Impacts of autonomous vehicles on traffic volume: scenarios based on survey data for the City of Karlsruhe

Autonomous vehicles will become a significant influence in the field of traffic and transportation. To determine the possible impact of fully automated traffic, this thesis analyzes trip-pattern data for the City of Karlsruhe, Germany. Based on survey data from the year 2012, the traveled distances are calculated in Karlsruhea baseline scenario as well as two competitive scenarios: best-case and worst-case. The database is analyzed for the most emerging trip patterns in three areas of the City of Karlsruhe. Trip data, including trip distance and mode choice, are analyzed by trip purpose and individual groups (based on employment status). By modifying the average trip distance, mode choice and trip patterns based on literature reviewed information, the consequences of autonomous vehicles are estimated. The study shows, that autonomous vehicles have the potential to reduce traffic (best-case), but on the other hand, could approximately double the overall traveled vehicle distances (worst-case).