As of 2018 driverless disciplines have been introduce into the Shell Eco Marathon. Since its inception, TUfast Eco Team have sought to develop an autonomous vehicle. This materialized into the creation of the muc018, where an autonomous driving system was successfully integrated into the vehicle for the first time, and in the same year the TUfast Eco Team achieved second place in the autonomous category of the SEM.

The goal of the current season is to equip the latest car with a more robust autonomous system able to fulfill more demanding tasks. To accomplish such an interdisciplinary project, there must be seamless interaction between the software and hardware of the autonomous system.

For example, it is of the utmost importance to install the appropriate actuators. Furthermore, a steering motor and an autonomous braking system must be incorporated into muc019. The precision of the calibration of the motors and their controls are of particular importance. The prior calculations for the trajectory of the vehicle must also be traced as accurately as possible. Therefore, it is of great significance to consider the dynamics of the car, to ensure that the vehicle behaves as intended, irrespective of external influences.

The continuous development towards muc019+, as we have christened our project, is already in full swing. The fusion of a highly efficient design with autonomous functionality through clever packaging is being refined. In addition, muc019+ will be fitted with various environmental sensors. Three cameras mounted on the roof of the vehicle form the main component of the environmental sensors. One camera will be fitted with a 190-degree wide-angle lens, capable of overseeing the entire front-area of the car. The other two cameras, together form a stereo camera, which estimates the distances to objects in front of the vehicle

The LiDAR sensor positioned on the bonnet, outputs a 3D point cloud environment. The sensor is placed in such a way to cover all objects in front of the vehicle and much of the road ahead.

By using the combination of cameras and LiDAR data we can create a hyper-accurate model of the environment around the car. The image recognition provides information about the object type, and the LiDAR sensor pinpoints the location of the object in the environment.

Additionally, ultrasonic sensors will be installed around the vehicle. These sensors can detect objects at extremely short distances, making it possible to park the autonomous vehicle in a parking space.

The main goal of this season is to participate in both the ‚ÄúAutonomous Urban Concept‚ÄĚ and efficiency competitions of the Shell Eco Marathon. The ‚ÄúAutonomous Urban Concept‚ÄĚ competition requires the car to independently master various driving disciplines without human intervention, such as driving on a track with pre-defined routes, 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


Lithium polymer batteries

  1. Competition battery: has a capacity of 190 Wh and a range of 25km
  2. Battery for test/ for autonomous operation: has a capacity of 480Wh and a range of  64km

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

Power Train

Motors: permanent-magnet synchronous motors

Self-developed GaN-Inverter

Maintenance-optimized, plug-in PCB design

Cable-reduced design (total 33m)

E-paper memory display as GUI

CAN and Bus for communication between control units 

Self-developed motor controller

Communication via CAN 

Nominal power in W




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

Self-manufactured CFRP-parts with requirement-oriented processes (MTI, VAP, prepreg autoclave) 

Suspension System

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