A Preliminary Investigation of the Effectiveness of High Visibility Enforcement Programs Using Naturalistic Driving Study Data: A Grouped Random Parameters Approach

Sonduru Pantangi, Sarvani; Fountas, Grigorios; Sarwar, Md Tawfiq; Anastasopoulos, Panagiotis Ch.; Blatt, Alan; Majka, Kevin; Pierowicz, John; Mohan, Satish B.

Abstract

This paper seeks to assess the effectiveness of high-visibility enforcement (HVE) programs in terms of reducing aggressive driving behavior. Using Strategic Highway Research Program 2 (SHRP2) Naturalistic driving study (NDS) data, behavioral reactions of drivers before, during, and after the conduct of high-visibility enforcement programs are analyzed, in order to identify the potential effect of high-visibility enforcement in driving behavior. In this context, two fundamental aspects of aggressive driving behavior (speeding and tailgating) are employed and analyzed. To simultaneously explore the intensity and the duration of these behavioral patterns, novel metrics are defined and used in the analysis. To investigate the effect of high-visibility enforcement programs, and at the same time, to control for the effect of driver-, trip-, vehicle-, and weather-specific characteristics on the extent of speeding and tailgating, univariate grouped random parameters linear regression models are estimated. In addition, likelihoods of speeding and tailgating occurrences are analyzed simultaneously, within a grouped random parameters bivariate probit modeling framework. The results of this preliminary analysis show that even though the implementation of the high-visibility enforcement has mixed effects on the extent and the likelihood of the driving behavior metrics, it demonstrates a promising potential in modifying driving behavior

Citation

Sonduru Pantangi, S., Fountas, G., Sarwar, M. T., Anastasopoulos, P. C., Blatt, A., Majka, K., Pierowicz, J., & Mohan, S. B. (2019). A Preliminary Investigation of the Effectiveness of High Visibility Enforcement Programs Using Naturalistic Driving Study Data: A Grouped Random Parameters Approach. Analytic Methods in Accident Research, 21, 1-12. https://doi.org/10.1016/j.amar.2018.10.003

• Journal Article Type: Article
• Acceptance Date: Oct 24, 2018
• Online Publication Date: Feb 22, 2019
• Publication Date: 2019-03
• Deposit Date: Nov 28, 2018
• Publicly Available Date: Aug 23, 2020
• Journal: Analytic methods in Accident Research
• Print ISSN: 2213-6657
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 21
• Pages: 1-12
• DOI: https://doi.org/10.1016/j.amar.2018.10.003
• Keywords: High-visibility enforcement; Speeding; Tailgating; Aggressive driving behavior; Grouped random parameters
• Public URL: http://researchrepository.napier.ac.uk/Output/1396802
• Contract Date: Nov 28, 2018