CASE STUDY 2 Taxi traffic management Dubai, United Arab Emirates Implemented STATUS Overview of mobility challenge Taxi services, as with other shared mobility services, are widely recognized as indispensable first- and last-mile solutions in urban areas, ensuring seamless transportation and reducing dependency on private cars within cities. However, challenges stemming from disorganized passenger demand and unpredictable driver patterns have led to an unbalanced distribution of taxis in many cities, particularly during peak traffic hours. Consequently, passengers can experience longer waiting times and increased fares while taxi drivers navigate through congested traffic lanes, leading to a demand-supply gap, longer commute times and increased stress levels. Such operational inefficiency also hampers the income of taxi service providers and undermines overall passenger satisfaction, primarily attributed to prolonged wait times and the inability to access timely service when required. In Dubai, a city that has experienced significant growth in recent years and continues to grow rapidly, developing an efficient transport system is a priority. Around 60% of trips in Dubai are made by private vehicles,21 making the growth of shared and public transport services important to minimize congestion. The use of taxis and shared mobility services is on the rise, with around 114 million journeys taking place in 2023, an 8% increase from 2022.22 With taxis becoming an increasingly important mode of transport in the city, managing them efficiently is a priority. Solution: Dynamic heat maps The Dubai Roads and Transport Authority (RTA) launched the Dynamic Heat Maps Programme for taxis with Trapeze’s artificial intelligence (AI) technology, which highlights high- demand areas and potential passenger concentrations. These heat maps are dynamically updated using real-time data analysis through advanced AI within the Enterprise Command and Control Center (EC3) of the city. All taxis are equipped with smart meters that directly connect with the control room. Within the cabs, heat maps utilize three colours: green, yellow and red. Green signifies heightened passenger demand at a specific destination, while yellow suggests sufficient vehicle availability in the vicinity to meet demand. Conversely, red indicates either a scarcity of passengers in the area or an excess of available vehicles, prompting drivers to relocate to another area, optimizing efficiency and reducing wait times for travellers.23 FIGURE 4. Smart meters installed in Dubai taxis24 The dynamic heat maps are meticulously updated through the central control system, closely monitoring the movement of 10,800 taxis and demand fluctuations across Dubai-designated target areas, all powered by advanced AI.25 This sophisticated control mechanism systematically analyses real-time passenger demand data while gauging the presence of taxis within specific zones. By juxtaposing these insights, the system accurately assesses the overall capacity of the taxi fleet to address the prevailing demand. Combatting Congestion: How Cities and Companies are Innovating First- and Last-Mile Transport 10

Combatting Congestion 2025