relating to the notalways smooth interaction between policy makers andcommercial enterprises, suggesting opportunities for newcooperative business models, joint partnerships and sharedresponsibilities in the provision of shared mobility services.In particular, the lack of acknowledgement in accepting sharedmobility services as merit goods, in the same way as otherpublic transport services, prevented shared mobility frombeing supported by the government policy intervention. Refereed/Peer-reviewed

Abstract

This report explores the role of commercial shared mobility services in supporting the needs of major trip generators, using the inner urban Adelaide as a case study. The commercial shared mobility services covered in this report are characterised by carshare (such as GoGet), rideshare (UBER), bicycle share (dockless within the context of Adelaide provided by OfO and OBike) and shared e-scooters (such as provided by Lime, Beam and Ride). Major trip generators described in this report are characterised by festivals, sporting events or public facilities (such as hospitals, universities and transport interchanges) that attract relatively high numbers of participants and workers.

Abstract

Due to the current urbanization trend, people are spending more time than ever on their daily commute. However, commuting in megacities often results in irritating scenarios. Especially when using public transportation. This project tried to provide an alternative way of commuting that would allow people to refresh themselves during the journey and prepare for their activities in the best way possible. Rather than looking at the commute as a transition from A to B, this project tried to envision different scenarios of daily life and implement smart solutions that would enhance the experience through seamlessly integrated technologies—based on the technological expertise from the sponsor Huawei. In this concept, smart sensors combined with data collection would provide a tailored experience for the customer at different depth levels. The process includes brand research and topic selection to set up the design goal. Basing on the valuable material got from the first step, the design moved to the next step and tried to find the solution for the thesis topic. This is processed by gathering information from the website, brainstorming the ideation. Then the author built up the prototype by sketching, rendering, and 3D modeling. The user experience got developed basing on the robust design. The author started with user research and analyzed and set up personas. The result is an interior design concept with a particular focus on its interaction and user experience. The seating position supports the user experience by changing in harmony with individual preferences and time of the day. Three unique travel modes provide different levels of control over the overall experience based upon the user's request and their trust in the smart system.

Abstract

Shared-use mobility systems, which enable users to have short-term access to transportation modes on an on-demand basis, have experienced tremendous growth over the last decade. However, most of the existing systems suffer from two confounding issues: the lack of modeling tools to understand, simulate and predict their behavior and the lack of integration with the existing transit network. To address those issues, this dissertation focuses on investigating the operational challenges of bikesharing systems, with an emphasis on the rebalancing operations and the modeling of a new mobility concept, Car2work, which builds upon existing carsharing ideas and successfully integrates with existing transit networks. A methodological framework to solve the bikesharing rebalancing problem is proposed. The novelties of the approach are that it is proactive instead of reactive, as the bike redistribution occurs before inefficiencies are observed, and uses the outputs of a demand-forecasting technique to decompose the inventory and the routing problem. The decomposition makes the problem scalable, responsive to operator inputs, and able to accommodate user-specific models. Simulation results based on data from the Hubway bikesharing system show that system performance improvements of 7% in the afternoon peak could be achieved.Car2work main goal is to connect commuters with workplaces while leveraging the line-haul capabilities of existing public transit systems and guaranteeing a trip back home, efficiently tackling the “last mile” problem that is a limiting characteristic of public transit. It differs from the traditional dynamic-ridesharing approaches because it is designed for recurrent commuting trips where commuters announce their (multiple) trips in advanced and an automated all-or-nothing matching strategy is performed, guaranteeing a ride home. The problem is formulated as a pure binary problem that is solved using an aggregation/disaggregation algorithm that renders optimal solutions. The solution approach is based on decomposing the problem into a master problem and a sub-problem, reducing the number of decision variables and constraints. As a result, various instances of the problem can be solved in reasonable amount of time, even when considering the transit network. The model can be used to simulate a widespread implementation of the concept.

Abstract

Shared mobility, including ride-hailing services, has been on the rise, enabled by emerging technologies, and allowing for more convenient and flexible travel. The Chinese market is particularly attractive for ride-hailing as the country pushes to relieve its transportation problems, namely traffic congestion and subjacent economic implications. This study aims to measure the impact of ride-hailing services on BYD’s share price performance. Three different scenarios of disruption were analyzed, quantifying the potential decrease in revenues. Moreover, an alternative view was considered, taking into consideration the depreciation suffered by society as a whole and the rate of substitution of vehicles.

Abstract

This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of the author’s knowledge, it is the first model that combines a network fundamental diagram with choice models. A second contribution is the inclusion of automated vehicles, automated (shared) taxis, automated shared vans and new parking concepts in the model as well as the way in which they affect mobility choices and traffic conditions. The insights into the impact mechanisms and the direct and indirect mobility impacts are the third contribution. The short computation time of the model enables exploration of large numbers of scenarios, sensitivity analyses and assessments of the impacts of interventions. The model was applied tin a case study of the Dutch Province of North-Holland, in which the potential impacts of automated and shared vehicles and mitigating interventions were explored. In this case study, four extreme scenarios were explored, in which 100% of the vehicles have SAE-level 3/4 or 5 and people have a low or high willingness to share. The extremes were chosen to get insights into maximum effects. The results show that if automated vehicles and sharing are accepted, it is likely that there will be considerable changes in mobility patterns and traffic performance, with both positive and problematic effects.