{"title":"量子退火相关技术在交通优化中的应用综述","authors":"Marwan Qaid Mohammed, Henri Meeß, Maximilian Otte","doi":"10.1007/s11128-025-04870-y","DOIUrl":null,"url":null,"abstract":"<div><p>Traffic optimization remains a significant challenge in urban planning and transportation management. While efficient traffic optimization is crucial for enhancing urban mobility, reducing congestion, and promoting environmental sustainability, traditional computational methods often struggle with the complex, dynamic nature of traffic systems. Recent advances in quantum computing, particularly quantum annealing, offer promising new techniques that could revolutionize traffic flow optimization. This work systematically reviews the literature, starting with search term formulation and ending with the final set of articles. These articles are categorized into three groups: (1) traffic signal control, (2) traffic flow optimization, and (3) routing problems optimization (including vehicle routing problem and traveling salesman problem). The review critically examines current studies on quantum annealing-based traffic optimization, focusing on contributions, methods, solvers, problem suitability, key findings, benchmark fairness, and limitations. It identifies key challenges and provides recommendations for future research. Insights from this work offer researchers and practitioners a concise overview of current challenges and future directions in traffic optimization.</p></div>","PeriodicalId":746,"journal":{"name":"Quantum Information Processing","volume":"24 9","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11128-025-04870-y.pdf","citationCount":"0","resultStr":"{\"title\":\"Review of the application of quantum annealing-related technologies in transportation optimization\",\"authors\":\"Marwan Qaid Mohammed, Henri Meeß, Maximilian Otte\",\"doi\":\"10.1007/s11128-025-04870-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Traffic optimization remains a significant challenge in urban planning and transportation management. While efficient traffic optimization is crucial for enhancing urban mobility, reducing congestion, and promoting environmental sustainability, traditional computational methods often struggle with the complex, dynamic nature of traffic systems. Recent advances in quantum computing, particularly quantum annealing, offer promising new techniques that could revolutionize traffic flow optimization. This work systematically reviews the literature, starting with search term formulation and ending with the final set of articles. These articles are categorized into three groups: (1) traffic signal control, (2) traffic flow optimization, and (3) routing problems optimization (including vehicle routing problem and traveling salesman problem). The review critically examines current studies on quantum annealing-based traffic optimization, focusing on contributions, methods, solvers, problem suitability, key findings, benchmark fairness, and limitations. It identifies key challenges and provides recommendations for future research. Insights from this work offer researchers and practitioners a concise overview of current challenges and future directions in traffic optimization.</p></div>\",\"PeriodicalId\":746,\"journal\":{\"name\":\"Quantum Information Processing\",\"volume\":\"24 9\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s11128-025-04870-y.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantum Information Processing\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11128-025-04870-y\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, MATHEMATICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantum Information Processing","FirstCategoryId":"101","ListUrlMain":"https://link.springer.com/article/10.1007/s11128-025-04870-y","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, MATHEMATICAL","Score":null,"Total":0}
Review of the application of quantum annealing-related technologies in transportation optimization
Traffic optimization remains a significant challenge in urban planning and transportation management. While efficient traffic optimization is crucial for enhancing urban mobility, reducing congestion, and promoting environmental sustainability, traditional computational methods often struggle with the complex, dynamic nature of traffic systems. Recent advances in quantum computing, particularly quantum annealing, offer promising new techniques that could revolutionize traffic flow optimization. This work systematically reviews the literature, starting with search term formulation and ending with the final set of articles. These articles are categorized into three groups: (1) traffic signal control, (2) traffic flow optimization, and (3) routing problems optimization (including vehicle routing problem and traveling salesman problem). The review critically examines current studies on quantum annealing-based traffic optimization, focusing on contributions, methods, solvers, problem suitability, key findings, benchmark fairness, and limitations. It identifies key challenges and provides recommendations for future research. Insights from this work offer researchers and practitioners a concise overview of current challenges and future directions in traffic optimization.
期刊介绍:
Quantum Information Processing is a high-impact, international journal publishing cutting-edge experimental and theoretical research in all areas of Quantum Information Science. Topics of interest include quantum cryptography and communications, entanglement and discord, quantum algorithms, quantum error correction and fault tolerance, quantum computer science, quantum imaging and sensing, and experimental platforms for quantum information. Quantum Information Processing supports and inspires research by providing a comprehensive peer review process, and broadcasting high quality results in a range of formats. These include original papers, letters, broadly focused perspectives, comprehensive review articles, book reviews, and special topical issues. The journal is particularly interested in papers detailing and demonstrating quantum information protocols for cryptography, communications, computation, and sensing.