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Autonomous Driving Sensor Software

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Autonomous Driving Sensor Software

About the client

The customer, in this business case, was a company that had undertaken a mission to transform automotive mobility. In this capacity, they needed a technology partner that could help them with a challenging software project in the domain of next-generation autonomous driving.

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About the project

Andersen assumed responsibility for carrying out a challenging next-gen automotive IT initiative to build software for an autonomous driving sensor.

Duration12 months
AUTOSAR Adaptive Platform


Eclipse iceoryx, DDS, Wireshark

Business Context

The autonomous driving niche is expected to hit $62 billion by 2026, compared to $24 billion back in 2021. The number of autonomous vehicles with at least some degree of automation is also growing steadily. Under these conditions, R&D efforts have to gain momentum to take hold in this expanding niche. Andersen’s customer is one of those ambitious market players offering autonomous driving software for major car brands.


The challenge that our team was asked to resolve within this automotive software development project can be split into two parts:

  • First, we were entrusted with building a dockerized image on top of Ubuntu 20.04 by applying the customer’s demo code;
  • Second, we were tasked with crafting a Sensor-Fusion-Actuator app that would be capable of working in a service-oriented fashion. Here, our priority was to simultaneously ensure the possibility of applying a variety of communication patterns.

App functionality

  • The solution designed and developed by our specialists can be used as a basis for the customer’s further adaptive projects in the autonomous driving domain;
  • The app is able to virtually read the info provided by the Sensor (the Radar part), process the information with data from other different sources (the Fusion part), and act accordingly (the Actuator part).


When working on this project, we accomplished an entire range of sophisticated tasks:

  • Built dockerized images based on Ubuntu 20.04 for the customer’s demo code to run;
  • Created the Sensor, Fusion, and Actuator app packages according to the customer’s adaptive modelling and implementation standards;
  • Created different communication bindings for the Sensor-Fusion-Actuator app communication
  • Integrated the DDS stack (over Ethernet) for Inter-Host communication;
  • Integrated the SOME/IP stack (over Ethernet) for Inter-Host communication;
  • Integrated the Eclipse iceoryx stack (Shared memory) for Inter-Host communication.

Project results

Thanks to the contribution made by our experts, the customer is now in the right position to capitalize on the following results:

  • Successful and dependable integration of different technologies within a virtualized environment that is easy to deploy and test;
  • The Sensor services are capable of detecting incoming events and successfully transmitting such information between the Fusion and Actuator components;

Andersen has also demonstrated that different services related to this project could be allocated within the same or different ECUs (different docker images) without any impact on the functionality.

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