MONICA GROSSO

Monica Grosso is a transport economist with a PhD in Transport, Logistics and Territory and Applied Economics. She has worked since 2017 at the Sustainable Transport Unit of the European Commission Joint Research Centre (JRC), Ispra, Italy. She is part of the Transport Research and Innovation Monitoring and Information System (TRIMIS) Team and is also involved in research on the socio-economic impact of Cooperative, Connected and Automated Mobility.

 

PBIAGIO CIUFFO

Biagio Ciuffo received his Ph.D. in transportation engineering from the Department of Transportation Engineering of the University of Napoli Federico II in 2008. He then joined the European Commission Joint Research Centre (JRC), Ispra, Italy, assessing the sustainability of traffic- and transport-related measures and policies. He is project leader for various projects concerning the reduction of CO2 emissions in road transport and the effect of automated/connected vehicles on transport and society. Ciuffo has published more than 50 papers in peer-reviewed journals and conference proceedings on transportation engineering. He is Associate Editor for the IEEE-Transaction on Intelligent Transportation Systems and acts as reviewer for several international journals and conferences.

 

MARÍA ALONSO RAPOSO

María Alonso Raposo holds a degree in Industrial Design Engineering and Human-Computer Interaction. She joined the Sustainable Transport Unit at the European Commission Joint Research Centre (JRC), Ispra, Italy, in 2016 as a technology and policy analyst on autonomous road transport. The main focus of her work is the analysis of the social and economic implications of a Cooperative, Connected and Automated Mobility, in support of EU policy-making in this area.

 

The future of transport will be marked by new technologies such as vehicle connectivity and automation, together with mobility services like ride-sharing or car-sharing. The combination of these technologies and services can have a disruptive effect, enabling new business models in place of the legacy vehicle ownership-based model. With improved safety and conditions (including accessibility), travel demand is expected to rise significantly. At the same time, it is anticipated that these new technologies will bring deep changes in the labour market, progressively reducing the relevance of some occupations and skills, while at the same time opening up new business opportunities and requiring new and more advanced skills.

©Metamorworks - istockphoto.com

The term Cooperative, Connected and Automated Mobility (CCAM) [1] enshrines the concept of a future mobility in which all actors are connected, communicating and interacting in a seamless and automated way. Recently, the third and last part of the Europe on the Move package [2] was presented by the European Commission, including a communication on automated mobility [3]. While CCAM may well reduce demand for professional drivers, it could also help to make jobs in driving more attractive and to remedy the current shortage of drivers. In response to the Council conclusions on the digitalisation of transport [4], the European Commission has already undertaken a review of the expected socio-economic impacts of automated and connected vehicles on the EU economy and jobs [5].

Concerns about job destruction due to automation

History has shown that even if effective technologies implementation affects workers negatively in the short term [6], technology advancements can lead to

'The maintenance and repair industry will require ICT skills in addition to traditional vehicle repair skills'

higher job creation [7] in the long run. Estimations of the number of jobs at risk of automation produce divergent results based on the approach followed. For instance, 47% of US jobs [8] have been estimated to be at risk of computerisation, while only 9% of jobs in OECD [9] countries are considered at risk. Nowadays, Automated Vehicles (AVs) cannot perform all the tasks required in most driving-related jobs, and there is much uncertainty whether they ever will [10].

Occupations at risk of job displacement by CCAM

According to different scenarios, the current 3.2 million truck-driving jobs in Europe may decrease to 2.3 or even to 0.5 million by 2040 [7]. Drivers and mobile plant operators working in land transport who are in danger of technological substitution amount to approximately 1.5% of total EU-15 employment in 2012. Those who require new training to keep performing the job, working in metal and machinery and related trades in wholesale, retail and repair of motor vehicles, amount to 0.7% of total EU-15 employment in 2012 [11]. Impact on employment is not restricted to the land transport sector but will affect all sectors in which drivers are employed, such as warehousing and support, wholesale trade and postal and courier activities.

Future requirements of the workforce

It is relevant to note that both occupations (metal, machinery and related trades, as well as drivers and mobile plant operators) have low levels of ICT use, whereas the land transport sector will depend increasingly on ICT-based and specialised equipment and products in the future [12]. In addition, the maintenance and repair industry will require ICT skills in addition to traditional vehicle repair skills [13]. In this context, a shortage of ICT professionals has been identified for 2020 [14].

New occupations or reallocation?

Fulfilling future skills demand might offer opportunities for the reallocation of employees. Some highly qualified mechanics might move to higher-paying jobs in the information sector [12]. Experienced drivers could apply their skills in remote control rooms for monitoring Connected Automated Vehicles (CAVs) [7]. It is very difficult to predict the qualifications and characteristics of future jobs as driven by the wider economy, but recent labour market experiences suggest that new occupations will tend mostly towards the higher end of skills distribution [7].

What can be done to facilitate a smooth transition to the workforce of the future?

The impacts of CCAM on employment are largely influenced by the speed of introduction of new technologies and mobility changes. The more gradual the introduction, the higher the probability that the negative implications on employment will be absorbed by the European economic system. A slow CAV uptake or an informative awareness campaign can lead workers to qualify on time and mitigate the transition costs for them [7]. Retraining or income assistance programmes could be used to support the transition [15].