Data-driven mobility in cities: the role of maps and traffic data

Cities everywhere are grappling with the same challenge: how to keep people and goods moving efficiently, safely, and sustainably as urban populations continue to grow. Congestion, air pollution, safety risks, and pressure on infrastructure are common problems – and they demand smarter, data-driven solutions. 

Real-time traffic data and adaptive, high-precision mapping are now transforming how cities plan and manage mobility. By harnessing increasingly connected vehicle ecosystems, community-generated data, and advanced mapping platforms, such as TomTom Orbis Maps, cities can gain unprecedented visibility into how people move and how networks perform.

Combined with policy, planning, and investment, these insights are helping to reshape urban mobility for a modern day where cities continue to grow, and safety and sustainability are front of mind. 

The switch to data-driven mobility

The broader story for data-driven mobility began more than two decades ago, with early fleet management systems for taxis and navigation. The leap forward came when community-generated data began to scale, revealing an opportunity to apply it far beyond navigation. Suddenly, data could help cities and businesses transform the way they planned and managed transport. 

Nearly 15 years ago, TomTom took this step with the launch of its Traffic Index, which now covers more than 500 cities worldwide. The Index provides governments with a clear picture of congestion and capacity challenges, putting a mirror in front of decision-makers to show them where the pain points lie. 

The fundamentals remain the same today – cities keep growing, but the ecosystem of connected cars, smartphones, and in-dash systems is now providing insights at a scale never seen before. We can track how people move across modes – cars, public transport, bikes, e-bikes – and this visibility forms the raw material for transformation. 

From traffic capacity to multimodality 

Sticking with the fundamentals, we see that capacity is the fundamental constraint. A single undisturbed lane carries only around 2,000 cars per hour under free-flow conditions. Once that capacity is exceeded, congestion rises and efficiency plummets.

This is why smart mobility management is not only about optimising flows on existing roads but also about rebalancing the modal split – encouraging a shift from cars to public transport, cycling, and walking. That requires alternatives to be attractive, safe, and accessible. Cities need to provide good transit, safe cycling infrastructure, and walkable environments if they want people to change behaviour.

Here, real-time traffic data and adaptive maps play a crucial role. They provide visibility across the whole road network – highways, arterials, and local roads – without relying solely on expensive fixed infrastructure. Connected vehicles will add even richer layers of information, from safety and environmental data to onboard sensor feeds. This precision supports both mobility management and planning for alternatives.

Traffic analytics are particularly powerful for guiding investment. TomTom’s solutions can compute origin-destination pairs, showing where shifting from car to public transport or cycling would deliver the best return. With this knowledge, cities can target funds where they will achieve the maximum return on investment in terms of reducing congestion and improving mobility.

History shows that congestion management often starts with discomfort – people need to feel the pressure before behaviour shifts. Copenhagen illustrates this journey; today, it has bicycle traffic jams, but that success came after years of consistent policy and change management, using data to rebalance road capacity and travel choices.

Multimodality is the key to making urban systems work at scale. With insights into how, where, and why people travel, cities can align infrastructure with demand and encourage a genuine shift towards more sustainable forms of mobility. 

Real-time data, adaptive maps, and safety

The same traffic data that helps manage congestion can also improve road safety. If a system can detect a traffic jam, it can also identify the hazardous tail of that jam and distinguish between dangerous hard stops and softer slowdowns. This principle underpins TomTom’s hazard warning services, which are now used widely in navigation and safety systems.

Over time, these services have expanded to cover construction zones, narrow lanes, and environmental conditions such as fog, rain, or snow – all of which have huge impacts on traffic flow, speed, and safety. By combining car-derived speed data, hazard detection, and contextual information, TomTom has created services that keep drivers not only legally compliant but genuinely safer.

This is increasingly critical with the rise of advanced driver assistance systems (ADAS) and the move toward autonomous driving. When control shifts from the driver to the car, the system must behave smoothly and safely in all conditions – from heavy rain to dense traffic. Lane-level precision, powered by Orbis Maps and real-time traffic feeds, enables these systems to make reliable, safe choices.

Safety is also a matter of policy. With TomTom’s traffic volume products, cities can analyse how many people move through a corridor at different times of day and plan roadworks accordingly. In Japan, roadworks are often scheduled at night as a principle, while the Netherlands incentivises contractors to finish faster to reduce disruption. These examples show how evidence-based decisions can protect people on the roads and minimise risks during construction.

Data for resilience and disaster response

Mobility data is not only about efficiency and safety in daily life – it is also a vital tool during emergencies. During disasters such as fires, floods, or storms, navigation systems must not guide people into danger. TomTom has built partnerships with governments to integrate official emergency data with its routing, creating disaster-aware navigation that steers people around unsafe zones.

Community input adds another layer of resilience. Drivers reporting incidents in real time feed into the system, helping others avoid hazards. In Japan, researchers have even used traffic volume data to train models for flood and tsunami impact, analysing where people stop moving or avoid certain areas.

This integration of official data, advanced modelling, and community reports creates a vital safety layer for disaster response and preparedness. It shows that traffic data is not only about saving time – it can save lives.

AI and the future of traffic management

Artificial intelligence is already enhancing traffic management. The precision of data from connected and automated vehicles is vastly improving, down to lane-level accuracy. This enables more reliable hazard detection, speed monitoring, and congestion management.

At the same time, AI supports collaborative traffic management. With ADAS and autopilot systems, information must be delivered inside the vehicle rather than through roadside signs. That requires close cooperation between public authorities and private-sector players to create virtual traffic signs and lights.

AI itself is not a silver bullet, but it makes decision-making faster and more effective. It can process vast amounts of data, surface insights, and prioritise actions better than humans alone. When guided by domain expertise and clear political objectives, AI becomes a powerful tool to help governments and operators plan interventions, manage congestion, and improve safety. 

Behind these capabilities lies TomTom’s technology ecosystem. Our real-time traffic service processes billions of data points every 30 seconds, with contributions from more than 600 million connected devices across 84 countries. This enables a live, detailed view of congestion, travel times, incidents, and hazards. 

For longer-term planning, TomTom offers historical traffic archives going back more than a decade. These datasets support scenario testing, roadwork planning, traffic modelling, and even geomarketing applications, such as identifying EV charging demand or retail site selection.

All of this is powered by TomTom Orbis Maps – a high-precision, constantly updated global map built from probes, survey vehicles, satellite and street-level imagery, and open data contributions. Orbis Maps includes lane-level information, turn restrictions, verified speed limits, and logistics attributes, making it a rich foundation for mobility management. 

Together, traffic data and Orbis Maps create a holistic view of urban mobility that cities can integrate into operations and planning. From managing VIP traffic during major events in Qatar to evaluating pop-up bicycle lanes in Brussels or adjusting speed limits in Amsterdam, the applications are broad and impactful.