Adaptable Advanced Driver Assistance Systems (ADAS)

Fully autonomous cars will be realized earlier than expected. Artificial intelligence (AI) will play a vital role in the development of self-driving cars. Challenges of self-driving cars include the ability of the vehicle to sense its environment and avoid collisions with objects, determine what action to take if unexpected events occur, and how to make the user feel comfortable in the self-driving car. One way to tackle the later challenge is by adapting the driving style of the self-driving car to that of the driver. Advanced Driver Assistance Systems (ADAS) is a system design to help relieve driver of some of the driving tasks. With respect to ADAS, this paper describes a real-time AI-based approach that continuously learns driving behavior, and adapts the Driver Assistance System to the current driving style of the driver. Such AI adaptation ensures that ADAS, while relieving the driver of certain tasks, does so in a way very natural to this driver. A field test confirmed that the AI model described in this paper achieved an accuracy level of 98%. In addition, the paper provides a model that can anticipate driving maneuver. Data collected on different categories of drivers, can be used as bases for creating driving profiles for first fully autonomous cars.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ70 Standing Committee on Artificial Intelligence and Advanced Computing Applications. Alternate title: Adaptable Advanced Driver Assistance Systems (ADASs)
• Authors:
  • Ohazulike, Anthony E
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; Photos; References; Tables;
• Pagination: 16p

Subject/Index Terms

• TRT Terms: Adaptive control; Artificial intelligence; Automobile drivers; Automobile driving; Autonomous vehicles; Connected vehicles; Data analysis; Driver performance; Driver support systems; Intelligent vehicles; Machine learning; Real time data processing
• Uncontrolled Terms: Big data
• Subject Areas: Data and Information Technology; Highways; Passenger Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01658304
• Record Type: Publication
• Report/Paper Numbers: 18-00675
• Files: TRIS, TRB, ATRI
• Created Date: Jan 29 2018 10:23AM