Vehicles for the Demonstration Day

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Below you can find the demonstrators for our demonstration day at the Aldenhoven Testing Center!

High-Speed-Track / Oval

JKU-ITS: Haptic Guidance on Driving Performance

Description: Dynamic with test drive opportunity

Effect on driving performance after a take-over request by a haptic guidance system
Participants will drive the JKU-ITS research vehicle while executing a Non Driving Related Task (NDRT)
AR Glasses will show a sudden event on the road
Participants will be required to gain control of the vehicle

DLR: Maneuver Cooperation in Emergency Situations

Description: Dynamic with test drive opportunity

Two automated vehicles drive on adjacent lanes with a similar velocity (ca. 50 km/h)
A virtual obstacle is presented to first vehicle so that it switches to emergency braking
Cooperative lane change maneuver is negotiated via vehicle-to-vehicle communication with the second vehicle
Second vehicle accepts the lane change request and brakes
First vehicle is now able to change lanes

FH Aachen & Hyundai Motor: Take over Request and Minimum Risk Maneuver

Description: Dynamic with test drive opportunity

This demonstrator shows how an automated vehicle will react in case that the driver does not respond to a Takeover Request (ToR)
Test vehicle transitions into automated mode after starting in manual driving mode
The test vehicle will be informed about an upcoming danger zone and warns the driver to take control over the vehicle
The driver does not take control so that the test vehicle must perform a minimum risk maneuver (MRM) automatically
The test vehicle slows down and changes lanes onto the emergency lane and stops

FEV Europe GmbH: Traffic Jam Chauffeur

Description: Dynamic with test drive opportunity

The demonstrator vehicle (SVD) follows a target vehicle which
drives at 60 km/h on the most right lane
Target Vehicle simulates a traffic jam with stop & go through the ATC
Oval
The target vehicle cuts out shortly behing a stationary vehicle close
to the middle of a straight section
SVD will stop in time behind the new target

Oval / Vehicle Dynamic Track

mm-lab GmbH: Ground Safety System for Motorcycles with Maneuver Detection

Description: Dynamic with test drive opportunity

Research and Development cooperation project “Zentrales
Innovationsprogramm Mittelstand (ZIM)” funded by the Bundesministerium für
Wirtschaft und Energie (BMWi)
Selected driving maneuvers will be demonstrated by a motorcyclist
Exhibition of the On-Board Unit for Motorcycles supported by video sequences
Detection of maneuvers and crashes of motorbikes
HMI System tailored to motorcycles
Proving Ground Management System (PGMS) already used at the Proving Ground of Aldenhoven

Urban Track

dSpace: Data Driven Development Solutions for Autonomous driving

Description: Dynamic with test drive opportunity

Showcase of the dSPACE Car used for data collection
Development of AI Algorithm
Car is equipped with and advanced data logger (AUTERA)
A complete sensor setup generates around 21 Gbit/s of sensor data

MRT-KIT:
Autonomous Driving in Urban Scenarios

Description: Dynamic with test drive opportunity

Autonomous driving vehicle (“Joy”) equipped with different sensors
Localization in high definition maps based in fusion between differential GPS and visual localization
Obstacle detection based on gridmap able to generate mid time prediction for different agents
Planning in high definition maps, avoiding unexpected obstacles and optimizing the passenger’s comfort
Interaction with the enviroment

fka GmbH: Automated Driving Function

Description: Dynamic with test drive opportunity

Demonstration of Automated Driving Function for Urban Scenarios including V2X
Communications with traffic lights

ika RWTH Aachen: UNICARagil

Description: Dynamic without test drive opportunity

Presentation of disruptive modular architectures for self-driving vehicles
Demonstration using full-sized vehicle prototypes
Driverless vehicle under supervision of a control room operator
The control room operator takes control when the vehicle encounters a situation that it cannot resolve on its own

Copyright: Patrick Pintscher

ika RWTH Aachen: EMMI-Project: Wizard-of-Oz Vehicle - An immersive, "automated" test drive

Description: Dynamic with test drive opportunity

Simulation of automated functions
Corresponding functions are not technically realized, but are realistically simulated by a human (wizard) without the user (test person) having any knowledge of the wizard’s presence or actions
Test vehicle represents an outstanding instrument for investigating the interaction between humans and automated systems where it is relevant, i.e. in real road traffic

Urban Track/ Static

IMECH Uni-Duisburg-Essen: Charging Robot

Description: Static

The charging robot is a collaborative robot syste
Functional demonstrator that implements the automated insertion and removal of a charging cable in an electric vehicle
Robot is equipped with appropriate tools to grab the charging cable from the wallbox and plug it into the vehicle
System has a camera system to detect the charging socket on the vehicle

Static

TH Aschaffenburg: Cooperative Intention Detection

Description: Static

Cooperation between car and roadside unit (RSU)
Car and RSU equipped with a stereo camera and able to communicate using a wireless network
Individual tracking and forecasting by single agents (car and RSU)
Resolvement of occlusion by the RSU
Reducing uncertainty in the pedestrian’s position through cooperation
Probabilistic forecast of pedestrian positions

University of Texas at Dallas: Data Discovery and Targeted Learning

Description: Static

In case of a rare event during autonomous driving the deep learning
models perfom poorly
Demonstration on data discovery and targeted learning
Use of data discovery in a large pool of unlabeled data in case of a rare event
Search of semantically similar samples from unlabeled data set
Targeted learning is the mining of these samples in order to increase performance

Robosense: RoboSense RS-Reference

Description: Static

Robosense RS-Reference is a tool-chain to evaluate all sensor’s performance in the vehicle, such as LiDAR, millimeter wave, camera, etc.
Can assist OEM, Tier1, and research institutes to perform highly efficient tests and validation and accelerate mass production of ADAS and AD applications.