A Framework for Integrating Transportation Into Smart Cities

In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities

Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes

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. It includes various forms of carsharing, bikesharing, scooter sharing, ridesharing (carpooling and vanpooling), transportation network companies (TNCs), and microtransit. Included in this ecosystem are smartphone “apps” that aggregate and optimize these mobility options, as well as “courier network services” that provide last mile package and food delivery. This chapter describes different models that have emerged in shared mobility and reviews research that has quantified the environmental, social, and transportation-related impacts of these services

Mobility on Demand in the United States

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

Planning for Density in a Driverless World

Automobile-centered, low-density development was the defining feature of population growth in the United States for decades. This development pattern displaced wildlife, destroyed habitat, and contributed to a national loss of biodiversity. It also meant, eventually, that commutes and air quality worsened, a sense of local character was lost in many places, and the negative consequences of sprawl impacted an increasing percentage of the population. Those impacts led to something of a shift in the national attitude toward sprawl. More people than ever are fluent in concepts of “smart growth,” “new urbanism,” and “green building,” and with these tools and others, municipalities across the country are working to redevelop a central core, rethink failing transit systems, and promote pockets of density. Changing technology may disrupt this trend. Self-driving vehicles are expected to be widespread within the next several decades. Those vehicles will likely reduce congestion, air pollution, and deaths, and free up huge amounts of productive time in the car. These benefits may also eliminate much of the conventional motivation and rationale behind sprawl reduction. As the time-cost of driving falls, driverless cars have the potential to incentivize human development of land that, by virtue of its distance from settled metropolitan areas, had been previously untouched. From the broader ecological perspective, each human surge into undeveloped land results in habitat destruction and fragmentation, and additional loss of biological diversity. New automobile technology may therefore usher in better air quality, increased safety, and a significant threat to ecosystem health. Our urban and suburban environments have been molded for centuries to the needs of various forms of transportation. The same result appears likely to occur in response to autonomous vehicles, if proactive steps are not taken to address their likely impacts. Currently, little planning is being done to prepare for driverless technology. Actors at multiple levels, however, have tools at their disposal to help ensure that new technology does not come at the expense of the nation’s remaining natural habitats. This Article advocates for a shift in paradigm from policies that are merely anti-car to those that are pro-density, and provides suggestions for both cities and suburban areas for how harness the positive aspects of driverless cars while trying to stem the negative. Planning for density regardless of technology will help to ensure that, for the world of the future, there is actually a world

Chapter 3 - Mobility on demand (MOD) and mobility as a service (MaaS): early understanding of shared mobility impacts and public transit partnerships

Technology is changing the way we move and reshaping cities and society. Shared and on-demand mobility represent notable transportation shifts in the 21st century. In recent years, mobility on demand (MOD)—where consumers access mobility, goods, and services on-demand by dispatching shared modes, courier services, public transport, and other innovative strategies—has grown rapidly due to technological advancements; changing consumer preferences; and a range of economic, environmental, and social factors. New attitudes toward sharing, MOD, and mobility as a service (MaaS) are changing traveler behavior and creating new opportunities and challenges for public transportation. This chapter discusses similarities and differences between the evolving concepts of MaaS and MOD. Next, it characterizes the range of existing public transit and MOD service models and enabling partnerships. The chapter also explores emerging trends impacting public transportation. While vehicle automation could result in greater public transit competition in the future, it could also foster new opportunities for transit enhancements (e.g., microtransit services, first- and last-mile connections, reduced operating costs). The chapter concludes with a discussion of how MOD/MaaS partnerships and automation could enable the public transit industry to reinvent itself, making it more attractive and competitive with private vehicle ownership and use

Modelling public transport accessibility with Monte Carlo stochastic simulations: A case study of Ostrava

Activity-based micro-scale simulation models for transport modelling provide better evaluations of public transport accessibility, enabling researchers to overcome the shortage of reliable real-world data. Current simulation systems face simplifications of personal behaviour, zonal patterns, non-optimisation of public transport trips (choice of the fastest option only), and do not work with real targets and their characteristics. The new TRAMsim system uses a Monte Carlo approach, which evaluates all possible public transport and walking origin-destination (O-D) trips for k-nearest stops within a given time interval, and selects appropriate variants according to the expected scenarios and parameters derived from local surveys. For the city of Ostrava, Czechia, two commuting models were compared based on simulated movements to reach (a) randomly selected large employers and (b) proportionally selected employers using an appropriate distance-decay impedance function derived from various combinations of conditions. The validation of these models confirms the relevance of the proportional gravity-based model. Multidimensional evaluation of the potential accessibility of employers elucidates issues in several localities, including a high number of transfers, high total commuting time, low variety of accessible employers and high pedestrian mode usage. The transport accessibility evaluation based on synthetic trips offers an improved understanding of local situations and helps to assess the impact of planned changes.Web of Science1124art. no. 709