The Vehicle Data Value Chain as a Lightweight Model to Describe Digital Vehicle Services

Abstract

Digitalization has become an important driver of innovation in the automotive industry. For instance, the Quantified Self-movement has recently started spreading to the automotive domain, resulting in the provision of novel digital vehicle services for various stakeholders such as individual drivers and insurance companies. In this direction, a growing number of ICT start-ups from outside Europe have entered the market. Their digital vehicle services are grounded on the availability of vehicle Big Data. Hence, to better understand and capture this ongoing digital transformation, we introduce the Vehicle Data Value Chain (VDVC) as a lightweight model to describe and examine digital vehicle services. Furthermore, we classify current digital vehicle services offered by four start-ups and five car manufacturers by applying the VDVC, thereby identifying commonalities and differences within three crucial steps: data generation, acquisition, and usage. Additionally, we apply the VDVC to describe a digital mobility service provided by a European industry consortium. This exemplary application serves to evaluate the VDVC and show its general applicability in a practical context. We end our paper with a brief conclusion and an outlook on various current activities of standardization organizations, the European Commission and car manufacturers related to the future of vehicle services.

Monitoring Distracted Driving Behaviours with Smartphones: An Extended Systematic Literature Review

“…On the other hand, smartphones have also become an important platform for mobile applications, in general, and for the transport and mobility sector, in particular. These include, for example, app-based vehicle information systems [44] or fleet management apps, which, if used appropriately, can even lead to the prevention of risky driving behaviour [45,46]. In addition, smartphone sensors and cameras are already being used to enable driver monitoring systems, and researchers are exploring new ways to improve detection accuracy.…”