TomTom DeepRoute.ai Collaboration Targets Paris Road Demo

TomTom and DeepRoute.ai Collaborate on Automated Driving Technology

On October 12, TomTom signed a memorandum of understanding (MOU) with DeepRoute.ai to collaborate on automated driving technology. The companies have integrated TomTom's location data into DeepRoute.ai's automated driving system and plan to demonstrate the technology on public roads in Paris during the 2026 Paris Motor Show. The TomTom DeepRoute.ai collaboration combines location information with automated driving capabilities, with the goal of supporting advanced driving functions. The planned demonstration will provide an opportunity to showcase the integrated technology in a real-world road environment.

Location Data Supports Automated Driving Navigation

DeepRoute.ai combines sensor data with TomTom's location data to help its automated driving system plan routes and navigate unfamiliar roads. This integration supports advanced Level 2+ and Level 2++ driving functions, according to the companies' description of the technology. By incorporating location information alongside sensor inputs, the system can use additional geographic context when planning routes and navigating road networks. The collaboration focuses on integrating these complementary data capabilities into an automated driving system rather than relying on sensor data alone. The companies have already integrated the location data, while the Paris road demonstration is planned for the 2026 Paris Motor Show.

Regional Road Conditions and Traffic Rules

TomTom's location data is intended to help automakers and technology companies adapt automated driving systems to regional road conditions and traffic rules. These differences can affect how driving systems operate when introduced in new markets. By providing location information that supports regional adaptation, TomTom aims to make it easier for companies to deploy automated driving technologies across different markets. The collaboration with DeepRoute.ai applies this capability to a system designed to support advanced Level 2+ and Level 2++ functions. The planned demonstration in Paris will showcase the integrated technology on roads, although the announcement does not specify additional deployment dates, commercial availability, or performance results.

Industry Impact & Outlook

The collaboration highlights the importance of combining location data with sensor-based systems as automakers and technology providers work to adapt automated driving functions to different road environments. For the automotive industry, regionally relevant location information could help address differences in road layouts and traffic rules when introducing these technologies in new markets. The planned Paris demonstration will offer a practical opportunity to showcase the integrated system, but its results have not yet been reported. Further progress will depend on the technology's demonstrated capabilities and the companies' subsequent development and deployment decisions. Automakers and mobility technology providers will have an interest in how effectively this type of integration supports advanced driving functions across varied operating environments.

Frequently Asked Questions

What did TomTom and DeepRoute.ai announce?
TomTom and DeepRoute.ai signed a memorandum of understanding to collaborate on automated driving technology and demonstrate their integrated system in Paris. The companies have already incorporated TomTom's location data into DeepRoute.ai's automated driving system. Their planned road demonstration is scheduled for the 2026 Paris Motor Show. The announcement establishes a collaboration focused on combining location information with sensor data to support route planning, navigation on unfamiliar roads, and advanced Level 2+ and Level 2++ driving functions.

How does TomTom's location data support automated driving?
TomTom's location data provides additional geographic information that DeepRoute.ai's automated driving system can combine with sensor data. This integration helps the system plan routes and navigate unfamiliar roads while supporting advanced Level 2+ and Level 2++ driving functions. TomTom also identifies regional road conditions and traffic rules as important considerations for adapting automated driving systems to different markets. The collaboration applies location data to these navigation and route-planning requirements, although the announcement does not provide quantitative performance measurements or independent validation results.

When and where will the companies demonstrate the technology?
TomTom and DeepRoute.ai plan to demonstrate their integrated automated driving technology on roads in Paris during the 2026 Paris Motor Show. The announcement identifies the location and event but does not provide a specific demonstration date, time, route, or public access arrangements. The demonstration is intended to showcase technology that combines TomTom's location data with DeepRoute.ai's sensor-based automated driving system. Further information about the demonstration's results, subsequent development milestones, and potential commercial deployment was not included in the announcement.

Which automated driving functions does the collaboration support?
The integrated system is designed to support advanced Level 2+ and Level 2++ driving functions through the combination of sensor data and location information. DeepRoute.ai uses these inputs to help its automated driving system plan routes and navigate unfamiliar roads. The announcement does not specify the individual functions included in either level, the operating conditions supported, or the system's performance limitations. It also does not establish that the collaboration enables fully autonomous driving. The stated objective is to support advanced driving functions through improved integration of relevant navigation and sensor information.

Why is regional location data important for automated driving?
Regional location data can help automakers and technology companies adapt automated driving systems to differences in road conditions and traffic rules across markets. TomTom identifies this adaptation as a way to make introducing automated driving technologies in different regions easier. Road layouts and applicable traffic rules can vary, making location information relevant to route planning and navigation. The collaboration demonstrates how such data can be integrated into an automated driving system, but the announcement does not establish how much deployment time, development cost, or operational complexity the approach may reduce.