Data-driven ecological driving behaviour evaluation and green supply chain improvement
In the 14th Five-Year Plan, China has emphasized the importance of promoting green development, and the policy once again emphasized the importance of promoting energy conservation, thus improving the green supply chain. This dissertation delves into eco-driving evaluation and its crucial role...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/174109 |
| _version_ | 1824454637627899904 |
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| author | Zhou, Zhongcan |
| author2 | Chen Songlin |
| author_facet | Chen Songlin Zhou, Zhongcan |
| author_sort | Zhou, Zhongcan |
| collection | NTU |
| description | In the 14th Five-Year Plan, China has emphasized the importance of promoting green
development, and the policy once again emphasized the importance of promoting
energy conservation, thus improving the green supply chain. This dissertation delves
into eco-driving evaluation and its crucial role in improving the green supply chain.
Initially, over 3 million GPS trajectory data pieces were collected, enabling trip
construction and feature extraction. Subsequently, short trips were classified and
matched based on OSM road data, then the remaining 198529 pieces of short trips
are clustered via Kmeans algorithms, resulting in 20 driving status categories across
five road types. After that, an energy consumption model and eco-driving evaluation
model were constructed in order to calculate the number for all short trips. Next
chapter clarify the results and explain the relationships among road types, driving
status and eco-driving scores. This dissertation also shows the relationship between
eco-driving and green supply chain improvement, offering actionable strategies from
the aspects of supplier testing, logistics optimization, and technological innovation.
This dissertation shows its practical significance in amplifying sustainability within
the green supply chain. |
| first_indexed | 2025-02-19T03:25:29Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/174109 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:25:29Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1741092024-03-23T16:51:43Z Data-driven ecological driving behaviour evaluation and green supply chain improvement Zhou, Zhongcan Chen Songlin School of Mechanical and Aerospace Engineering Songlin@ntu.edu.sg Engineering Green supply chain improvement Eco-driving Short trips Clustering Energy consumption In the 14th Five-Year Plan, China has emphasized the importance of promoting green development, and the policy once again emphasized the importance of promoting energy conservation, thus improving the green supply chain. This dissertation delves into eco-driving evaluation and its crucial role in improving the green supply chain. Initially, over 3 million GPS trajectory data pieces were collected, enabling trip construction and feature extraction. Subsequently, short trips were classified and matched based on OSM road data, then the remaining 198529 pieces of short trips are clustered via Kmeans algorithms, resulting in 20 driving status categories across five road types. After that, an energy consumption model and eco-driving evaluation model were constructed in order to calculate the number for all short trips. Next chapter clarify the results and explain the relationships among road types, driving status and eco-driving scores. This dissertation also shows the relationship between eco-driving and green supply chain improvement, offering actionable strategies from the aspects of supplier testing, logistics optimization, and technological innovation. This dissertation shows its practical significance in amplifying sustainability within the green supply chain. Master's degree 2024-03-18T08:20:19Z 2024-03-18T08:20:19Z 2023 Thesis-Master by Coursework Zhou, Z. (2023). Data-driven ecological driving behaviour evaluation and green supply chain improvement. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/174109 https://hdl.handle.net/10356/174109 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering Green supply chain improvement Eco-driving Short trips Clustering Energy consumption Zhou, Zhongcan Data-driven ecological driving behaviour evaluation and green supply chain improvement |
| title | Data-driven ecological driving behaviour evaluation and green supply chain improvement |
| title_full | Data-driven ecological driving behaviour evaluation and green supply chain improvement |
| title_fullStr | Data-driven ecological driving behaviour evaluation and green supply chain improvement |
| title_full_unstemmed | Data-driven ecological driving behaviour evaluation and green supply chain improvement |
| title_short | Data-driven ecological driving behaviour evaluation and green supply chain improvement |
| title_sort | data driven ecological driving behaviour evaluation and green supply chain improvement |
| topic | Engineering Green supply chain improvement Eco-driving Short trips Clustering Energy consumption |
| url | https://hdl.handle.net/10356/174109 |
| work_keys_str_mv | AT zhouzhongcan datadrivenecologicaldrivingbehaviourevaluationandgreensupplychainimprovement |