2023

Aittoniemi, Elina; Itkonen, Teemu; Innamaa, Satu

Impacts of driving automation on traffic flow and emissions are usually studied with traffic simulations using only few speed limits and traffic volumes. Without considering the real-world prevalence of simulated scenarios, it is unknown how the results translate to real-world conditions, such as a regional motorway network. The present study assessed the potential impacts of conditionally automated driving, described by stable vehicle motion control and longer time gaps, on the European motorway network assuming no changes in other influential factors, such as travel demand or vehicle fleet. Traffic simulations provided estimates of the effect magnitude per vehicle kilometre travelled (VKT) in representative conditions, and results were scaled up using map-, traffic- and weather-related data, accounting for the VKT per condition. Overall, the impacts of automated vehicles (AVs) on the European motorway network are likely small. Travel times and delay are estimated to increase by 0.8% and 1.3% respectively at a 100% AV penetration rate among passenger cars, and CO2 emissions to drop by 0.5%. While large reductions of average travel time (up to 8.0–10.4%), delay (up to 17.5–34.8%) and emissions (up to 13.5–15.0%) were found at high traffic volumes, most (86%) of the VKT accumulate at low traffic volumes, with small estimated effects. Thus, although beneficial in some conditions, the AVs considered in this study are not likely to support Europe’s sustainability goals. Findings advocate a comprehensive approach: Whereas impacts are likely greatest in heavy traffic, the prevalence of conditions must be considered in network level assessment.