A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs
With the development of smart cities and intelligent transportation systems, path planning in multi-scenario urban mobility has become increasingly complex. Traditional path-planning approaches typically focus on a single optimization objective, limiting their applicability in complex urban traffic...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/18/1/41 |
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| author | Zhaohui Wang Meng Zhang Shanqing Liang Shuang Yu Chengchun Zhang Sheng Du |
| author_facet | Zhaohui Wang Meng Zhang Shanqing Liang Shuang Yu Chengchun Zhang Sheng Du |
| author_sort | Zhaohui Wang |
| collection | DOAJ |
| description | With the development of smart cities and intelligent transportation systems, path planning in multi-scenario urban mobility has become increasingly complex. Traditional path-planning approaches typically focus on a single optimization objective, limiting their applicability in complex urban traffic systems. This paper proposes a multi-objective vehicle path-planning approach tailored for diverse scenarios, addressing multi-objective optimization challenges within complex road networks. The proposed method simultaneously considers multiple objectives, including total distance, congestion distance, travel time, energy consumption, and safety, and incorporates a dynamic weight-adjustment mechanism. This allows the algorithm to provide optimal route choices across four application scenarios: urban commuting; energy-efficient driving; holiday travel; and nighttime travel. Experimental results indicate that the proposed multi-objective planning algorithm outperforms traditional single-objective algorithms by effectively meeting user demands in various scenarios, offering an efficient solution to multi-objective optimization challenges in diverse environments. |
| format | Article |
| id | doaj-art-43c0d3cf7d9c4272807601a6e8a145ab |
| institution | Kabale University |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-43c0d3cf7d9c4272807601a6e8a145ab2025-01-24T13:17:35ZengMDPI AGAlgorithms1999-48932025-01-011814110.3390/a18010041A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility NeedsZhaohui Wang0Meng Zhang1Shanqing Liang2Shuang Yu3Chengchun Zhang4Sheng Du5China Satellite Network Digital Technology Co., Ltd., Xiong’an 070001, ChinaChina Satellite Network Digital Technology Co., Ltd., Xiong’an 070001, ChinaChina Satellite Network Digital Technology Co., Ltd., Xiong’an 070001, ChinaChina Satellite Network Digital Technology Co., Ltd., Xiong’an 070001, ChinaChina Satellite Network Digital Technology Co., Ltd., Xiong’an 070001, ChinaSchool of Automation, China University of Geosciences, Wuhan 430074, ChinaWith the development of smart cities and intelligent transportation systems, path planning in multi-scenario urban mobility has become increasingly complex. Traditional path-planning approaches typically focus on a single optimization objective, limiting their applicability in complex urban traffic systems. This paper proposes a multi-objective vehicle path-planning approach tailored for diverse scenarios, addressing multi-objective optimization challenges within complex road networks. The proposed method simultaneously considers multiple objectives, including total distance, congestion distance, travel time, energy consumption, and safety, and incorporates a dynamic weight-adjustment mechanism. This allows the algorithm to provide optimal route choices across four application scenarios: urban commuting; energy-efficient driving; holiday travel; and nighttime travel. Experimental results indicate that the proposed multi-objective planning algorithm outperforms traditional single-objective algorithms by effectively meeting user demands in various scenarios, offering an efficient solution to multi-objective optimization challenges in diverse environments.https://www.mdpi.com/1999-4893/18/1/41path planningurban travelsmart transportationmulti-objective optimization |
| spellingShingle | Zhaohui Wang Meng Zhang Shanqing Liang Shuang Yu Chengchun Zhang Sheng Du A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs Algorithms path planning urban travel smart transportation multi-objective optimization |
| title | A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs |
| title_full | A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs |
| title_fullStr | A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs |
| title_full_unstemmed | A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs |
| title_short | A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs |
| title_sort | multi objective path planning approach for multi scenario urban mobility needs |
| topic | path planning urban travel smart transportation multi-objective optimization |
| url | https://www.mdpi.com/1999-4893/18/1/41 |
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