Incorporating car owner preferences for the introduction of economic incentives for speed limit enforcement

Incorporating car owner preferences for the introduction of economic incentives for speed limit enforcement

Sahebi, Sina (Sharif University of Technology)
Nassiri, Habibollah (Sharif University of Technology)
van Wee, G.P. (TU Delft Transport and Logistics)
Araghi, Y. (TU Delft Transport and Logistics; TNO)

2019

Human error including driving misbehavior contributes to over 90 percent of road vehicle accidents, and speeding is considered to be risky. Smart technologies, such as Connected Vehicle System (CVS) are among the interesting technical options to improve driving behavior, and Pay-As-You-Speed (PAYS) is an effective economic incentive to reduce speed violations. We investigated the acceptability of CVS with and without the presence of economic incentives, such as PAYS, in the context of a middle-income country: Iran. We used a Zero-Inflated Ordered Probit model (ZIOP) to estimate drivers’ willingness to pay for a CVS, and a hazard-based model for predicting the incentive level needed for accepting CVS via a PAYS scheme. ZIOP model indicated that drivers with the following characteristics were more likely to pay more for CVS: having a comprehensive insurance coverage, being younger than 60 years, owning more than one car, and having older vehicles. The hazard-based model also confirmed that drivers that speed relatively often have a lower tendency to adopt CVS, and drivers who experienced an accident in the past were more inclined to adopt CVS via PAYS. Also, drivers' opinion about CVS, vehicle characteristics, demographics, and driving experience influenced the effect of PAYS characteristics on acceptability of CVS. Finally, we offer recommendations for how to effectively implement CVS, in order to significantly reduce the high fatality and accident rates in middle-income countries such as Iran.

Connected Vehicle System
Parametric hazard-based model
Pay-As-You-Speed
Speed limit enforcement
Zero-Inflated Ordered Probit model

http://resolver.tudelft.nl/uuid:117dc3b1-dcb3-4d22-82a0-011cf8820312

https://doi.org/10.1016/j.trf.2019.05.014

2020-01-13

1369-8478

Transportation Research. Part F: Traffic Psychology and Behaviour, 64, 509-521

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2019 Sina Sahebi, Habibollah Nassiri, G.P. van Wee, Y. Araghi