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This study is aimed at supporting left-turn assist (LTA) applications, which provide warnings to drivers making a left turn across the path of oncoming traffic (LTAP/OD scenarios). The primary goal was to provide much-needed information on typical or “baseline” driving in LTAP/OD scenarios that can be used to refine alert criteria to reduce false and nuisance alerts. A secondary goal was to provide performance data useful for informing practical test procedures, e.g., setting turning speed when evaluating LTA applications on a test track. To accomplish this, LTAP/OD events were identified in the databases of two large-scale naturalistic driving studies. For these events, we estimated the size of the gaps in oncoming traffic into which drivers chose to turn, what factors (environmental, demographic, etc.) affected the choice to turn into a gap of a given size, and the speed profiles throughout each turn.

An understanding of the relationship between user acceptance and system effectiveness is necessary for designing collision warning systems for cars and for accurately estimating their safety benefits. To better understand this relationship, an exploration was conducted into the results of a recent naturalistic field operational test of an integrated vehicle-based safety system installed into a fleet of passenger vehicles. Correlation analyses were conducted for system effectiveness, which was measured in terms of near-crash reduction, and for user acceptance, which was measured using responses to a questionnaire that drivers filled out after completing the study. The key findings were as follows: (1) although remaining generally positive overall, user acceptance decreased slightly for drivers as system effectiveness increased.