Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network
Electric vehicles (EVs) are one of the most promising applications that are reshaping the future urban mobility market and benefitting the urban environment. Analyzing the adoption of EVs helps both vehicle sales market management and urban transportation-related environmental cost estimation. Previ...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/11/3/149 |
| _version_ | 1797608857495666688 |
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| author | Jie Ma Yu Zhu Dawei Chen Chenhao Zhang Maocan Song Honggang Zhang Jingxu Chen Kai Zhang |
| author_facet | Jie Ma Yu Zhu Dawei Chen Chenhao Zhang Maocan Song Honggang Zhang Jingxu Chen Kai Zhang |
| author_sort | Jie Ma |
| collection | DOAJ |
| description | Electric vehicles (EVs) are one of the most promising applications that are reshaping the future urban mobility market and benefitting the urban environment. Analyzing the adoption of EVs helps both vehicle sales market management and urban transportation-related environmental cost estimation. Previous studies have shown that EV adoption is mostly affected by the economic environment and users’ psychological factors; however, both factors vary among specific urban transportation networks. This paper thus proposes network-related vehicle operating cost functions and a logit-based choice model, which considers both the economic environment and users’ psychological factors at a network level. The model can thus estimate the vehicle adoption for specific networks. Numerical experiments and sensitivity analyses were conducted to illustrate the proposed method and provide practical insights in estimating EV adoption, respectively. The results suggest that EV adoption greatly varies among different cities. |
| first_indexed | 2024-03-11T05:49:25Z |
| format | Article |
| id | doaj.art-8fb5c65dcc6248d8a1b24565538699e8 |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-11T05:49:25Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-8fb5c65dcc6248d8a1b24565538699e82023-11-17T14:11:24ZengMDPI AGSystems2079-89542023-03-0111314910.3390/systems11030149Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation NetworkJie Ma0Yu Zhu1Dawei Chen2Chenhao Zhang3Maocan Song4Honggang Zhang5Jingxu Chen6Kai Zhang7School of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaElectric vehicles (EVs) are one of the most promising applications that are reshaping the future urban mobility market and benefitting the urban environment. Analyzing the adoption of EVs helps both vehicle sales market management and urban transportation-related environmental cost estimation. Previous studies have shown that EV adoption is mostly affected by the economic environment and users’ psychological factors; however, both factors vary among specific urban transportation networks. This paper thus proposes network-related vehicle operating cost functions and a logit-based choice model, which considers both the economic environment and users’ psychological factors at a network level. The model can thus estimate the vehicle adoption for specific networks. Numerical experiments and sensitivity analyses were conducted to illustrate the proposed method and provide practical insights in estimating EV adoption, respectively. The results suggest that EV adoption greatly varies among different cities.https://www.mdpi.com/2079-8954/11/3/149electric vehicle adoptionvehicle ownershipoperating costlogit choice modelurban transportation network |
| spellingShingle | Jie Ma Yu Zhu Dawei Chen Chenhao Zhang Maocan Song Honggang Zhang Jingxu Chen Kai Zhang Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network Systems electric vehicle adoption vehicle ownership operating cost logit choice model urban transportation network |
| title | Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network |
| title_full | Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network |
| title_fullStr | Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network |
| title_full_unstemmed | Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network |
| title_short | Analysis of Urban Electric Vehicle Adoption Based on Operating Costs in Urban Transportation Network |
| title_sort | analysis of urban electric vehicle adoption based on operating costs in urban transportation network |
| topic | electric vehicle adoption vehicle ownership operating cost logit choice model urban transportation network |
| url | https://www.mdpi.com/2079-8954/11/3/149 |
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