Driver speed compliance following automatic incident detection

Insights from a naturalistic driving study

Journal Article (2021)
Author(s)

Silvia F. Varotto (Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV))

Reinier Jansen (Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV))

Frits Bijleveld (Vrije Universiteit Amsterdam, Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV))

N. Nes (Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV), TU Delft - Human Factors)

Research Group
Human Factors
Copyright
© 2021 Silvia F. Varotto, Reinier Jansen, Frits Bijleveld, C.N. van Nes
DOI related publication
https://doi.org/10.1016/j.aap.2020.105939
More Info
expand_more
Publication Year
2021
Language
English
Copyright
© 2021 Silvia F. Varotto, Reinier Jansen, Frits Bijleveld, C.N. van Nes
Research Group
Human Factors
Volume number
150
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Automatic incident detection (AID) systems and variable speed limits (VSLs) can reduce crash probability and traffic congestion. Studies based on loop detector data have shown that AID systems decrease the variation in speeds between drivers. Despite the impact on driver behaviour characteristics, most mathematical models evaluating the effect of AID systems on traffic operations do not capture driver response realistically. This study examines the main factors related to driver speed compliance with a sequence of three VSLs triggered by an AID system. For this purpose, the variable speed limit database of the executive agency of the Dutch Ministry of Infrastructure and Water Management (Rijkswaterstaat) was integrated into the UDRIVE naturalistic driving database for passenger car data collected in the Netherlands. The video data were annotated to analyse driver glance behaviour and secondary task engagement. A logistic regression model was estimated to predict driver speed compliance after each VSL in the sequence. The results reveal that the factors predicting compliance to the VSLs differ based on which of the three VSLs the driver is subjected to. Low speeds and accelerations before the gantry, approaching a slower leader, high proportion of time with eyes-on-road and close consecutive gantries were associated with high compliance with the first VSL in the sequence (i.e., indicating a speed limit of 70 km/h with flashing attention lights). Low speeds and accelerations before the gantry, close consecutive gantries and a small number of lanes resulted in high compliance with the second VSL (i.e., a speed limit of 50 km/h with flashing attention lights). Low speeds before the gantry and close consecutive gantries were linked to high compliance with the third VSL (i.e., indicating a speed limit of 50 km/h). Although further investigations based on a larger sample are needed, these findings are relevant to the development of human-like driving assistance systems and of traffic simulations that assess the impact of AID systems on traffic operations realistically.

Files

1_s2.0_S0001457520317590_main.... (pdf)
(pdf | 2.11 Mb)
- Embargo expired in 01-07-2023
License info not available