Impacts of highly automated vehicles on travel demand: macroscopic modeling methods and some results

Artikel

Automated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific passenger car unit factors that depend on roadway type and the capabilities of the vehicles. The second extension enables travel demand models to calculate demand changes caused by a different perception of travel time as the active driving time is reduced. The presented methods are applied to a use case of a regional macroscopic travel demand model. The basic assumption is that AV are considered highly but not fully automated and still require a driver for parts of the trip. Model results indicate that first-generation AV, probably being rather cautious, may decrease traffic performance. Further developed AV will improve performance on some parts of the network. Together with a reduction in active driving time, cars will become even more attractive, resulting in a modal shift towards car. Both circumstances lead to an increase in time spent and distance traveled.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Transportation ; ISSN: 1572-9435 ; Volume: 49 ; Year: 2021 ; Issue: 3 ; Pages: 927-950 ; New York, NY: Springer US

Classification and Topics

• Classification: Handel, Kommunikation, Verkehr
• Subject: Automated vehicles ; Macroscopic travel demand model ; Traffic performance ; Perception of time ; CoEXist

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Sonnleitner, Jörg ; Friedrich, Markus ; Richter, Emely
• Event: Veröffentlichung
• (who): Springer US
• (where): New York, NY
• (when): 2021

Further information

• DOI: doi:10.1007/s11116-021-10199-z
• Last update: 10.03.2025, 11:45 AM CET