Non-Compliant Behaviour of Automated Vehicles in a Mixed Traffic Environment
Legal requirements for minimum distances between vehicles are often not met for short periods of time, especially when changing lanes on multi-lane roads. These situations are typically non-hazardous, as human drivers anticipate surrounding traffic, allowing for shorter headways and improved traffic flow. Automated vehicles (AVs), however, are typically designed to maintain strict headway limits, potentially reducing traffic efficiency. Therefore, legal questions arise as to whether mandatory gap and headway limits for AVs may be violated during periods of non-compliance. While traffic flow simulation is a common method for analyzing AV impacts, previous studies have typically modeled AV behavior using driver models originally designed to replicate human driving. These models are not well suited for representing clearly defined, structured non-compliant maneuvers, as they cannot simulate intentional, rule-deviating strategies. This paper addresses this gap by introducing a concept for AV non-compliant behavior and implementing it as a module within a pre-existing AV driver model. Simulations were conducted on a three-lane highway with an on-ramp under varying traffic volumes and AV penetration rates. The results showed that, with an AV-penetration rate of more than 25%, road capacity at highway entrances could be increased and travel times reduced by over 20%, provided that AVs were allowed to merge with a legal gap of 0.9 s and a minimum non-compliant gap of 0.6 s lasting up to 3 s. This suggests that performance gains are achievable under adjusted legal requirements. In addition, the proposed framework can serve as a foundation for further development of AV driver models aiming at improving traffic efficiency while maintaining regulatory compliance.
Authors
- Michael Haberl (ORCID: https://orcid.org/0000-0003-4779-7101)
- Martin Fellendorf (ORCID: https://orcid.org/0000-0001-5111-943X)
- Marlies Mischinger-Rodziewicz
- Felix Hofinger (ORCID: https://orcid.org/0000-0002-1566-6935)
Institutions
- Graz University of Technology (AT)
- Virtual Vehicle Research GmbH (Austria) (AT)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-07-14
- DOI
- https://doi.org/10.3390/app15147852
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Österreichische Forschungsförderungsgesellschaft
- Steirische Wirtschaftsförderungsgesellschaft
- Amt der Steiermärkischen Landesregierung