期刊
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
卷 156, 期 -, 页码 270-284出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tra.2022.01.009
关键词
Pay-How-You-Drive; Questionnaire survey; Eco-driving; Value-of-time; Interpretable machine learning; User profiling
资金
- European Regional Development Fund of the European Union [T2EDK-03966]
- Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation
A novel scheme is proposed to investigate the acceptance of a Pay-How-You-Drive (PHYD) road pricing system in Athens, Greece. Findings reveal that the percent of travel time increase and the offered discount are the most important determinants of the system's acceptance.
In order to investigate the acceptance of a Pay-How-You-Drive (PHYD) road pricing system in Athens, Greece, a novel scheme is proposed which is designed to provide recommendations to the drivers in order to change their behavior towards a more ecological one and charges more those that would not follow them. For modeling the acceptance of the system's recommendations, first, a stated preferences questionnaire survey was designed and conducted on 600 drivers. Next, several Machine Learning models were developed to identify the characteristics that may affect the acceptance of such a scheme. To enrich the modeling process, a clustering framework was exploited to separate the respondents into different profiles, based on their mobility pattern and their attitude towards eco-driving. Furthermore, novel interpretation techniques, namely the calculation of permutation importance and partial dependence, were applied to gain a deeper understanding of the models' outputs. Findings revealed that the percent of travel time increase when following the system's recommendation and the offered discount are the most important determinants of the system's acceptance. More specifically, the estimation of the value of time showed that those who would drive ecologically would expect a discount of 0.21euro for each minute of additional travel time. The results of this research can be exploited in the design of fair toll systems that will meet the requirements of potential users, as well as the needs of demand responsive and eco-friendly urban road networks.
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