Evaluating the impact of adaptive signal control technology on driver stress and behavior using real-world experimental data Zulqarnain H. Khattak a,⇑ , Michael D. Fontaine b , Richard A. Boateng a a Center for Transportation Studies, Department of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA 22904, United States b Virginia Transportation Research Council, 530 Edgemont Rd., Charlottesville, VA 22903, United States article info Article history: Received 16 November 2017 Received in revised form 6 June 2018 Accepted 7 June 2018 Keywords: Human factors Heart rate Driver stress Adaptive signal control technology Driving behavior Intelligent transportation systems Traffic safety GPS trajectories abstract While the operational and crash reduction benefits of adaptive signal control technology (ASCT) have long been investigated, the impact of this technology on driver behavior and stress is still uncertain. This study evaluated the impact of ASCT on driver behavior and stress in a real-world environment. Participants travelled through two arterial corri- dors, one equipped with ASCT and the other having traditional time-of-day coordinated signals. Driver stress was measured using a heart rate detector and a perceived stress scale while driver behavior was examined using vehicular trajectory data. Overall, driving behavior improved on the ASCT as compared to the non-ASCT corridor, as indicated by higher speeds and a fewer number of stops on the ASCT corridor relative to the non- ASCT corridor. Repeated measures ANOVA showed a statistically significant reduction in driver heart rate by À10 beats per minute over the ASCT corridor. A similar trend was observed for drivers’ perceived stress, analyzed by Wilcoxon sign ranked test. Driving behavior also showed significant improvement with ASCT presence, and speed was found to be negatively correlated with stress. Furthermore, the participants’ speed was controlled by the two systems i.e. ASCT and non-ASCT as expected. This study provides a significant proof of concept that ASCT can create positive improvements in driver stress and behavior that can be further investigated in the future. Ó 2018 Elsevier Ltd. All rights reserved. 1. Introduction Traffic safety is one of the major concerns for transportation engineers across the world, and a common cause of traffic crashes is human error. Driving is a complex cognitive phenomenon and stress levels may affect drivers’ abilities thus, lead- ing to decision making errors and crashes (Hill & Boyle, 2007). One study estimated that 30 percent of road crashes are caused by driver stress, thus making stress a major contributor to crashes (Aworemi, Abdul-Azeez, Oyedokun, & Adewoye, 2010). Similarly, Desmond and Matthews (2009) also recognized the importance of drivers’ stress as a potential safety problem, but noted that it may differ by individuals in response to the demands of driving. Adaptive signal control technology (ASCT) is an emerging method for operating traffic signals using real-time data. ASCT relies on improved intersection detection to determine traffic demands in real time. These demand data are then processed through an algorithm to adjust timing plans on-the-fly based on real time traffic volumes. This is in contrast to traditional https://doi.org/10.1016/j.trf.2018.06.006 1369-8478/Ó 2018 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail addresses: zk6cq@virginia.edu, zhkhattak@gmail.com (Z.H. Khattak), Michael.Fontaine@VDOT.Virginia.gov (M.D. Fontaine), ra3fb@virginia.edu (R.A. Boateng). Transportation Research Part F 58 (2018) 133–144 Contents lists available at ScienceDirect Transportation Research Part F journal homepage: www.elsevier.com/locate/trf