Exploring turn signal usage patterns in lane changes: A Bayesian hierarchical modelling analysis of realistic driving data
Journal article, 2024

Using turn signals to convey a driver's intention to change lanes provides a direct and unambiguous way of communicating with nearby drivers. Nonetheless, past research has indicated that drivers may not always use their turn signals before starting a lane change. In this study, realistic driving data are analyzed to investigate turn signal usage during lane changes on highways in and around Gothenburg, Sweden. Turn signal usage is examined and factors that influence it are identified by employing Bayesian hierarchical modelling. The study found that drivers used their turn signal before changing lanes in 60% of cases, after starting the lane change in 33% of cases, and did not use it at all in 7% of cases. The Bayesian hierarchical modelling results indicate that various factors, such as the speed and direction of lane changes and the presence of surrounding vehicles, influence the usage of turn signals. The study concludes that understanding the factors affecting turn signal usage is crucial for improving traffic safety in current and future mixed traffic with autonomous vehicles. The study discusses the implications of findings concerning increasing turn signal compliance through general policy-making, improving existing in-vehicle technologies and including turn signal usage in Pay-As-You-Drive insurances.

Bayesian hierarchical modelling

Autonomous vehicles

Realistic driving data

Lane changing

Turn signal usage

Author

Sarang Jokhio

University of Ulm

Pierluigi Olleja

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Jonas Bärgman

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Fei Yan

University of Ulm

Martin Baumann

University of Ulm

IET Intelligent Transport Systems

1751-956X (ISSN) 1751-9578 (eISSN)

Vol. 18 2 393-408

Subject Categories

Probability Theory and Statistics

Signal Processing

DOI

10.1049/itr2.12457

More information

Latest update

3/7/2024 9