Shared Mobility and Smartphone Applications: Expanding Choice and Facilitating Multi-Modal Connections
Technological advancements in social networking, location-based services (satellite- and cellular-based), the Internet and mobile technologies have given rise to a sharing economy. The sharing economy is a developing phenomenon based on renting and borrowing goods and services, rather than owning them. Sharing can occur as a peer-to-peer service (e.g. community drivers, personal vehicle sharing or bikesharing) or through businesses-to-consumer models (e.g. a carsharing operator). The sharing economy has the potential to improve efficiency, deliver cost savings, monetize underused resources and disrupt traditional norms.
Impacted by the Internet and the dot-com boom of the late-1990s, websites such as eBay, Craigslist and PayPal created a marketplace where individual entrepreneurs had access to global markets. Peer-to-peer (P2P) sharing via file-sharing networks (e.g. Napster) became one of the most prominent sharing models in the early-2000s. These technological advancements enabled not only changes in consumption and financial transactions, but they are facilitating sociological transformations about how people view resources and consumption. These technological advancements and social disruptions coupled with the Great Recession of 2007 to 2009 became a driving factor for many individuals and households to rethink resource consumption. During the late-2000s, numerous sharing models emerged, such as P2P marketplaces (e.g. Airbnb), crowdfunding (e.g. Kickstarter) and shared mobility (e.g. Getaround).
What is Shared Mobility?
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 (Shaheen, Cohen, and Zohdy 2016). The term shared mobility includes various forms of carsharing, bikesharing, ridesharing (carpooling and vanpooling) and on-demand ride services (e.g. ridesourcing, taxis, etc.). Shared mobility also includes alternative transit services (e.g. paratransit, shuttles and microtransit), which can supplement fixed-route public transportation services. In addition to these innovative travel modes, new app-based methods of transporting and delivering goods are also emerging, referred to as courier network services. These courier network services have the potential to change the nature of the package and food delivery industry, as well as the broader transportation network. Broadly, there are two ways of viewing shared mobility in the larger network of surface transportation modal choices. Shared modes can be classified as emerging or innovative (e.g. bikesharing, carsharing, etc.) in contrast to existing core and incumbent services (e.g. taxis, public transportation, etc.).
What are the Impacts?
A number of environmental, social and transportation-related impacts have been reported from the use of shared mobility modes, and an increasing body of empirical evidence supports these relationships. These impacts can be grouped into four categories: 1) travel behaviour, 2) environmental, 3) land use, and 4) social. Cost savings and convenience are frequently cited as popular reasons for shifting to a shared mode. Shared mobility can also extend the catchment area of public transit, potentially helping to bridge gaps in existing transportation networks and encouraging multimodality by addressing the first-and-last-mile issue related to public transit access. Shared mobility may also provide economic benefits in the form of cost savings, increased economic activity near public transit stations and multimodal hubs, and increased access by creating connections with origin points not previously accessible via traditional public transportation. Some of the impacts documented through self-reported travel behaviour surveys include:
- Carsharing: Several academic studies of roundtrip and one-way carsharing have documented sold or postponed vehicle purchases, reduced vehicle miles/kilometres travelled (VMT/VKT), increased access and mobility for formerly carless households, lower greenhouse gas emissions and greater environmental awareness.
- Bikesharing: Studies of bikesharing document increased mobility, reduced greenhouse gas emissions, increased use of alternative modes (e.g. walking), economic development, health benefits (e.g. increased physical activity, calories burned, etc.).
- Ridesharing: Studies of ridesharing are more limited with respect to impacts. However, due to increased vehicle occupancies, ridesharing is commonly associated with reductions in energy consumption and emissions, congestion mitigation and reduced parking infrastructure demand.
Impacts of other shared modes are not well understood. Shared mobility can be integral in bridging first-and-last mile gaps in the transportation network and potentially encouraging multi-modal trips. Note, differences in service models, data collection and study methodologies can produce inconsistent results due to limited survey samples and aggregate-level analyses. Travel behaviour surveys may contain validity issues (e.g. respondents exaggerating travel behaviours, underreporting the extent or frequency of travel, or reporting inaccurately as well as sample bias). Self-reported travel behaviour surveys offer a source of behavioural research. Understanding the impacts of shared mobility can aid policymakers in leveraging positive impacts and taming the negative impacts to achieve public policy goals. However, more data and research is needed to fully understand the spectrum of impacts that shared modes have on the transportation network.
Why Do Impacts Matter?
There is no doubt that social and technological changes are altering how people travel. Despite this growth, traditional transportation planning methods are unable to accurately capture modal share and the impacts of shared mobility (and other emerging technologies) on the broader transportation network. Early four-step planning models have matured into more advanced activity-based modeling. Although some planning agencies have embraced activity-based modeling as more representative of the transportation environment, existing activity-based modeling almost always fails to incorporate shared mobility. Additional data are needed to aid cities, public agencies and metropolitan planning organizations in understanding the impacts of shared mobility and better scale and deliver these services in a variety of land-use settings.
The Role of Smartphone Apps
In recent years, shared mobility has become increasingly reliant on smartphone applications (apps) for deployment. At the most basic level, these apps facilitate on-demand access to shared modes. However, more advanced apps are emerging that employ open data, algorithms and advanced programing interfaces (known as APIs) to aggregate real-time information services, multi-modal trip planning and fare payment into a single application. Commonly referred to as trip or multi-modal aggregator apps, these apps have the ability to make both on-demand mobility and multi-modal trips more convenient and effective for the mobility consumer, potentially reducing single occupant vehicle travel, increasing public transit ridership and more broadly improving the overall efficiency of the surface transportation network.
Both smartphone apps and shared mobility operators, whether in a single-mode or multi-modal context, collect detailed travel behaviour data that can be useful for public agencies in understanding travel patterns and identifying critical gaps in the transportation network. For example, shared mobility operators typically track several important data points – the origin and destination of shared services (e.g. the pickup and return location for a carsharing or bikesharing vehicle, or ridesourcing passenger), travel time and trip duration. For example, Bay Area Bike Share, Capital Bikeshare and Citi Bike are a few shared mobility operators that provide expansive data sets for public download. Some of the bikesharing data provided include information on trip origin and destination (location and time), rider type (e.g. the type of user passes), home zip code for annual members, the bicycle number, weather information and bicycle/dock availability at each station. Similarly, single- and multi-modal apps may collect data on the origins, destinations, time of travel, routing and modal choices of thousands of travellers within any given city or region.
Access to this data can aid public agencies in their local and regional understanding of the transportation network and guide future transportation planning and investment decisions. With these data, public agencies now have the potential to develop models, planning platforms and formal methodologies to measure the travel and economic impacts of shared mobility and other emerging transportation technologies. This can aid public agencies in developing tools to enable forecasting and guide public policy development related to urban and spatial planning, rights-of-way, parking and zoning.
Opportunities for Public and Private Partnerships
In the future, data sharing and interoperability will enable public agencies to understand how shared mobility is impacting the transportation network and can facilitate the integration of multi-modal information and fare collection. In the future, public and private partnerships will be the key.
Innovative public and private partnerships are already beginning to exemplify opportunities and best practices. In June 2014, for example, during the World Cup, Rio de Janeiro’s government obtained driver navigation data from Google’s Waze app and combined it with information from pedestrians who use the public transportation app Moovit, providing local authorities with valuable real-time information about the transportation network. Previously, the local transportation department had been reliant solely on road cameras and roadway sensor data. Incorporating data from Waze and Moovit allowed local officials to use aggregated crowdsourced data from a pool of 110,000 drivers (half a million over the course of the month) and to identify thousands of operational issues ranging from congestion to roadway hazards. In exchange for sharing user mobility data with government authorities, Waze asked for transportation network data (e.g. sensor data, construction information, etc.).
Best Practices and Guiding Principles
Public agencies and app developers can work together to mutually improve the quality and availability of transportation data by ensuring that data made available are in an open format that can be downloaded, indexed, searchable and machine-readable to allow automated processing. Additionally, they should ensure that data are open and available to the public for use. Finally, they should ensure high-quality and timely data. This can include data scrubbing for plug-and-play end use by developers without requiring extensive effort to make datasets usable and making data available as quickly as possible and frequently enough to remain current and usable.
One guiding principle that public agencies can employ to encourage public and private data sharing and app development is to establish data exchanges that can serve as repositories for public and private transportation data sets. In doing so, public agencies and the private sector should work together to establish data standards. This includes identifying the type of data that the public and private sectors can use both for the planning, design, operation, safety and maintenance of the transportation network and the development of third-party apps and determining the format and standards for publishing data sets that are consistent with industry standards, other public entities, and address interoperability issues. Public agencies should require two-way sharing of data whenever possible. For example, public agencies could require that apps share self-reported (crowdsourced) incident data with public agencies in exchange for receiving their data. Public agencies could then provide a critical public service by aggregating these data and re-disseminating aggregated data in real time.
Leveraging the convergence of shared mobility and smartphone applications represents a key opportunity for public agencies to enhance multi-modality. Smartphone apps and shared mobility offer the potential to: 1) bridge first-and-last mile connections by addressing the physical barriers of multi-modal connectivity and 2) integrating information systems and fare payment so that users have a single interface to plan, execute and pay for an entire trip.
About the Authors:
Susan Shaheen, Ph.D. and Adam Cohen, Transportation Sustainability Research Center, University of California, Berkeley
Susan Shaheen is a co-director of the Institute of Transportation Studies' Transportation Sustainability Research Center (TSRC) at the University of California (UC), Berkeley. She is also an adjunct professor in the Civil and Environmental Engineering Department at UC Berkeley.
Adam Cohen is a research associate at the (TSRC). Shaheen and Cohen are co-authors of two Federal Highway Administration Primers on shared mobility and smartphone applications.
For more information, please consult:
Shaheen, Susan, Adam Cohen, and Ismail Zohdy (2016). “Shared Mobility: Current Practices and Guiding Principles,” FHWA-HOP-16-022, U.S. Department of Transportation, Washington, DC., April. 120 pages. http://www.ops.fhwa.dot.gov/publications/fhwahop16022/index.htm
Shaheen, Susan, Adam Cohen, Ismail Zohdy, and Beaudry Kock (2016). “Smartphone Applications to Influence Travel Choices,” FHWA-HOP-16-023, U.S. Department of Transportation, Washington, DC., April. 90 pages. http://www.ops.fhwa.dot.gov/publications/fhwahop16023/index.htm
