Field Operational Test of V2V between Tramcars and Cars ‘Towards Automated Driving System

Author(s):  
Hideaki Nanba ◽  
Takeo Kawai ◽  
Manabu Sawada ◽  
Md. Shoaib Bhuiyan ◽  
Koji Oguri
Author(s):  
Michael G. McNally ◽  
Stephen P. Mattingly ◽  
James E. Moore ◽  
Hsi-Hwa Hu ◽  
C. Arthur MacCarley ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
pp. 845-852
Author(s):  
Aleksandra Rodak ◽  
Paweł Budziszewski ◽  
Małgorzata Pędzierska ◽  
Mikołaj Kruszewski

Abstract In L3–L4 vehicles, driving task is performed primarily by automated driving system (ADS). Automation mode permits to engage in non-driving-related tasks; however, it necessitates continuous vigilance and attention. Although the driver may be distracted, a request to intervene may suddenly occur, requiring immediate and appropriate response to driving conditions. To increase safety, automated vehicles should be equipped with a Driver Intervention Performance Assessment module (DIPA), ensuring that the driver is able to take the control of the vehicle and maintain it safely. Otherwise, ADS should regain control from the driver and perform a minimal risk manoeuvre. The paper explains the essence of DIPA, indicates possible measures, and describes a concept of DIPA framework being developed in the project.


2021 ◽  
Vol 129 ◽  
pp. 103271
Author(s):  
Zhigang Xu ◽  
Zijun Jiang ◽  
Guanqun Wang ◽  
Runmin Wang ◽  
Tingting Li ◽  
...  

Author(s):  
Travis Terry ◽  
Tammy E. Trimble ◽  
Mindy Buchanan-King ◽  
Myra Blanco ◽  
Vikki L. Fitchett ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Frederik Naujoks ◽  
Yannick Forster ◽  
Katharina Wiedemann ◽  
Alexandra Neukum

During conditionally automated driving (CAD), driving time can be used for non-driving-related tasks (NDRTs). To increase safety and comfort of an automated ride, upcoming automated manoeuvres such as lane changes or speed adaptations may be communicated to the driver. However, as the driver’s primary task consists of performing NDRTs, they might prefer to be informed in a nondistracting way. In this paper, the potential of using speech output to improve human-automation interaction is explored. A sample of 17 participants completed different situations which involved communication between the automation and the driver in a motion-based driving simulator. The Human-Machine Interface (HMI) of the automated driving system consisted of a visual-auditory HMI with either generic auditory feedback (i.e., standard information tones) or additional speech output. The drivers were asked to perform a common NDRT during the drive. Compared to generic auditory output, communicating upcoming automated manoeuvres additionally by speech led to a decrease in self-reported visual workload and decreased monitoring of the visual HMI. However, interruptions of the NDRT were not affected by additional speech output. Participants clearly favoured the HMI with additional speech-based output, demonstrating the potential of speech to enhance usefulness and acceptance of automated vehicles.


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