State-of-the-Art in Irregular Driving Detection

In this chapter, the definition of irregular driving and the importance of its detection are set out, along with related recent research. In particular, for the review of the irregular driving detection research: firstly, the relevant research to date is reviewed; secondly, in-car positioning technology, which is the core technology behind lane level positioning, based on vehicle motion sensors and models and filter algorithms for sensor integration, is presented; finally, driving pattern recognition algorithms are discussed.

[1]  Antonella Ferrara,et al.  Application of Switching Control for Automatic Pre-Crash Collision Avoidance in Cars , 2006 .

[2]  G. Schmidt,et al.  Inertial sensor technology trends , 2001 .

[3]  Jay A. Farrell,et al.  Magnetometer and differential carrier phase GPS-aided INS for advanced vehicle control , 2003, IEEE Trans. Robotics Autom..

[4]  Sou-Chen Lee,et al.  Gyroscope Free Strapdown Inertial Measurement Unit by Six Linear Accelerometers , 1994 .

[5]  James L. Farrell Inertial Instrument Error Characterization , 2007 .

[6]  Yuichi Motai,et al.  Multiple model framework of adaptive extended kalman filtering for predicting vehicle location , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[7]  Mohinder S. Grewal,et al.  Global Positioning Systems, Inertial Navigation, and Integration , 2000 .

[8]  Mahamod Ismail,et al.  Abnormal driving detection using real time Global Positioning System data , 2011, Proceeding of the 2011 IEEE International Conference on Space Science and Communication (IconSpace).

[9]  Dong Xuan,et al.  Mobile phone based drunk driving detection , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.

[10]  Yakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .

[11]  A. Lambert,et al.  Reducing Navigation Errors by Planning with Realistic Vehicle Model , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[12]  Han-Shue Tan,et al.  DGPS-Based Vehicle-to-Vehicle Cooperative Collision Warning: Engineering Feasibility Viewpoints , 2006, IEEE Transactions on Intelligent Transportation Systems.

[13]  Liqiang Feng,et al.  Measurement and correction of systematic odometry errors in mobile robots , 1996, IEEE Trans. Robotics Autom..

[14]  A. Decherney,et al.  Turn, Turn, Turn , 1987, Diabetes Care.

[15]  Fumihiko Sakaue,et al.  Detection of abnormal driving using multiple view geometry in space-time , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[16]  Kenneth R Britting,et al.  Inertial navigation systems analysis , 1971 .

[17]  Jinling Wang,et al.  Adaptive estimation of multiple fading factors in Kalman filter for navigation applications , 2008 .

[18]  Brian N. Fildes,et al.  COST-EFFECTIVE INFRASTRUCTURE MEASURES ON RURAL ROADS , 2004 .

[19]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[20]  Gregory Dudek,et al.  Probabilistic cooperative localization and mapping in practice , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[21]  Zhiwei Zhu,et al.  Real time and non-intrusive driver fatigue monitoring , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[22]  Angelos Amditis,et al.  Sensor Fusion for Predicting Vehicles' Path for Collision Avoidance Systems , 2007, IEEE Transactions on Intelligent Transportation Systems.

[23]  Hiromi Okada,et al.  Vehicular-Collision Avoidance Support System (VCASS) by Inter-Vehicle Communications for Advanced ITS , 2005, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[24]  Nikolaos Papanikolopoulos,et al.  Driver fatigue: a vision-based approach to automatic diagnosis , 2001 .

[25]  Zixing Cai,et al.  Kinematics model of unmanned driving vehicle , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[26]  Fredrik Gustafsson,et al.  Particle filters for positioning, navigation, and tracking , 2002, IEEE Trans. Signal Process..

[27]  Mona Omidyeganeh,et al.  Intelligent driver drowsiness detection through fusion of yawning and eye closure , 2011, 2011 IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems Proceedings.

[28]  Jarek Krajewski,et al.  Steering wheel behavior based estimation of fatigue , 2017 .

[29]  Gerd Wanielik,et al.  Advanced Filtering Techniques for Multisensor Vehicle Tracking , 2008 .

[30]  Isaac Skog,et al.  In-Car Positioning and Navigation Technologies—A Survey , 2009, IEEE Transactions on Intelligent Transportation Systems.

[31]  C.R. Jung,et al.  A lane departure warning system using lateral offset with uncalibrated camera , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[32]  A V Desai,et al.  Vigilance monitoring for operator safety: A simulation study on highway driving. , 2006, Journal of safety research.

[33]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[34]  Marco Calabrese,et al.  Experimental System to Support Real-Time Driving Pattern Recognition , 2008, ICIC.

[35]  J. David Powell,et al.  Error Sources When Land Vehicle Dead Reckoning with Differential Wheelspeeds , 2004 .

[36]  Yilin Zhao,et al.  Vehicle Location And Navigation Systems , 1997 .

[37]  Chih-Sheng Hsu,et al.  Onboard Measurement and Warning Module for Irregular Vehicle Behavior , 2008, IEEE Transactions on Intelligent Transportation Systems.

[38]  Young Jae Lee,et al.  Artificial neural networks for predicting DGPS carrier phase and pseudorange correction , 2008 .

[39]  Sukhan Lee,et al.  Experiments on decision making strategies for a lane departure warning system , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[40]  D. Powell,et al.  Land-vehicle navigation using GPS , 1999, Proc. IEEE.

[41]  C.R. Jung,et al.  A lane departure warning system based on a linear-parabolic lane model , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[42]  Gerd Wanielik,et al.  High-accurate vehicle localization using digital maps and coherency images , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[43]  Wilfried Enkelmann,et al.  A video-based lane keeping assistant , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[44]  Ahmad Aljaafreh,et al.  Web Driving Performance Monitoring System , 2012 .

[45]  Cláudio Rosito Jung,et al.  Lane following and lane departure using a linear-parabolic model , 2005, Image Vis. Comput..

[46]  Hiroshi Mouri,et al.  A Study on Vehicle Lane Departure Delay System , 2006 .

[47]  Araki Hideo,et al.  Development of rear-end collision avoidance system , 1997 .

[48]  Joon Woong Lee,et al.  A lane-departure identification based on LBPE, Hough transform, and linear regression , 2005, Comput. Vis. Image Underst..

[49]  Han Wang,et al.  Adaptive state estimation for 4-wheel steerable industrial vehicles , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[50]  Udo Trutschel,et al.  TECHNOLOGIES FOR THE MONITORING AND PREVENTION OF DRIVER FATIGUE , 2017 .

[51]  David Mais,et al.  Reported Road Casualties in Great Britain: Main Results 2013 , 2014 .

[52]  Hugh F. Durrant-Whyte,et al.  On the role of process models in autonomous land vehicle navigation systems , 2003, IEEE Trans. Robotics Autom..

[53]  Sungsu Park,et al.  Design of accelerometer-based inertial navigation systems , 2005, IEEE Transactions on Instrumentation and Measurement.

[54]  P. Pongpaibool,et al.  Detection of hazardous driving behavior using fuzzy logic , 2008, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[55]  A.B. Albu,et al.  A computer vision-based system for real-time detection of sleep onset in fatigued drivers , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[56]  Gerd Wanielik,et al.  Comparison and evaluation of advanced motion models for vehicle tracking , 2008, 2008 11th International Conference on Information Fusion.

[57]  Anna Anund,et al.  Detecting Driver Sleepiness Using Optimized Nonlinear Combinations of Sleepiness Indicators , 2011, IEEE Transactions on Intelligent Transportation Systems.

[58]  F. Daum Nonlinear filters: beyond the Kalman filter , 2005, IEEE Aerospace and Electronic Systems Magazine.

[59]  John Weston,et al.  Strapdown Inertial Navigation Technology, Second Edition , 2005 .