Smartphone-Interlocked Advanced Driver Assistance System Development for Safety

  • Authors

    • DongIn Lee
    • Bonghwan Kim
    • Byeung Leul Lee
    • Kyunghan Chun
    https://doi.org/10.14419/ijet.v7i3.7.18872
  • ADAS, HUD, DIRD, Safety

  • In this paper, we propose new advanced driver assistance system (ADAS) that interfaces with smartphones. The proposed system consists of a heads-up-display (HUD) and a driving information rear display (DIRD), and this configuration outputs information from the ADAS into the front and rear windshields. The HUD and DIRD help drivers operate their vehicles safely. In particular, the HUD and DIRD are constructed by combining navigation information provided by a smart phone and vehicle maintenance information, where vehicle information is provided by the electronic control unit (ECU). Experimental results show that the ADAS can be improved by providing the driver with the necessary safe driving information, and the vehicle can be easily maintained using the information obtained directly from the ECU.

     

     

  • References

    1. [1] Landau, K., Usability criteria for intelligent driver assistance systems. Theoretical Issues in Ergonomics Science, 2002, 3(4): p. 330-345.

      [2] Mohan, P., et al., Nericell: Rich monitoring of road and traffic conditions using mobile smartphones. 6th ACM Conference on Embedded Network Sensor Systems, 2008, (November): p. 323-336.

      [3] Dai, J., et al., Mobile phone based drunken driving detection. International Conference on Pervasive Health – No Permissions, 2010, (March): p. 1-8.

      [4] Langle L., et al., Are you a safe driver? International Conference on Computational Science and Engineering, 2009, 2(August): p. 502-507.

      [5] Amin, S., et al., Mobile century-Using GPS mobile phones as traffic sensors: A field experiment. 15th World Congress Intelligent Transportation Systems. USA, 2008, (November): p. 1-4.

      [6] Pham, M. H., et al., Random forest models for identifying motorway rear-end crash risks using disaggregate data. 13th IEEE International Conference on Intelligent Transportation Systems, 2010, (September): p. 468-473

      [7] Kim, J., et al, Proc. Intersection collision avoidance using wireless sensor network. IEEE International Conference on Vehicular Electronics and Safety, 2009, (November) p. 68-73.

      [8] Gharavi, H., et al., 3-d segmentation and motion estimation of range data for crash prevention. IEEE Intelligent Vehicles Symposium, 2007, (June): p. 386-391.

      [9] N. S. Council, Injury Facts, 2008.

      [10] Maag, C., et al., Studying effects of advanced driver assistance systems (ADAS) on individual and group level using multi-driver simulation. IEEE Intelligent Vehicles Symposium, 2011, (June): p. 589-594.

      [11] Hsiao, P. Y., et al., A portable vision-based real-time departure warning system: Day and night. IEEE Transportation and Vehicular Technology, 2009, 58(4): p. 2089-2094.

      [12] Amditis, A., et al., A holistic approach to the integration of safety applications: The insafes sub-project within the European framework programme 6 integrating project prevent. IEEE Transactions on Intelligent Transportation and Systems, 2010, 11(3): p. 554-566.

      [13] Needham, P., Collision prevention: The role of an accident data recorder (ADR). IEEE International Conference on Advanced Driver Assistance Systems, 2001, 483: p. 48-51.

  • Downloads

  • How to Cite

    Lee, D., Kim, B., Leul Lee, B., & Chun, K. (2018). Smartphone-Interlocked Advanced Driver Assistance System Development for Safety. International Journal of Engineering & Technology, 7(3.7), 332-335. https://doi.org/10.14419/ijet.v7i3.7.18872