Harnessing the combined strengths of shared mobility and high capacity public transit is key to the future of mobility

Shared mobility can bridge the last and the first mile in a transport chain, and thus act as a complement to public transit. However, shared mobility could also turn out to be mainly a substitute, as it reduces the cost of the alternatives to public transport. Policies need thus to be designed that harness the strengths of shared mobility solutions to promote alternatives to unimodal car mobility. A ‘backbone’ of high-capacity public transit also remains essential. Otherwise, the huge traffic volumes created by shared cars that are repositioned for picking up new clients will result in further increases in congestion.

• Shared mobility can bridge the last and the first mile in a multimodal transport chain.

• Shared mobility can bridge the last and the first mile in a multimodal transport chain.

• Policies should harness the strengths of shared mobility to promote alternatives to unimodal car mobility.

• A ‘backbone’ of high-capacity public transit is needed to prevent increased congestion from shared automated vehicles.

Shared mobility can act as a complement, because it can be an effective tool to bridge the last and the first mile in a transport chain (see Deutsche Bahn, 2016; Greenblatt and Shaheen, 2015; Kockelman et al., 2016; Martin and Shaheen, 2014; and Shaheen et al., 2015). The “first/last mile” problem can have a dramatic effect on door-to-door travel time, and is therefore an important barrier to a shift from private car use to public transit.

The “first/last mile” problem is also an important barrier to mobility in general for poorer households who cannot afford private cars. Access to mobility in turn affects access to jobs if there is an important spatial mismatch in job accessibility, and the “last mile” problem can effectively worsen the employment prospects of poorer people (Chetty et al., 2014). 

As a result, for low income households, solving the “last mile” problem can signify a step change in their employment prospects that should be weighted higher than the time savings of households who already have access to private mobility.

However, shared mobility could also turn out to be mainly a substitute for public transit (see Martin and Shaheen, 2014), as it reduces the cost of the alternatives to public transport (cars, jitney services, bicycles). For some trips, the door-to-door distance of a shared vehicle may also be much lower than for public transit, especially if big data allows for a further improvement of routing algorithms. In these cases, the move to an increasing use of shared solutions could create a new vicious circle of decreased transit patronage and decreased service levels.

Arguably, the most important question in transport policy in the next few years will be whether policies can be designed that harness the strengths of shared mobility solutions to solve the “first/last” mile problem, and thus to promote alternatives to unimodal car mobility. Several authorities or operators are already trying to do exactly this.

If ride sourcing is a natural monopoly in any given city, ride sourcing could be considered to be a public utility, and thus be subject to public service obligations, which could include acting as feeder services to the transit system.

The concept of “Mobility as a Service” also fits within this pattern (by Kamargianni et al., 2015). Even if one does not go as far as the implementation of “complete” MaaS, partial measures (such as integrated ticketing and the provision of real-time multi-modal travel information) already go a long way.

Public authorities can also reinforce this complementarity by providing the necessary infrastructure of bike-, ride- and car-sharing in the neighbourhood of important public transport hubs (Hallock and Inglis, 2015).

An important element to bear in mind is that, with the rise of automated mobility, the opportunity cost of travel time and time spent in congestion will decrease, and this will further undermine the competitive position of some transit services (Levin and Boyles, 2015). In the absence of an appropriate policy response, substitution effects are thus likely to dominate possible complementarities.

In line with the simulations performed by the ITF (2015; 2016), we can reasonably expect that, in the future, transit will increasingly concentrate on the task it is good at: moving huge quantities of people from one transport hub to the other. Whether this can only be implemented by metro, light rail, or BRT systems, or whether traditional bus services still have a role to play in such a landscape, remains an open question.

The analysis by the ITF (2015; 2016) is also important because it shows that this ‘backbone’ of high-capacity remains an essential element in urban mobility. Otherwise, the huge traffic volumes created by shared cars that are repositioned for picking up new clients will result in even more congestion than nowadays.

  • Chetty, R., Hendren, N., Kline, P. & Saez, E., 2014. Where is the land of Opportunity? The Geography of Intergenerational Mobility in the United States, The Quarterly Journal of Economics, Oxford University Press, vol. 129(4), pages 1553-1623
  • Deutsche Bahn (2016), DB technology strategy, http://uic.org/com/uic-e-news/464/article/germany-db-diffuses-brochure-db?page=iframe_enews
  • Greenblatt, J. B. and Shaheen, S., Automated Vehicles, On-Demand Mobility, and Environmental Impacts, Current Sustainable/Renewable Energy Reports, 2015, vol 2, n° 3, pp 74—81.
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  • International Transport Forum (ITF) (2015) How shared self-driving cars could change city traffic? Corporate Partnership Board, http://www.itf-oecd.org/sites/default/files/docs/15cpb_self-drivingcars.pdf
  • International Transport Forum (ITF) (2016), Shared Mobility: Innovation for Liveable Cities. Corporate Partnership Board, Policy Insights, http://www.itf-oecd.org/shared-mobility-innovation-liveable-cities
  • Kockelman, K.M., Chen D. & Hanna, J. (2016) Operations of a Shared, Autonomous, Electric Vehicle (SAEV) Fleet: Implications of Vehicle & Charging Infrastructure Decisions. Proceedings of the 95th Annual Meeting of the Transportation Research Board (2016), and under review for publication in Transportation Research Part A (2015).
  • Levin, M.W. & Boyles, S.D. (2015), Effects of Autonomous Vehicle Ownership on Trip, Mode, and Route Choice, Transportation Research Record: Journal of the Transportation Research Board, Volume 2493, 2015, Travel Demand Forecasting, Vol. 1   DOI: http://dx.doi.org/10.3141/2493-04
  • Martin, E. &  Shaheen, S.. The Impact of Carsharing on Public Transit and Non-Motorized Travel: An Exploration of North American Carsharing Survey Data. Energies 2011, 4(11), 2094-2114; doi:10.3390/en4112094 Elliot
  • Shaheen, S., Chan, N., Bansal, A. & Cohen, A. (2015), Shared Mobility: Definitions, Industry Developments, and Early Understanding Bikesharing, Carsharing, On-Demand Ride Services, Ridesharing, Shared-Use Mobility http://innovativemobility.org/?project=shared-mobility-definitions-industry-developments-and-early-understanding   

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