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Access to real-time data helps Taipei’s citizens to move around more easily, from understanding congestion levels to finding shared bicycles.
The national government’s smart transport initiative demonstrates a readiness to supply data to meet public demand for traffic updates. It incorporates existing information sources, such as eTag automatic tolling data, as well as the transport data and smart technology strategies already in development. This information is displayed across multiple platforms in the city as a dynamic real-time transport data feed. By looking up at a digital sign or checking an app on your phone, you can understand the time and pace of nearby buses, find shared bikes, and gauge the congestion level of roads to plan trips.
Shared bikes are a common sight across the city. Users can access one of 13,072 YouBikes, with the latest models incorporating the contactless payment system into the handlebars for added convenience.
AI traffic management may respond in real time with preventative changes within the traffic network, or by improving the timing of traffic lights.
Annual ridership on the Taipei Metro continues to grow steadily, with 765 million trips made in 2018. The Wenhu line operates a fully automated and driverless service, and is among the fastest and most punctual driverless metro trains in the world. Now Taipei’s road users may soon see traffic being managed by AI. In 2018, the Taiwan Ministry of Science and Technology announced plans to invest US$133 million in AI over a period of four years, possibly leading to new innovations across multiple sectors. This could greatly benefit mobility by analyzing where and when traffic jams often occur, then predicting when one may arise next. AI traffic management may respond in real time with preventative changes within the traffic network, or by improving the timing of traffic lights. Synchronization with meteorological data could reroute vehicles to streamline traffic, or advise on the best routes for drivers to get home safely in case of storms or weather events.