{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:31:38Z","timestamp":1778085098293,"version":"3.51.4"},"reference-count":28,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,12]],"date-time":"2025-01-12T00:00:00Z","timestamp":1736640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Industry\u2013University\u2013Research Cooperation Project","award":["2024-P-01-00001536-07-1453"],"award-info":[{"award-number":["2024-P-01-00001536-07-1453"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/a18010041","type":"journal-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T06:42:15Z","timestamp":1736750535000},"page":"41","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs"],"prefix":"10.3390","volume":"18","author":[{"given":"Zhaohui","family":"Wang","sequence":"first","affiliation":[{"name":"China Satellite Network Digital Technology Co., Ltd., Xiong\u2019an 070001, China"},{"name":"School of Computer, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Satellite Network Digital Technology Co., Ltd., Xiong\u2019an 070001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanqing","family":"Liang","sequence":"additional","affiliation":[{"name":"China Satellite Network Digital Technology Co., Ltd., Xiong\u2019an 070001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuang","family":"Yu","sequence":"additional","affiliation":[{"name":"China Satellite Network Digital Technology Co., Ltd., Xiong\u2019an 070001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengchun","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Satellite Network Digital Technology Co., Ltd., Xiong\u2019an 070001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8396-7388","authenticated-orcid":false,"given":"Sheng","family":"Du","sequence":"additional","affiliation":[{"name":"School of Automation, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Jin, B. 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