Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Driver Steering Override and Its Control

Author : Tarun 1

Date of Publication :23rd March 2018

Abstract: The cost of sensory technology including camera and radar has encouraged the outspreading of advanced driver assistance systems (ADAS) into modern vehicles. ADAS systems can function beyond the limits of stability control, using both longitudinal and lateral autonomous operation.Lane-keeping aid (LKA) and Adaptive cruise control and are the pinnacles of ADAS technology and both driving effort and unintended lane-drifts have been demonstrated. The current paper compares the latest Volvo approach and a design strategy for driver steering override specific to LKA systems. The driver steering override theme evaluates the interaction of the driver with the vehicle and modulates the level of intervention accordingly. Both strategies quantify activation of the driver by means of torque steering and information on road or vehicle.The results show that the override strategy has a decisive influence on the advantages of the LKA, thus depicting the need for careful design and rigorous testing. ACC and LKA plays main role in ADAS development and demonstrated a related reduction in driving effort and unintended lane-drifts. A shared control framework for the automatic steering control override for drivers is proposed. This framework formulates the transfer of control between driver and system as a constrained problem of optimization which is solved online by a predictive controller model.

Reference :

    1.  M. Heesen et al., “Interaction design of automatic steering for collision avoidance: Challenges and potentials of driver decoupling,” in IET Intelligent Transport Systems, 2015, doi: 10.1049/iet-its.2013.0119.
    2. D. I. Katzourakis, N. Lazic, C. Olsson, and M. R. Lidberg, “Driver Steering Override for LaneKeeping Aid Using Computer-Aided Engineering,” IEEE/ASME Trans. Mechatronics, 2015, doi: 10.1109/TMECH.2015.2401044.
    3. C. Guo, C. Sentouh, J. C. Popieul, and J. B. Haué, “Predictive shared steering control for driver override in automated driving: A simulator study,” Transp. Res. Part F Traffic Psychol. Behav., 2019, doi: 10.1016/j.trf.2017.12.005.
    4. H. Muslim and M. Itoh, “Human factor issues associated with lane change collision avoidance systems: Effects of authority, control, and ability on drivers’ performance and situation awareness,” in Proceedings of the Human Factors and Ergonomics Society, 2017, doi: 10.1177/1541931213601894.
    5. J. Shah and M. Benmimoun, “Driver Perceived Threat and Behavior in Rear End Collision Avoidance Situations,” in SAE Technical Papers, 2015, doi: 10.4271/2015-01-1414.
    6. P. Lin, “Here’s How Tesla Solves A SelfDriving Crash Dilemma,” Forbes, 2017. 
    7.  X. He, H. Chen, J. Chen, W. Ran, Y. Nishimura, and K. Ando, “Evaluation and Optimization of Driver Steering Override Strategy for LKAS Based on Driver’s Acceptability,” in SAE Technical Papers, 2018, doi: 10.4271/2018-01- 1631
    8. R. Yamaguchi and H. Nozaki, “Effective Steering Assistance Control by External Information Feedback,” Int. J. Automot. Technol., 2019, doi: 10.1007/s12239-019-0115- 7.
    9. A. Parisio, C. Wiezorek, T. Kyntäjä, J. Elo, K. Strunz, and K. H. Johansson, “Cooperative MPC-Based Energy Management for Networked Microgrids,” IEEE Trans. Smart Grid, 2017, doi: 10.1109/TSG.2017.2726941. 
    10. P. Sterling, “Allostasis: A model of predictive regulation,” Physiol. Behav., 2012, doi: 10.1016/j.physbeh.2011.06.004.

Recent Article