Identifying and Quantifying Factors Determining Dynamic Vanpooling Use
Nowadays, the growth of traffic congestion and emissions has led to the emergence of an innovative and sustainable transportation service, called dynamic vanpooling. The main aim of this study is to identify factors affecting the travel behavior of passengers due to the introduction of dynamic vanpo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Smart Cities |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-6511/4/4/66 |
| _version_ | 1797500550115229696 |
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| author | Konstantinos Tsiamasiotis Emmanouil Chaniotakis Moeid Qurashi Hai Jiang Constantinos Antoniou |
| author_facet | Konstantinos Tsiamasiotis Emmanouil Chaniotakis Moeid Qurashi Hai Jiang Constantinos Antoniou |
| author_sort | Konstantinos Tsiamasiotis |
| collection | DOAJ |
| description | Nowadays, the growth of traffic congestion and emissions has led to the emergence of an innovative and sustainable transportation service, called dynamic vanpooling. The main aim of this study is to identify factors affecting the travel behavior of passengers due to the introduction of dynamic vanpooling in the transportation system. A web-based mode choice survey was designed and implemented for this scope. The stated-preference experiments offered respondents binary hypothetical scenarios with an ordered choice between dynamic vanpool and the conventional modes of transport, private car and public transportation. In-vehicle travel time, total travel cost and walking and waiting time or searching time for parking varies across the choice scenarios. An ordered probit model, a multinomial logit model and two binary logit models were specified. The model estimation results indicate that respondents who are aged between 26 and 35 years old, commute with PT or are members of bike-sharing services were significantly more likely to choose dynamic vanpool or PT than private car. Moreover, respondents who are worried about climate change and are willing to spend more for environmentally friendly products are significantly more likely to use dynamic vanpool in comparison with private cars. Finally, to indicate the model estimation results for dynamic vanpool, the value of in-vehicle travel time is found to be 12.2€ per hour (13.4€ for Munich subsample). |
| first_indexed | 2024-03-10T03:05:26Z |
| format | Article |
| id | doaj.art-11ea92bd7d9c462b910de1bc4532f395 |
| institution | Directory Open Access Journal |
| issn | 2624-6511 |
| language | English |
| last_indexed | 2024-03-10T03:05:26Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Smart Cities |
| spelling | doaj.art-11ea92bd7d9c462b910de1bc4532f3952023-11-23T10:33:14ZengMDPI AGSmart Cities2624-65112021-09-01441243125810.3390/smartcities4040066Identifying and Quantifying Factors Determining Dynamic Vanpooling UseKonstantinos Tsiamasiotis0Emmanouil Chaniotakis1Moeid Qurashi2Hai Jiang3Constantinos Antoniou4TUM Department of Civil, Geo and Environmental Engineering, Technical University of Munich, Arcisstraße 21, 80333 Munich, GermanyMaaSLab, Energy Institute, University College London, 14 Upper Woburn Place, London WC1H 0NN, UKTUM Department of Civil, Geo and Environmental Engineering, Technical University of Munich, Arcisstraße 21, 80333 Munich, GermanyDepartment of Industrial Engineering, Tsinghua University, Beijing 100084, ChinaTUM Department of Civil, Geo and Environmental Engineering, Technical University of Munich, Arcisstraße 21, 80333 Munich, GermanyNowadays, the growth of traffic congestion and emissions has led to the emergence of an innovative and sustainable transportation service, called dynamic vanpooling. The main aim of this study is to identify factors affecting the travel behavior of passengers due to the introduction of dynamic vanpooling in the transportation system. A web-based mode choice survey was designed and implemented for this scope. The stated-preference experiments offered respondents binary hypothetical scenarios with an ordered choice between dynamic vanpool and the conventional modes of transport, private car and public transportation. In-vehicle travel time, total travel cost and walking and waiting time or searching time for parking varies across the choice scenarios. An ordered probit model, a multinomial logit model and two binary logit models were specified. The model estimation results indicate that respondents who are aged between 26 and 35 years old, commute with PT or are members of bike-sharing services were significantly more likely to choose dynamic vanpool or PT than private car. Moreover, respondents who are worried about climate change and are willing to spend more for environmentally friendly products are significantly more likely to use dynamic vanpool in comparison with private cars. Finally, to indicate the model estimation results for dynamic vanpool, the value of in-vehicle travel time is found to be 12.2€ per hour (13.4€ for Munich subsample).https://www.mdpi.com/2624-6511/4/4/66autonomous vehiclesdynamic vanpoolingemerging mobility |
| spellingShingle | Konstantinos Tsiamasiotis Emmanouil Chaniotakis Moeid Qurashi Hai Jiang Constantinos Antoniou Identifying and Quantifying Factors Determining Dynamic Vanpooling Use Smart Cities autonomous vehicles dynamic vanpooling emerging mobility |
| title | Identifying and Quantifying Factors Determining Dynamic Vanpooling Use |
| title_full | Identifying and Quantifying Factors Determining Dynamic Vanpooling Use |
| title_fullStr | Identifying and Quantifying Factors Determining Dynamic Vanpooling Use |
| title_full_unstemmed | Identifying and Quantifying Factors Determining Dynamic Vanpooling Use |
| title_short | Identifying and Quantifying Factors Determining Dynamic Vanpooling Use |
| title_sort | identifying and quantifying factors determining dynamic vanpooling use |
| topic | autonomous vehicles dynamic vanpooling emerging mobility |
| url | https://www.mdpi.com/2624-6511/4/4/66 |
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