Transformation of the Mobility System: Exploring the Impacts of Automated Driving on Future Labour Markets

Type de publication:

Conference Paper

Auteurs:

Boos, A.

Source:

Gerpisa colloquium, Bordeaux (2024)

Résumé:

This paper analyses how the emergence of a new mobility paradigm that prioritises the needs of society's mobility users and increases flexibility and inclusivity through the integration of automated vehicles (AVs) into public transport (PT) or, even better, a Mobility as a Service (MaaS) system that combines public and private providers, is reshaping the labour markets of these societies. Particular attention is given to AVs as mobility gap fillers in a MaaS and the use of data and artificial intelligence (AI) to create continuous improvements loops for the mobility system. User-centricity could make e.g. MaaS with AVs so attractive for citizen that a substitution of private cars could be envisaged and the production of private (automated) cars and accordingly jobs in the automotive industry would be endangered. Furthermore, by increasing the efficiency of AVs, the in-vehicle safety driver could be replaced by an out-of-vehicle supervisor who looks after several vehicles at the same time, which would have an immediate impact on existing and future jobs in this new form of mobility system. Moreover, such a new form of mobility through MaaS would certainly change the labour market for drivers in public transport, taxis, Uber, trucks and much more. In addition, sectors such as car-related services like towing, repair, insurance and even public services like recording traffic accidents would change.
Therefore, based on an integrative literature review on the topic of changes in labour markets due to automated driving, this paper derives quantitative and qualitative projections on the development of multiple sectors. Since the literature on the increase/decrease in (non-)employment due to automated driving is limited, this literature review also draws on the literature on changes in labour markets due to AI to fill these gaps. Specifically, of course, the literature that mentions mobility and/or transport is used for this, but the literature on the impact of AI on production is also included where it seems appropriate.
Accordingly, two macro-level models are developed from this integrative literature review which, on the one hand, quantitatively show which changes can be expected on the labour markets due to automated driving on the basis of existing data, and, on the other hand, qualitatively explain/evaluate not only these in detail, but above all expected changes that cannot yet be quantified due to non-existing data. The available information is used to elaborate predictions about expected changes on the macro level of the labour market, at least in industrialized nations and especially in the EU and the USA. The predictions cover up expected job losses, expected job gains, and expected jobs no longer to be filled that were vacant due to a shortage of skilled workers.
Keywords: automated driving, MaaS, new mobility, labour market, future of work.

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