Sustainable impact of urban road class on smart transportation systems: A field data-informed exploration

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2025-09-04 DOI:10.1016/j.scs.2025.106792

Bin Sun , Qiang Bai , Qijun Zhang , Hongjun Mao

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引用次数: 0

Abstract

Urban transportation systems face critical sustainability challenges, including congestion and carbon emissions, where the Speed Guidance System (SGS) serves as a key smart technology. However, systematic analysis of its context-dependent impacts—particularly across urban road classes—remains limited, hindering optimized deployment. This study addresses this gap by leveraging field data from Zibo City, collecting and processing millions of vehicle trajectory records using the SGS, categorized by road class (branch, minor arterial, arterial, expressway). Through sustainability metrics (travel comfort, delay, carbon emissions), the analysis reveals significant road-class variations in SGS optimization effects. Results show that SGS performance differs markedly by road class: it degrades sustainability on branch roads (increasing delays by 11 % and emissions by 1-16 %) but optimizes minor arterials most effectively (reducing delays by 20 % and emissions by 2 %). Crucially, driver inexperience reduces comfort by 11-29 % across classes, while emission peaks controlled near 60 km/h enable superior decarbonization on minor arterials. Based on partial correlation analysis, the study develops road-class-specific carbon emission regression models and proposes three targeted strategies (e.g., Prioritizing minor arterial deployment). This work advances intelligent transportation by providing a data-informed understanding of SGS's sustainable impacts under varying urban contexts.

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城市道路类别对智能交通系统的可持续影响：实地数据信息探索

城市交通系统面临着严峻的可持续性挑战，包括拥堵和碳排放，其中速度引导系统（SGS）是一项关键的智能技术。然而，对其环境相关影响的系统分析仍然有限，特别是在城市道路类别中，这阻碍了优化部署。本研究利用淄博市的现场数据，利用SGS收集和处理数百万条车辆轨迹记录，按道路类别（支路、小干道、主干道、高速公路）分类，弥补了这一空白。通过可持续性指标（出行舒适度、延迟、碳排放），分析发现不同道路等级的SGS优化效果存在显著差异。结果表明，SGS的性能因道路类别而有显著差异：它降低了分支道路的可持续性（增加11%的延误和1- 16%的排放），但优化次要动脉最有效（减少20%的延误和2%的排放）。最重要的是，驾驶员经验不足会使不同级别的舒适性降低11% - 29%，而排放峰值控制在60公里/小时附近，可以在次要动脉上实现卓越的脱碳。在偏相关分析的基础上，建立了特定道路类别的碳排放回归模型，并提出了三种有针对性的策略（如优先考虑小动脉部署）。这项工作通过提供基于数据的SGS在不同城市环境下的可持续影响的理解来推进智能交通。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sustainable Cities and Society Social Sciences-Geography, Planning and Development

CiteScore

22.00

自引率

13.70%

发文量

810

审稿时长

27 days

期刊介绍： Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;