Citation

Reina P. Transp. Res. Interdiscip. Persp. 2021; 9: e100266.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trip.2020.100266

PMID

unavailable

Abstract

Rubbernecking on freeways is a common problem that arises when queuing traffic develops in the opposite direction of a freeway incident. The goals of this study are to evaluate the effects of rubbernecking on traffic, investigate incident and freeway characteristics associated with it, evaluate rubbernecking models, and analyze drivers' behavior in relationship to rubbernecking. To this end, traffic data around a major incident were analyzed.

RESULTS revealed that rubbernecking can instigate significant queue lengths, congestion durations, and traffic delays. In addition, analysis of 637 incidents revealed that 12% of incidents instigated rubbernecking queues. A logistic regression model was also fitted to the data.

RESULTS from the model suggest that on-ramps, high-occupancy vehicle (HOV) lanes, and percent of trucks are factors associated with rubbernecking. In addition, validation analyses of rubbernecking models pointed to limitations of estimated statistical models in effectively predicting rubbernecking events. Furthermore, results from a drivers' behavior self-reporting survey suggest that a majority of drivers tend to decrease their speed around an incident in the opposite direction of traffic. It was also observed that respondents attributed these actions to habits and behavior more frequently than incident and freeway characteristics.

FINDINGS from this work can be used to help develop targeted rubbernecking traffic control measures, enhance rubbernecking data collection methods and modeling, and advance behavioral interventions to reduce the onset of rubbernecking queues on freeways.

Language: en

Keywords

Empirical traffic analysis; Freeway incidents; Rubbernecking; Statistical modeling