Examining Future Transport Scenarios to Drive Innovation in the UK

Autonomous self-driving driverless vehicle with radar on the road

Photo by martialred/Fotolia

The UK’s roads, railways and airports are some of the most congested in the world. In the past, countries have addressed such problems with additional infrastructure investment. But this strategy has its limits: land is finite, government resources are constrained, and study after study has shown that it is not possible to build one’s way out of congestion.

In this project we looked at how emerging technologies might help to make the transport system more efficient and effective. We used a futures methodology that takes a systematic view of travel activity, looking at scenarios that incorporate insights from key activities that generate travel: work/business, health, retail, long-distance travel for work and leisure, and freight movement. Our focus was on the year 2035, and we therefore concentrated on technologies that are in development today (2015-16).


The study approach consisted of three stages.

First, based on expert interviews, we identified six technologies that are likely to have an impact on the efficiency and effectiveness of the transport network, either by influencing travel demand, increasing the capacity of the transport network, or improving the productivity of travellers.

  • Autonomous vehicles (AVs)

    A field of technologies that, in their fullest expression, will allow vehicles to sense their environment and navigate without human input (e.g. driverless cars).

  • Next generation of information and communications technology (ICT) connectivity

    A range of telecommunications technologies that improve bandwidth, network availability and download and upload speeds for wireless communication, facilitating telecommuting, telehealth and retail activities.

  • User apps / Big Data / intelligent processing

    Collectively this refers to the gathering and analysis of vast amounts of data that can be used to provide personalised information. Together these technologies offer substantial potential for expansion of new mobility services, whether as part of autonomous or non-autonomous vehicle sharing schemes, or through more efficient transporting of freight, or by allowing travellers to seamlessly travel across modes.

  • Advanced manufacturing

    A range of novel technologies, including 3D printing, that improve manufacturing processes and could have the ability to influence freight travel.

  • Internet of Things

    A network of physical objects capable of detecting and communicating information between each other, which could influence health, retail, logistics and freight.

  • Novel materials and embedded sensors in infrastructure

    A range of advances in materials science and production techniques across the transport network, which could reduce damage and wear-and-tear of road surfaces or automatically repair ruptures or abrasions, thus reducing travel delays.

Next we developed three future travel scenarios, incorporating the six technologies described earlier, as well as social and economic factors that may influence future travel. These scenarios vary by gross domestic product (GDP) growth assumptions, technology development, cost of travel and total travel. The scenarios are not predictions of the future, but rather cover a range of possibilities.

  1. Driving Ahead is a scenario where gross domestic product (GDP) and per capita travel have grown at rates higher than anticipated and autonomous vehicles are widespread.
  2. Live Local is distinguished by more use of digital substitution for travel and lower per capita travel.
  3. Digital Divide has an economy growing at a slower-than-anticipated rate and high income inequality with advanced technologies remaining financially out of reach for many.

Our methodology combined expert opinion, gathered via in-person workshops, with cross-impact analysis, consistency analysis, and cluster analysis using specialised computer tool support. Even though it relied more on substantive expertise than on formal research and modelling, the approach was highly empirical.

The scenarios were then used as a basis for interviews with policymakers from government, industry and academia to determine which technologies and innovations will be most valuable across a wide range of future scenarios and to identify key policy and investment interventions to support their innovation.

Key Findings & Recommendations

There is no clear relationship between the amount of popular interest a technology generates and its potential to create value. Decision makers need to have the knowledge to assess technology advancement, and potential impact, including in the appraisal of transport investments, to ensure new technologies have the best outcomes for society.

In order to encourage efficient and effective transport in future, government agencies should:

Invest in and monitor technological interventions which are robust across a range of future scenarios

  • Ensure that high quality ICT services are available, across all geographies, and that these services are accessible to all.
  • Support development of frameworks and systems necessary for addressing issues of data governance, transparency, value, ownership and privacy, ensuring regulatory balance between beneficial uses of data and consumer protection.
  • Support pilot testing of new technologies and experimentation; particularly those that will bring substantial societal benefits.

Develop policies to ensure that new technologies lead to the best outcomes for society

  • Monitor road congestion and introduce road pricing policies to manage travel demand, if required.
  • Support training and up-skilling of workers to ensure they have the skills needed for future jobs.
  • Assure equity of access to technologies that have the possibility of bringing substantial societal benefits, across geographies and society.
  • Monitor and appraise future technologies and their social impact, considering the entire technology eco-system to ensure public investments are made in those technologies which will have a substantial positive impact on society.

Support innovation of autonomous vehicles (AVs), next generation ICT and big data/user apps/intelligent processing

  • Address future liability and safety issues for AVs.
  • Monitor and, if needed, support development of standards supporting interoperability of systems.
  • Support research on operational issues which may impact AV use and adoption, and which affect the benefit of AVs to society.