Effects of Intelligent Advanced Warnings on Drivers Negotiating the Dilemma Zone. (September 2014)

• Record Type: Journal Article
• Authors: Gugerty, Leo; McIntyre, Scott E.; Link, Drew; Zimmerman, Karl; Tolani, Devendra; Huang, Peter; Pokorny, Robert A.
• Is Part Of: Human factors. Volume 56:Number 6(2014)
• Page Start: 1021
• Page End: 1035
• Publication Date: 2014-09
• Subjects: driving simulator -- human factors; Human engineering -- Periodicals; 620.82
• DOI: 10.1177/0018720814525438
• Languages: English
• ISSNs: 0018-7208

Abstract

Objective: We investigated whether intelligent advanced warnings of the end of green traffic signals help drivers negotiate the dilemma zone (DZ) at signalized intersections and sought to identify behavioral mechanisms for any warning-related benefits. Background: Prior research suggested that warnings of end of green can increase slowing and stopping frequency given the DZ, but drivers may sometimes respond to warnings by speeding up. Method: In two simulator studies, we compared six types of roadway or in-vehicle warnings with a no-warning control condition. Using multilevel modeling, we tested mediation models of the behavioral mechanisms underlying the effects of warnings. Results: In both studies, warnings led to more stopping at DZ intersections and milder decelerations when stopping compared with no warning. Drivers' predominant response to warnings was anticipatory slowing on approaching the intersection, not speeding up. The increased stopping with warning was mediated by increased slowing. In Study 1, anticipatory slowing given warnings generalized to green-light intersections where no warning was given. In Study 2, we found that lane-specific warnings (e.g., LED lights embedded in each lane) sometimes led to fewer unsafe emergency stops than did non-lane-specific roadside warnings. Conclusion: End-of-green warnings led to safer behavior in the DZ and on the early approach to intersections. The main mechanism for the benefits of warnings was drivers' increased anticipatory slowing on approaching an intersection. Lane-specific warnings may have some benefits over roadside warnings. Application: Applications include performance models of how drivers use end-of-green warnings, control algorithms and warning displays for intelligent intersections, and statistical methodology in human factors research.