Do High Visibility Enforcement Programs Affect Aggressive Driving Behavior? An Empirical Analysis Using Naturalistic Driving Study Data
| Autor: | John Pierowicz, Panagiotis Ch. Anastasopoulos, Grigorios Fountas, Kevin Majka, Sarvani Sonduru Pantangi, Alan Blatt |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Male
Computer science Applied psychology Poison control Human Factors and Ergonomics Ordered probit Affect (psychology) Tailgating High-visibility enforcement Aggressive Driving Behavior Injury prevention Humans Duration (project management) Unsafe lane changes Aggressive Driving Safety Risk Reliability and Quality Speeding Grouped random parameters Accidents Traffic Public Health Environmental and Occupational Health Videotape Recording Human factors and ergonomics Social Control Formal Aggressive driving Logistic Models Female |
| ISSN: | 0001-4575 |
| Popis: | This paper investigates the effect of High Visibility Enforcement (HVE) programs on different types of aggressive driving behavior, namely, speeding, tailgating, unsafe lane changes and 'other' aggressive driving behavior types (occurrence of not-yielding right-of-way and red light or stop signs violations). For this purpose, the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) data are used, which include forward-facing videos and time series information with regard to trips conducted at or near the locations of HVE implementation. To capture the intensity and duration of speeding and tailgating, scaled metrics are developed. These metrics can capture varying levels of aggressive driving behavior enabling, thus, a direct comparison of the various behavioral aspects over time and among different drivers. To identify the effect of HVE and other trip, driver, vehicle or environmental factors on speeding and tailgating, while accounting for possible interrelationship among the behavior-specific scaled metrics, Seeming Unrelated Regression Equation (SURE) models were developed. To analyze the likelihood of occurrence of unsafe lane changes and 'other' aggressive driving behavior types, a grouped random parameters ordered probit model with heterogeneity in means and a correlated grouped random parameters binary logit model were estimated, respectively. The results showed that drivers' awareness of HVE implementation has the potential to decrease aggressive driving behavior patterns, especially unsafe lane changes and 'other' aggressive driving behaviors. |
| Databáze: | OpenAIRE |
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