10 citations · 11 across the 5 of their papers we have counts for
5 papers
Improving Crash Frequency Prediction from Simulated Traffic Conflicts Using Machine Learning Based Microsimulation
Xian Liu, Carlo G. Prato, Gustav Markkula
Traffic microsimulation combined with surrogate safety measures has increasingly been used as a proactive alternative to historical crash data for predicting crash frequency for cu…
Knowing When to Move: Evidence Accumulation Models of Human Behavior in Traffic
Floor Bontje, Felix van Waveren, Leendert van Maanen +3
Evidence accumulation models provide a formal framework for studying decision making as a dynamic process unfolding over time. While these models have been extensively developed an…
Automated Brake Onset Detection in Naturalistic Driving Data
Shu-Yuan Liu, Johan Engström, Gustav Markkula
Response timing measures play a crucial role in the assessment of automated driving systems (ADS) in collision avoidance scenarios, including but not limited to establishing human…
Looking for an out: Affordances, uncertainty and collision avoidance behavior of human drivers
Leif Johnson, Johan Engström, Aravinda Srinivasan +2
Understanding collision avoidance behavior is of key importance in traffic safety research and for designing and evaluating advanced driver assistance systems and autonomous vehicl…
Validation of human benchmark models for Automated Driving System approval: How competent and careful are they really?
Pierluigi Olleja, Gustav Markkula, Jonas Bärgman
Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) are expected to improve comfort, productivity and, most importantly, safety for all road users. To ens…