2nd PerAda Workshop on User-Centric Pervasive Adaptive Systems

Research Article

An Adaptive Driver Alert System Making Use of Implicit Sensing and Notification Techniques

  • @INPROCEEDINGS{10.1007/978-3-642-29154-8_51,
        author={Gilbert Beyer and Gian Bertolotti and Andrea Cristiani and Shadi Al Dehni},
        title={An Adaptive Driver Alert System Making Use of Implicit Sensing and Notification Techniques},
        proceedings={2nd PerAda Workshop on User-Centric Pervasive Adaptive Systems},
        proceedings_a={UCPA},
        year={2012},
        month={10},
        keywords={driver assistance systems sensor-actuator supported interaction psycho-physiological sensing computer vision adaptive control implicit interaction adaptive user interfaces head-up displays},
        doi={10.1007/978-3-642-29154-8_51}
    }
    
  • Gilbert Beyer
    Gian Bertolotti
    Andrea Cristiani
    Shadi Al Dehni
    Year: 2012
    An Adaptive Driver Alert System Making Use of Implicit Sensing and Notification Techniques
    UCPA
    ACM
    DOI: 10.1007/978-3-642-29154-8_51
Gilbert Beyer1,*, Gian Bertolotti2,*, Andrea Cristiani2,*, Shadi Al Dehni1,*
  • 1: Ludwig-Maximilians-University Munich
  • 2: Università di Pavia
*Contact email: gilbert.beyer@ifi.lmu.de, gianmario.bertolotti@unipv.it, andrea.cristiani@unipv.it, shadi.aldehni@ifi.lmu.de

Abstract

In this paper we present an adaptive driver alert system that uses passive techniques for extracting psycho-physiological features from the user, and a head-up display actuator that hands preprocessed information about the driving behavior back to the user. The paper starts with background information on driver inattentiveness. That followed we present our conception of an adaptive loop with a view to improve the driver’s attention. We give an overview on current research on sensor and actuator techniques that support our adaptation strategy attaining data about user drowsiness and distraction. Then we describe a suitable hardware and software solution for the proposed system, using a head-up display and vision-based sensor techniques. We close describing first tests of our system in the lab and road tests with a Ferrari car.