通过对自动驾驶汽车和车辆即服务集成的数据驱动建模来评估圣保罗的公共交通效率和覆盖范围
Lucas Henrique L Antonio1, Sidney Junior C Terenciani1, Danilo M Eler2
1School of Sciences, São Paulo State University (UNESP), Av. Eng. Luís Edmundo Carrijo Coube, 17033-360, Bauru, São Paulo, Brazil.
Scientific reports
|December 23, 2025
概括
这是圣保罗的圣保罗.
科学领域:
- 城市规划 城市规划
- 运输工程 运输工程
- 地理空间分析是什么
背景情况:
- 圣保罗的城市流动性受到人口增长和公共交通分配不平等的挑战.
- 密集的中心地区和服务不足的边缘社区之间存在差异.
研究的目的:
- 使用地理空间数据分析圣保罗的公共交通效率.
- 探索新兴技术,如自动驾驶汽车和车辆即服务 (VaaS),以改善移动性.
主要方法:
- 地理空间可视化技术.
- 对公共交通系统的数据分析.
- 探索自动驾驶汽车和VaaS模型.
主要成果:
- 发现了中部和外围地区之间的连接和服务频率的显著差异.
- 突出了自动驾驶汽车在减少事故和拥堵方面的潜力.
- 认可VaaS模型的灵活和可扩展的移动解决方案的能力.
结论:
- 实施分析技术和新兴解决方案对于改变圣保罗的城市流动性至关重要.
- 未来的移动性需要解决新技术的监管,基础设施和公众接受方面的挑战.
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