用AI分析迪拜与利雅得交通与民众情绪，优化城市出行体验
Traffic and Mobility Optimization Using AI: Comparative Study between Dubai and Riyadh
- 结合实时路况与地理位置情绪数据，构建动态交通分析模型
- 识别出两地交通拥堵热点及居民不满区域，定位问题节点
- 为中东城市提供可落地的交通优化方案，适合政策制定者参考
城市规划在现代城市发展中的作用至关重要，影响经济增速、生活质量与环境可持续性。快速城市化导致交通拥堵问题日益严峻。本研究探讨人工智能如何帮助理解交通与出行相关问题及其对居民情绪的影响。方法融合实时交通数据与地理定位情绪分析，采用AI模型与探索性数据分析预测交通拥堵模式、分析通勤行为，并识别拥堵热点与不满区域。研究结果为优化交通流、提升通勤体验、应对中东地区特有出行挑战提供了可操作建议。
原文摘要 · Abstract (English)
Urban planning plays a very important role in development modern cities. It effects the economic growth, quality of life, and environmental sustainability. Modern cities face challenges in managing traffic congestion. These challenges arise to due to rapid urbanization. In this study we will explore how AI can be used to understand the traffic and mobility related issues and its effects on the residents sentiment. The approach combines real-time traffic data with geo-located sentiment analysis, offering a comprehensive and dynamic approach to urban mobility planning. AI models and exploratory data analysis was used to predict traffic congestion patterns, analyze commuter behaviors, and identify congestion hotspots and dissatisfaction zones. The findings offer actionable recommendations for optimizing traffic flow, enhancing commuter experiences, and addressing city specific mobility challenges in the Middle East and beyond.
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