Vehicle Automation Field Test: Impact on Driver Behavior and Trust

  • Walter Morales Alvarez (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

With the growing technological advances in autonomous driving, the transport industry and research community seek to determine the impact that autonomous vehicles (AV) will have on consumers, as well as identify the different factors that will influence their use. Most of the research performed so far relies on laboratory-controlled conditions using driving simulators, as they offer a safe environment for testing advanced driving assistance systems (ADAS). In this study we analyze the behavior of drivers that are placed in control of an automated vehicle in a real life driving environment. The vehicle is equipped with advanced autonomy, making driver control of the vehicle unnecessary in many scenarios, although a driver take over is possible and sometimes required. In doing so, we aim to determine the impact of such a system on the driver and their driving performance. To this end road users' behavior from naturalistic driving data is analyzed focusing on awareness and diagnosis of the road situation. Results showed that the road features determined the level of visual attention and trust in the automation. They also showed that the activities performed during the automation affected the reaction time to take over the control of the vehicle.
Period22 Sept 2020
Event titleIEEE International Conference on Intelligent Transportation Systems (ITSC) 2020
Event typeConference
LocationAustriaShow on map

Fields of science

  • 202003 Automation
  • 303 Health Sciences
  • 501 Psychology
  • 102029 Practical computer science
  • 203 Mechanical Engineering
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 102 Computer Sciences
  • 202041 Computer engineering
  • 202040 Transmission technology
  • 501030 Cognitive science
  • 211911 Sustainable technologies
  • 203004 Automotive technology
  • 201306 Traffic telematics
  • 211917 Technology assessment
  • 102013 Human-computer interaction
  • 102034 Cyber-physical systems
  • 201305 Traffic engineering
  • 102015 Information systems
  • 501026 Psychology of perception
  • 501025 Traffic psychology
  • 202038 Telecommunications
  • 102019 Machine learning
  • 303008 Ergonomics
  • 202037 Signal processing
  • 202036 Sensor systems
  • 202035 Robotics
  • 202034 Control engineering
  • 202031 Network engineering
  • 202030 Communication engineering
  • 211902 Assistive technologies
  • 102021 Pervasive computing
  • 102002 Augmented reality
  • 102024 Usability research
  • 102001 Artificial intelligence
  • 211908 Energy research
  • 102026 Virtual reality
  • 211909 Energy technology
  • 102003 Image processing

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management