Social and Economic Implications of Transport Sharing and Automation

68665a26-eba0-45ea-ba91-77a89fa90089

Closed

ESRC
ESRC
ESRC
ESRC
ESRC

£1,511,715

Jan. 19, 2018

Oct. 12, 2021

This study will link the changing nature of jobs due to automation and the platform economy to regional infrastructure planning and transport operations, and the role specifically of transport automation within this context. The patterns and forms of jobs are changing due to many different reasons, leading to non-traditional work schedules and differences in commuting patterns, non-standard work travel patterns, and even elimination of certain jobs and creation of new ones, with significant implications for regional infrastructure planning and transport operations. At the same time, there are enormous changes anticipated in infrastructure and operations, due to large-scale automation in the transport sector (eg autonomous and connected vehicles).

This project will make estimates of the changing nature of jobs due to these considerations at the regional level towards the goal of deriving the transport and regional infrastructural planning consequences. The project will use labour market survey data as well as privately-held labour market data on jobs, skills and industry to estimate regional variations due to these trends, given regional industry-occupation mix. These changes will be linked to the Spatial Urban Data System (SUDS), which is a UK-wide geospatial data infrastructure under development within UBDC containing transport infrastructural and operational conditions. , and which has been recently used to identify areas of transport poverty throughout the UK and the extent to which and which we will expand through work with the project's industrial partners.

Using these data sources, we will identify regional automation risks due to unique industry and skill concentrations and derive transport and infrastructure planning implications. Within this context, we will also evaluate the role of autonomous vehicles given potentially different commuting patterns using specialist transport simulation models. We will further develop specialist transport simulation models to ascertain which packages of "last-mile" transport solutions (low-energy station cars, autonomous vehicles, shared transport, active travel and demand-response services) are likely to bring about high-quality, sustainable and socially-equitable forms of transport accessibility in areas at risk of changing nature of jobs. We will then combine the results of our various model scenarios, using ensemble forecasting methods utilising Bayesian Model Averaging or related techniques to ascertain which packages are more likely to bring about high-quality transport accessibility in the selected areas.

Potential Impact:
With 66% of the world's population estimated to be living in urban areas by 2050, the need to provide new transport infrastructure and to address traffic congestion, road fatalities, air pollution, and associated problems continue to generate debates in policy circles.

Impact on local economic development and labour market planning: The work related to estimating the potential impact of automation and AI on jobs given skills required in the occupation-industry mix regionally available is likely to be of immense value to regional infrastructure planners and business owners, as well as for skills-development initiatives and organisations in the local economic development planning. Through UBDC's networks, we will engage local authorities and other stakeholders in co-creating our results on this topic, so as to involve our work in their planning processes.

Transport and infrastructure planning and operations impact: Additionally, there is a range of shared technology, automation and use of AI and Machine Learning (ML) being proposed in transport, and a growing business community involved in their development and use. Although the trends surrounding automation and sharing transport are being driven primarily by private companies, governments around the world are increasingly developing policies to support as well as to regulate many of these developments, and the UK government has an active programme on Connected and Autonomous Vehicles (CAV); among the high-value economic infrastructure to be funded through the 2016 National Productivity Investment Fund (NPIF) is £390 million for future transport including ultra-low emission vehicles and CAVs. Additionally, various types of shared mobility services, e.g., car-sharing, dynamic ride-sharing, on-demand personal mobility vans, and express, crowd-sourced urban delivery services, under the banner of Mobility-As- A-Service (MaaS) are now offered by private companies in UK cities. Just as the introduction of the private car in the beginning of the twentieth century transformed the way we live our daily lives and the ways in which cities developed, large-scale automation, connectivity and sharing of mobility resources (sharing economy) are expected to be a step-change changing daily lives in future society and the form and functions in cities.We expect that our results will help highlight significant regional planning and operations impact of such technology, against the backdrop of changing commuting and work-related travel patterns resulting from the changing nature of jobs.

Industrial Impacts: The approach will allow us to evaluate spatial and regional effects of varying degrees of automation and sharing mobility, and to identify new markets in smart cities and urban planning. Our industry partner, Peter Brett Associates, views that the risks of emerging technology being left out of the planning agenda are great due to lack of empirical data, leading technology disruption in transport to occur in an ad-hoc way. Having the results of the analysis and the associated data would help them reach new markets and also to reduce uncertainty in their forecasts. Scottish MaaS, has similarly noted that the methods and results being proposed will help them reach new markets both geographically thereby opening up UK companies to a global pipeline of contracts in integrating CAVs into infrastructure planning and construction, and MaaS solutions in addressing expensive last-mile problems facing city managers worldwide.