Intelligent traffic management for a better quality of life

When it comes to actively designing living space and improving quality of life in cities, there are no limits to data-based applications. The technological triad of data analytics, location intelligence and cloud computing makes it possible to use location-based data to improve the quality of life in cities. The first part of this series was about how cities can be made more livable based on social factors. In this, the second part, we talk about the potential of geodata for intelligent traffic management.

Reduce parking search traffic and better manage traffic flows

The available space in large cities is scarce. Many road users compete for little free space. The intelligent use of geodata offers a lot of potential here. Interactive web applications and maps help city planners gain a more precise overview of the current traffic, emissions or parking situation.

For example, Deutsche Telekom has been equipping parking lots in German cities and communities with smart sensors in various projects for the past year. In collaboration with data and location technology experts, the aim is to gain insights into the use of parking space and, on this basis, to reduce parking search traffic and improve the distribution of urban space for all residents. Using map-based dashboards, users* can view statistics or track the utilization of specific parking spaces throughout the day. This includes residents who want to know if a parking space is free, as well as law enforcement officers who check for compliance with maximum parking hours. In the next iterations of the project, analyses of historical data, forecasts or even route planning for parking management are to be added. It would also be possible to integrate additional location-based data that indirectly influence the traffic situation: For example, it would be possible to take into account how certain events or the current weather situation affect the parking situation. It is also conceivable that live data could be fed into the system and alerts set up in the event that maximum parking times are exceeded. 

Flexible mobility solutions and optimal utilization of means of transport

The potential of data analytics and location intelligence can also be used in particular for optimized route planning. The visualization of movement data and traffic information in real time and the annotation with external data (altitude profiles, weather, events, etc.) provide a valid foundation for the optimal utilization of fleets and traffic connections. This extends to scheduling clearing vehicles or delivery services as efficiently as possible. The result of these efforts: Intelligent control of traffic and demand-based distribution of road and open spaces. Another plus point: Improving logistical processes helps reduce CO2 emissions and thus also has an impact on climate protection.

Buses and trains that travel along optimized routes with minimal energy consumption and coordinate with each other. Intelligent mobility services that relieve traffic congestion. Smart solutions for resource-saving freight and logistics. Car-sharing and e-mobility on demand, exactly where they are needed: This is what the new mobility looks like. However, this would not be feasible without location intelligence: Sophisticated technologies derive reliable analyses and forecasts from a multitude of location-based data. Mobility dashboards provide information on where mobility services should be available, what they are needed for, and what they need to look like. 

Interactive maps can be used to make detailed evaluations of fleet utilization, show hot spots and typical traffic routes, and compare them with each other. Clearly sorted by time of day, day of the week or season. Where were mobility services used last week? What is the current demand for various services? Where will demand be highest next week? Based on this information, cities and companies can not only develop more customer-friendly and environmentally conscious solutions, but also work more innovatively and cost-efficiently. This applies to the fleet management of car, bike and scooter sharing providers as well as to the optimization of public transport.

This article is based on an article by Jens Wille in the trade magazine Transforming Cities