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2019
Conference Paper
Title
A real world data based potential analysis of non-driving related in-vehicle activities in the context of automated driving
Abstract
The present study examines the theoretical potential of digitalization and vehicle automation in quantitative terms for non-driving-related in-vehicle activities in either full automated or autonomous electric vehicles (SAE level 4 and 5). The focus here is on the passenger car market in Germany and the United States of America. Methodologically, the study is based on an accounting framework and analyzes driving profiles for their theoretical potential of non-driving-related in-vehicle activities (e.g. working, sleeping, eating, communicating or dedicated entertainment services). Therefore, real world driving data is used and several restrictions (e.g. traveled time) applied. Based on this, the relative potential of different non-driving-related tasks in (partial) autonomous vehicles is determined. Overall, the study can show that there is a potential for non-driving-related in-vehicle activity categories. Depending on the trip purpose, a theoretical potential for the non-driving related activity category""being productive"" is given for around 29% of all analyzed trips in the United States of America and 36% in Germany.