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Optimized routing

How TomTom and EPG leverage real-world traffic intelligence for smarter routing

Route planning has long struggled to bridge the gap between theory and reality. When DHL drivers reported that they rarely followed their suggested stop sequences due to heavy traffic, it raised a fundamental question: how can route planning dynamically adapt to real-world conditions?

This challenge led to the creation of EPG’s Greenplan solution, a routing system developed in collaboration with the University of Bonn’s discrete mathematics department. However, even the most advanced algorithm is only as effective as the data it processes. To create truly optimized routes, Greenplan needed precise, predictive traffic intelligence. That’s where TomTom came in.

Traditional route planning tools focus on minimizing distance, but in practice, the shortest route is not always the fastest. Congestion, road restrictions, and peakhour traffic can turn an optimized plan into a logistical headache …

Who is TomTom?

Seoul Semiconductor logo text with red marker icon.

TomTom is a Dutch multinational company specializing in location technology and consumer electronics. In 2004, TomTom introduced its first portable GPS navigation device, the TomTom GO, which gained significant popularity. Over the years, TomTom has evolved into a leading provider of digital maps, navigation software, and real-time traffic information.  TomTom’s product portfolio includes navigation devices, mobile applications, and advanced mapping services. Notably, TomTom supplies mapping data to major clients such as Apple and Uber. The company is also involved in developing technologies for autonomous driving and smart mobility solutions.

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Datos clave de un vistazo

Los resultados

Desafío

  • Pre-planned stop sequences don’t consider traffic flows
  • Drivers waste time and fuel in congested zones
  • Unmet ETAs due to traffic delays
  • Traditional mapping services don’t consider trucks

Solución

  • EPG incorporates TomTom traffic data into its routing algorithm
  • Time-of-day dependent speed profiles for every 200m of street
  • Consideration of fleet-specific constraints

Resultado

  • Higher efficiency: More deliveries achievable per day
  • Lower costs: Fewer wasted minutes and miles/km in traffic
  • Higher quality: Improved punctuality, driver happiness, and customer satisfaction

Descubre más sobre nuestras soluciones EPG.

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