Smooth Automatic Stopping for Ultra-Compact Vehicles

Traffic accidents by elderly drivers are increasing each year in countries like Japan. Ultra-compact vehicles have attracted attention as one solution to this problem, and are looked to as a more compact, environmentally friendly, and convenient transportation means than conventional automobiles. However, their small size makes the use of conventional safety technologies difficult, and there has been little detailed research considering related safety issues. Because elderly persons are the primary target users of ultra-compact vehicles, there is a pressing need for applicable safety technologies. This research investigates miniaturized hardware for driving support that reduces the shock to passengers during sudden stopping due to the sudden appearance of obstacles. In this method, an optimal automatic stop is realized based on the distance to a detected obstacle, the speed of the vehicle, and the coefficient of friction with the road surface. We close with a description of experiments using simulations and actual machines which confirm the effectiveness and usefulness of the proposed method.

[1]  J. C. van den Heuvel,et al.  Stereo based Obstacle Detection with Uncertainty in Rough Terrain , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[2]  E. Coelingh,et al.  A situation and threat assessment algorithm for a rear-end collision avoidance system , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[3]  Halpage Chinthaka Nuwandika Premachandra,et al.  Improving landmark detection accuracy for self-localization through baseboard recognition , 2017, Int. J. Mach. Learn. Cybern..

[4]  Hamid Reza Karimi,et al.  Speed control design for a vehicle system using fuzzy logic and PID controller , 2015, 2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY).

[5]  Haruki Kawanaka,et al.  Assessment and prediction of older drivers' driving performance , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[6]  Haruki Kawanaka,et al.  Study of the senior driver's driving conscious against the specification traffic situation and driving behaviors , 2015, 2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES).

[7]  Halpage Chinthaka Nuwandika Premachandra,et al.  High performance embedding environment for reacting suddenly appeared road obstacles , 2014, 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014).

[8]  Xiao Luo,et al.  Safety benefits of motorized seat belt as a component in ADAS in front-end collisions , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[9]  Kara E MacLeod,et al.  Driving cessation and increased depressive symptoms. , 2005, The journals of gerontology. Series A, Biological sciences and medical sciences.

[10]  Zohaib Mushtaq,et al.  Fuzzy logic based automatic vehicle collision prevention system , 2015, 2015 IEEE Conference on Systems, Process and Control (ICSPC).

[11]  Guodong Yin,et al.  Modeling and parameters sensitivity analysis of lightweight vehicles considering payload variations , 2013, 2013 Conference on Control and Fault-Tolerant Systems (SysTol).

[12]  Nan Wu,et al.  Automatic driving system by small electric vehicle for elderly person , 2012, 2012 Proceedings of SICE Annual Conference (SICE).

[13]  Xiaoxia Wang,et al.  Vehicle active security based on driver modeling , 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

[14]  T. Tomizawa,et al.  Development of an intelligent mobility scooter , 2012, 2012 IEEE International Conference on Mechatronics and Automation.

[15]  Junmin Wang,et al.  Lightweight Vehicle Control-Oriented Modeling and Payload Parameter Sensitivity Analysis , 2011, IEEE Transactions on Vehicular Technology.

[16]  Saeid Nahavandi,et al.  A collision avoidance system with fuzzy danger level detection , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).

[17]  Nobuyo Kasuga,et al.  Study on Deceleration Pattern of Automatic Braking , 2008 .

[18]  Wang Lifeng,et al.  The Security Technology and Tendency of New Energy Vehicle in the Future , 2013, 2013 Fifth International Conference on Measuring Technology and Mechatronics Automation.

[19]  Halpage Chinthaka Nuwandika Premachandra,et al.  A study on smooth automatic vehicle stopping control for suddenly-appeared obstacles , 2015, 2015 IEEE International Conference on Vehicular Electronics and Safety (ICVES).

[20]  Peter Sergeant,et al.  Drivetrain design for an ultra light electric vehicle with high efficiency , 2013, 2013 World Electric Vehicle Symposium and Exhibition (EVS27).

[21]  Hong Jeong,et al.  Stereo-based road obstacle detection and tracking , 2011, 13th International Conference on Advanced Communication Technology (ICACT2011).

[22]  Fuqiang Liu,et al.  Real-Time Stereovision Approach of Object Detection for Driving Assistance , 2009, International Congress on Image and Signal Processing.

[23]  Yuki Matsumoto,et al.  A Study on Autonomous Entering into Narrow Path Using a Mobile Robot , 2018, 2018 3rd International Conference on Information Technology Research (ICITR).

[24]  Erwan Sulaiman,et al.  Development of a novel permanent magnet flux switching machine prototype for light weight electric vehicles , 2015, 2015 IEEE Student Conference on Research and Development (SCOReD).

[25]  Sadayuki Tsugawa.  The current trends and issues on ITS in Japan: Safety, energy and environment , 2011, 2011 IEEE MTT-S International Microwave Workshop Series on Intelligent Radio for Future Personal Terminals.

[26]  Lesley A Ross,et al.  Examination of cognitive and instrumental functional performance as indicators for driving cessation risk across 3 years. , 2008, The Gerontologist.

[27]  Sergiu Nedevschi,et al.  Superpixel-based obstacle segmentation from dense stereo urban traffic scenarios using intensity, depth and optical flow information , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[28]  Jonas Sjöberg,et al.  Model-Based Threat Assessment for Avoiding Arbitrary Vehicle Collisions , 2010, IEEE Transactions on Intelligent Transportation Systems.

[29]  Yu Chunxuan,et al.  Any type of obstacle detection in complex environments based on monocular vision , 2013, Proceedings of the 32nd Chinese Control Conference.

[30]  Halpage Chinthaka Nuwandika Premachandra,et al.  A Study on Computational Time Reduction of Road Obstacle Detection by Parallel Image Processor , 2014, J. Adv. Comput. Intell. Intell. Informatics.

[31]  Chinthaka Premachandra,et al.  Development of hybrid aerial/terrestrial robot system and its automation , 2017, 2017 IEEE International Systems Engineering Symposium (ISSE).

[32]  Halpage Chinthaka Nuwandika Premachandra,et al.  A study on development of a hybrid aerial / terrestrial robot system for avoiding ground obstacles by flight , 2019, IEEE/CAA Journal of Automatica Sinica.

[33]  Shin Kato,et al.  An automated truck platoon for energy saving , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.