An invariant may drive the decision to encroach at unsignalized intersections
Paper i proceeding, 2009

This paper introduces a novel approach to understanding when and where drivers make the Go / No Go decision (not) to turn left and encroach upon an approaching car that has the right-of-way in an unsignalized intersection. The source of data is approximately 2,400 hours of video recordings at two intersections near Göteborg, Sweden. Automated image processing software extracted the trajectories of the pairs of cars involved in more than 14,000 left turns across traffic at the first intersection and 2,400 at the second. We subdivided the data into four different left-turn scenarios - where the approaching car arrives from the opposite direction, from the lateral direction, from the intended direction (merging), and while making its own left turn. For each scenario, we found the distances between the turning car and the approaching car at the time when we can assume the decision (not) to turn is made and conducted logistic regressions to identify the distances associated with the 50/50 acceptance probabilities for the decision (not) to turn. We also calculated the resulting encroachment distances (‘trailing buffers’) for every decision to turn. We expected to find wide variability in these buffers. Instead, we observed separations that were virtually the same across scenarios at each intersection but differed across intersections. Tacit, intersection-dependent knowledge of this invariant may drive the decision of whether or not to turn and encroach. We discuss the implications this finding has for the design of in-vehicle active safety systems.

Intersection

driver behavior

gap acceptance

Författare

Kip Smith

Chalmers, Tillämpad mekanik, Fordonssäkerhet

Aurélie Thome

Chalmers, Tillämpad mekanik, Fordonssäkerhet

Christian Blåberg

Chalmers, Tillämpad mekanik, Fordonssäkerhet

Jonas Bärgman

Chalmers, Tillämpad mekanik, Fordonssäkerhet

PROCEEDINGS of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design

313-319

Ämneskategorier

Maskinteknik

Tillämpad psykologi

Människa-datorinteraktion (interaktionsdesign)

Drivkrafter

Hållbar utveckling

Styrkeområden

Transport

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2017-10-07