Since 2018, the participating teams in the Shell Eco Marathon have also been able to compete in driverless disciplines. From the beginning the TUfast Eco Team was interested in developing an autonomous vehicle. With muc018 this was successfully implemented for the first time and we were able to achieve the 2nd place in the autonomous category.

This season’s goal is now to equip the latest car with an autonomous system that offers new functionalities to cope with new and more demanding tasks.

Such a project is interdisciplinary in many respects and requires a perfect interaction of software and hardware. 

For example, it is very important to install and commission the appropriate actuators. The vehicle muc019 is to be extended by a steering motor and an autonomous brake system. The precise calibration of the motors and their control is particularly important. The previously calculated trajectory of the vehicle should be run as accurately as possible. It is very important that the dynamics of the car are also taken into account, so that the vehicle behaves as desired regardless of external influences. 

The further development towards muc019+, as we have christened our project, is already in full swing and attempts are being made to combine a highly efficient design with autonomous functionalities through clever packaging. In addition, muc019+ is to be equipped with various environment sensors. The main component is the three cameras that will be mounted on the roof. One camera is equipped with a 190° wide-angle lens to cover the entire area in front of the vehicle. The other two together form a stereo camera, which makes it possible to estimate the distance to objects in front. 

The LiDAR sensor on the bonnet, which outputs a 3D point cloud of the environment, is also of particular importance. The sensor is positioned so that it can cover objects in front of the vehicle and a large part of the road ahead.  

The fusion of camera and LiDAR data is intended to combine the best of both worlds to create an accurate model of the environment. For example, image recognition provides information about the type of object and the LiDAR sensor provides information about where exactly this object is located in space.  

In addition, ultrasonic sensors are to be installed all around the vehicle. These can detect objects at a very close distance and should, for example, make it possible to park in a parking space. 

The main goal of this season is to participate in the “Autonomous Urban Concept” competition within the Shell Eco Marathon, as well as to participate in the efficiency competition of the Shell Eco Marathon. The “Autonomous Urban Concept” competition requires the car to independently master various driving disciplines without human intervention, such as driving on a track with gangs, identifying obstacles or parking.

Key Data

Load-bearing carbon fiber composite monocoque

Length: 2.5m



Mass (ready to drive) in kg
Maximum speed in km/h

Two electric motors in the steered front axle

With efficiency value from the Shell Eco Marathon (130.4km/kWh)   

  1. Competition battery: 25km range
  2. Battery for test/autonomous operation: 64km range

Lithium polymer batteries

  1. Competition battery: has a capacity of 190 Wh
  2. Battery for test/ for autonomous operation: has a capacity of 480Wh

Power Train

Motors: permanent-magnet synchronous motors

Self-developed GaN converter

Maintenance-optimized, pluggable PCB design

Cable-reduced design (total 33 m)

E-paper memory display as GUI

CAN bus for communication between control units 

Self-developed motor controller

Communication via CAN 

Nominal power in W (2x430W)


Innovative package, complete drive train and all computing units in the front end, spacious interior and luggage compartment

Entire body in carbon fibre composite construction and use of novel joining methods

Closed and load-optimized monocoque, one-piece sandwich structure


Non-structural, aerodynamic components such as multi-part front end, doors, underbody panelling and rear spoiler

In-house production of fibre composites with requirement-oriented processes (MTI, VAP, prepreg autoclave) 


Uprights optimised for robustness

Organic, topology optimized Scalmalloy uprights

MacPherson front axle with elastokinematic suspension and damping

Double wishbone rear axle with air suspension and hydraulic damping

Cable operated steering system

Four hydraulic disc brakes

Hydraulically controlled autonomous braking system

Spindle driven steering motor for more precise control


Perception bases on sensor fusion

Modular integration into the platform

New components specialized for specific applications

Simplification of the hardware architecture (reduction of components and wiring harness)

Image recognition by means of neural networks trained on computer-generated images

More efficient trajectory planning with better support for dynamic scenarios and more complex manoeuvres

Trajectory following control with state estimation for precise execution of the planned trajectory

More extensive testing through the use of continuous integration and multiple Simulation Pipelines

Self-developed steering and brake actuators