Urban mobility is currently undergoing three fundamental transformations with the sharing economy, electrification, and autonomous vehicles changing how people and goods move across cities. In this paper, we demonstrate the valuable contribution of decision support systems that combine data-driven analytics and simulation techniques in understanding complex systems such as urban transportation. Using the city of Berlin as a case study, we show that shared, autonomous electric vehicles can substantially reduce resource investments while keeping service levels stable. Our findings inform stakeholders on the trade-off between economic and sustainability-related considerations when fostering the transition to sustainable urban mobility.

随着共享经济，电气化和自动驾驶汽车的出现，城市交通目前正在经历三个根本性转变，这将改变人们和商品在城市间的流动方式。在本文中，我们展示了决策支持系统的宝贵贡献，该系统结合了数据驱动的分析和模拟技术，可以帮助您理解复杂的系统，例如城市交通。以柏林市为例，我们表明共享的自动驾驶电动汽车可以在保持服务水平稳定的同时，大大减少资源投资。我们的发现为利益相关者在促进向可持续城市交通的过渡过程中，在经济因素和可持续发展因素之间的权衡取舍提供了信息。