Germany's Microsimulation Study Evaluated the Mobility Impacts and Monetary Benefits Saved by Re-Purposing of Travel Time of Level Four and Five Vehicle Automation.
Karlsruhe, Germany
Graben-Neudorf, Germany
Assessing travel time savings and user benefits of automated driving – A case study for a commuting relation
Summary Information
Connected and Automated Vehicles (CAV), when supported with appropriate infrastructure information, offer great potential to increase roadway capacity. To quantify the impacts of automated driving on travel time-related user benefits, this study analyzed a typical commuting origin-destination (OD) pair between Graben-Neudorf and Karlsruhe, Germany. Three route options were considered consisting of freeway, arterial and collector routes, as well as Level Four and Five vehicle automation (high or full driving automation) using microscopic traffic flow simulations. A signalized three-leg intersection was selected as a representative network element to estimate capacity increase and travel time savings for Level Four and Five vehicle automation and to compare it with the mean vehicle delays of conventionally controlled traffic. To investigate the potential travel time savings by avoiding circling the block for parking, the researchers also developed a microscopic traffic flow model of the Karlsruhe-Oststadt district with about 2,000 curb parking spaces that considered passenger cars only. Finally, monetary benefits generated by the re-purposing of travel time saved by vehicle automation were estimated using the average willingness-to-pay values for utilizing additional services in an automated car.
METHODOLOGY
This study evaluated the impacts of 100 percent CAV penetration on travel times and vehicle delays, applying the German Highway Capacity Manual's delay-flow relations and updating them for CAV operation. New capacity values from microscopic traffic simulations of German roads were used, assuming Level Four CAVs revert to manual control at Operational Design Domain (ODD) borders, with a slight delay added for this transition. The study incorporated human driving behavior into the psycho-social model, differentiating between cautious and assertive AV driving styles. For neighborhood simulations, it assumed no prior parking occupancy information for CAVs, with rerouting to the nearest available parking. The monetary benefits of commute time savings with CAVs were estimated based on an average willingness to pay of 27€ per month for a 30-min trip. Adjusting for actual commuting distances and times resulted in a willingness to pay of 17.55€ per month for the specific commuting scenarios studied.
FINDINGS
- The commuter OD pair simulations revealed travel time reductions ranging from 11 to 27 percent, with the greatest savings of 27 percent observed with Level Five automation, and up to 20 percent for Level Four.
- Monetary benefits analysis indicated annual savings of up to 374€ (442 US Dollars using 2018 rate) for Level Four and 573€ (677 US Dollars using 2018 rate) for Level Five automation. This translates to total benefits of approximately 1,310–2,240€ (1,547-2,646 US Dollars using 2018 average rate) for Level Four and 2,770–3,440€ (3,272-4,063 US Dollars using 2018 average rate) for Level Five over a passenger car's six-year depreciation period.
- The neighborhood simulation findings indicated that with Parking Pressure Factor (the number of vacant parking places relative to the parking demand) resulting in 75 to 100 percent occupancy, the average cruising time to find parking for a human driver was two minutes, a time saved by CAVs equipped to autonomously navigate to the neighborhood’s parking garage.
