TY  - CHAP
A1  - Schulte-Tigges, Joschua
A1  - Matheis, Dominik
A1  - Reke, Michael
A1  - Walter, Thomas
A1  - Kaszner, Daniel
ED  - Krömker, Heidi
T1  - Demonstrating a V2X enabled system for transition of control and minimum risk manoeuvre when leaving the operational design domain
T2  - HCII 2023: HCI in Mobility, Transport, and Automotive Systems
N2  - Modern implementations of driver assistance systems are evolving from a pure driver assistance to a independently acting automation system. Still these systems are not covering the full vehicle usage range, also called operational design domain, which require the human driver as fall-back mechanism. Transition of control and potential minimum risk manoeuvres are currently research topics and will bridge the gap until full autonomous vehicles are available. The authors showed in a demonstration that the transition of control mechanisms can be further improved by usage of communication technology. Receiving the incident type and position information by usage of standardised vehicle to everything (V2X) messages can improve the driver safety and comfort level. The connected and automated vehicle’s software framework can take this information to plan areas where the driver should take back control by initiating a transition of control which can be followed by a minimum risk manoeuvre in case of an unresponsive driver. This transition of control has been implemented in a test vehicle and was presented to the public during the IEEE IV2022 (IEEE Intelligent Vehicle Symposium) in Aachen, Germany.
KW  - V2X
KW  - Transiton of Control
KW  - Minimum Risk Manoeuvre
KW  - Operational Design Domain
KW  - Connected Automated Vehicle
Y1  - 2023
SN  - 978-3-031-35677-3 (Print)
SN  - 978-3-031-35678-0 (Online)
U6  - http://dx.doi.org/10.1007/978-3-031-35678-0_12
N1  - 5th International Conference, MobiTAS 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagen, Denmark, July 23–28, 2023.
SP  - 200
EP  - 210
PB  - Springer
CY  - Cham
ER  - 
TY  - JOUR
A1  - Schulte-Tigges, Joschua
A1  - Förster, Marco
A1  - Nikolovski, Gjorgji
A1  - Reke, Michael
A1  - Ferrein, Alexander
A1  - Kaszner, Daniel
A1  - Matheis, Dominik
A1  - Walter, Thomas
T1  - Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments
JF  - Sensors
N2  - Abstract
In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.
KW  - Lidar
KW  - Benchmark
KW  - Self-driving
Y1  - 2022
U6  - http://dx.doi.org/10.3390/s22197146
SN  - 1424-8220
N1  - This article belongs to the Special Issue "Sensor Fusion for Vehicles Navigation and Robotic Systems"
VL  - 22
IS  - 19
PB  - MDPI
CY  - Basel
ER  -