Willingness-to-pay for automated vehicles: A random parameters and random thresholds HOPIT model. Shabanpour, R., Golshani, N., Auld, J., & Mohammadian, A. In International Choice Modelling Conference 2017, March, 2017. Paper abstract bibtex It is argued that CAVs technology may significantly change both transportation demand and supply sides. However, their potential impacts have yet to be understood and incorporated into transportation plans. In an effort to understand public acceptance and adoption of these technologies, this paper presents the results of a recent internet-based survey conducted in Chicago Metropolitan area. An extended version of Hierarchical Ordered Probit model is presented to estimate respondents’ willingness to pay (WTP) for adding partial automation (Level 3) and full automation (Level 4) to their next vehicle purchase. Survey results indicate that average WTP for adding level 3 is \$3225 and for adding level 4 is \$5475. It is also found that possibility of imperfect performance in response to unexpected traffic situations is the most critical concern of the respondents, while having more productive use of time in the vehicle and experiencing less stressful driving are the most anticipated benefits. Respondents with higher income, those who regularly drive to workplace, those who anticipates higher safety and better fuel efficiency from CAVs, and technology-savvy individuals have greater interest in and higher WTP for the new vehicle technologies. The analysis of estimation results reveals that the proposed random parameters random thresholds HOPIT model is statistically superior to its counterparts in terms of goodness-of-fit measures and prediction accuracy.
@inproceedings{shabanpour_willingness--pay_2017,
title = {Willingness-to-pay for automated vehicles: {A} random parameters and random thresholds {HOPIT} model},
copyright = {Papers presented at the Conference of Choice Modelling are licensed under a Creative Commons Attribution-Non-Commercial 2.0 UK: England \& Wales License ( http://creativecommons.org/licenses/by-nc/2.0/uk/ ). By submitting a paper, authors will agree to have their work made available on the conference website. The authors retain the right to: - use the paper on personal or institutional websites - distribute their paper via e-mail or other means, including the version hosted on the conference website - publish the paper in a journal or book after the end of the conference},
shorttitle = {Willingness-to-pay for automated vehicles},
url = {https://anl.box.com/s/iz1hnkphizadjmcbzukb2dzpom8hrds6},
abstract = {It is argued that CAVs technology may significantly change both transportation demand and supply sides. However, their potential impacts have yet to be understood and incorporated into transportation plans. In an effort to understand public acceptance and adoption of these technologies, this paper presents the results of a recent internet-based survey conducted in Chicago Metropolitan area. An extended version of Hierarchical Ordered Probit model is presented to estimate respondents’ willingness to pay (WTP) for adding partial automation (Level 3) and full automation (Level 4) to their next vehicle purchase. Survey results indicate that average WTP for adding level 3 is \$3225 and for adding level 4 is \$5475. It is also found that possibility of imperfect performance in response to unexpected traffic situations is the most critical concern of the respondents, while having more productive use of time in the vehicle and experiencing less stressful driving are the most anticipated benefits. Respondents with higher income, those who regularly drive to workplace, those who anticipates higher safety and better fuel efficiency from CAVs, and technology-savvy individuals have greater interest in and higher WTP for the new vehicle technologies. The analysis of estimation results reveals that the proposed random parameters random thresholds HOPIT model is statistically superior to its counterparts in terms of goodness-of-fit measures and prediction accuracy.},
language = {en},
urldate = {2019-09-10},
booktitle = {International {Choice} {Modelling} {Conference} 2017},
author = {Shabanpour, Ramin and Golshani, Nima and Auld, Joshua and Mohammadian, Abolfazl},
month = mar,
year = {2017},
keywords = {POLARIS},
}
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