Pedestrian Protection Systems: Issues, Survey, and Challenges

This paper describes the recent research on the enhancement of pedestrian safety to help develop a better understanding of the nature, issues, approaches, and challenges surrounding the problem. It presents a comprehensive review of research efforts underway dealing with pedestrian safety and collision avoidance. The importance of pedestrian protection is emphasized in a global context, discussing the research programs and efforts in various countries. Pedestrian safety measures, including infrastructure enhancements and passive safety features in vehicles, are described, followed by a systematic description of active safety systems based on pedestrian detection using sensors in vehicle and infrastructure. The pedestrian detection approaches are classified according to various criteria such as the type and configuration of sensors, as well as the video cues and classifiers used in detection algorithms. It is noted that collision avoidance not only requires detection of pedestrians but also requires collision prediction using pedestrian dynamics and behavior analysis. Hence, this paper includes research dealing with probabilistic modeling of pedestrian behavior for predicting collisions between pedestrians and vehicles.

[1]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[2]  Mohan M. Trivedi,et al.  Moving shadow and object detection in traffic scenes , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[3]  Liang Zhao,et al.  Stereo- and neural network-based pedestrian detection , 2000, IEEE Trans. Intell. Transp. Syst..

[4]  Uwe Franke,et al.  Real-time stereo vision for urban traffic scene understanding , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[5]  Mohan M. Trivedi,et al.  Distributed video networks for incident detection and management , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[6]  Mohan M. Trivedi,et al.  Database-centered architecture for traffic incident detection, management, and analysis , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[7]  S Milch,et al.  PEDESTRIAN DETECTION WITH RADAR AND COMPUTER VISION , 2001 .

[8]  Dariu Gavrila,et al.  Sensor-Based Pedestrian Protection , 2001, IEEE Intell. Syst..

[9]  V. Willhoeft,et al.  Object tracking and classification using laserscanners-pedestrian recognition in urban environment , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[10]  Charles V. Zegeer,et al.  Safety Effects of Marked Versus Unmarked Crosswalks at Uncontrolled Locations: Analysis of Pedestrian Crashes in 30 Cities , 2001 .

[11]  Tim J. Ellis,et al.  Spatial and Probabilistic Modelling of Pedestrian Behaviour , 2002, BMVC.

[12]  L. McCloskey,et al.  Crosswalk markings and the risk of pedestrian-motor vehicle collisions in older pedestrians. , 2002, JAMA.

[13]  Dinesh Mohan WORK TRIPS AND SAFETY OF BICYCLISTS , 2002 .

[14]  Klaus Dietmayer,et al.  Pedestrian recognition in urban traffic using a vehicle based multilayer laserscanner , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[15]  Mark Howard,et al.  Comprehensive approach to increased pedestrian safety in pedestrian-to-car accidents , 2002 .

[16]  Massimo Bertozzi,et al.  Artificial vision in road vehicles , 2002, Proc. IEEE.

[17]  J. Crandall,et al.  Designing road vehicles for pedestrian protection , 2002, BMJ : British Medical Journal.

[18]  Hiroshi Hattori,et al.  Development of night-vision system , 2002, IEEE Trans. Intell. Transp. Syst..

[19]  Shigeru Okuma,et al.  Active frame subtraction for pedestrian detection from images of moving camera , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[20]  Keiichi Yamada,et al.  Comparison between infrared-image-based and visible-image-based approaches for pedestrian detection , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[21]  Mohan M. Trivedi,et al.  Detecting Moving Shadows: Algorithms and Evaluation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Osama Masoud,et al.  Computer vision algorithms for intersection monitoring , 2003, IEEE Trans. Intell. Transp. Syst..

[23]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[24]  J. Stewart,et al.  SAFETY ANALYSIS OF MARKED VS UNMARKED CROSSWALKS IN 30 CITIES , 2003 .

[25]  Anne T McCartt,et al.  A review of evidence-based traffic engineering measures designed to reduce pedestrian-motor vehicle crashes. , 2003, American journal of public health.

[26]  T. Poggio,et al.  Direction Estimation of Pedestrian from Images , 2003 .

[27]  Q. M. Tian,et al.  Pedestrian detection in nighttime driving , 2004, Third International Conference on Image and Graphics (ICIG'04).

[28]  Keiichi Yamada,et al.  A shape-independent method for pedestrian detection with far-infrared images , 2004, IEEE Transactions on Vehicular Technology.

[29]  A. Shashua,et al.  Pedestrian detection for driving assistance systems: single-frame classification and system level performance , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[30]  A. Broggi,et al.  A multi-resolution approach for infrared vision-based pedestrian detection , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[31]  László Havasi,et al.  Pedestrian Detection using derived Third-Order Symmetry of Legs , 2004 .

[32]  Ching-Yao Chan,et al.  Impact of Pedestrian Presence on Movement of Left-Turning Vehicles: Method, Preliminary Results & Possible Use in Intersection Decision Support , 2004 .

[33]  L. Andreone,et al.  Developing a near infrared based night vision system , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[34]  Gabriel K. Rousseau,et al.  SEEING CROSSWALKS IN A NEW LIGHT , 2004 .

[35]  D.M. Gavrila,et al.  Vision-based pedestrian detection: the PROTECTOR system , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[36]  W. Ritter,et al.  Reinforcing the reliability of pedestrian detection in far-infrared sensing , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[37]  C. Thorpe,et al.  Development of the side component of the transit integrated collision warning system , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[38]  M.-M. Meinecke,et al.  Radar sensors and sensor platform used for pedestrian protection in the EC-funded project SAVE-U , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[39]  Hui Sun,et al.  A multi-stage classifier based algorithm of pedestrian detection in night with a near infrared camera in a moving car , 2004, Third International Conference on Image and Graphics (ICIG'04).

[40]  Toshihiro Osaragi Modeling of pedestrian behavior and its applications to spatial evaluation , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[41]  F. Large,et al.  Avoiding cars and pedestrians using velocity obstacles and motion prediction , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[42]  Christophe F. Wakim,et al.  A Markovian model of pedestrian behavior , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[43]  A. Ferrara Automatic pre-crash collision avoidance in cars , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[44]  F. Rivara,et al.  Strengthening the prevention and care of injuries worldwide , 2004, The Lancet.

[45]  A. Zelinsky,et al.  3D vision sensing for improved pedestrian safety , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[46]  B. Zavidovique,et al.  A context-dependent vision system for pedestrian detection , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[47]  G. Wanielik,et al.  Multi sensor based tracking of pedestrians: a survey of suitable movement models , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[48]  Tomaso A. Poggio,et al.  A Trainable System for Object Detection , 2000, International Journal of Computer Vision.

[49]  B. Steux,et al.  Hardware-friendly pedestrian detection and impact prediction , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[50]  Xia Liu,et al.  Pedestrian detection using stereo night vision , 2004, IEEE Transactions on Vehicular Technology.

[51]  Margaret M. Peden,et al.  World Report on Road Traffic Injury Prevention , 2004 .

[52]  J. Richard Stewart,et al.  Safety Analysis of Marked Versus Unmarked Crosswalks in 30 Cities , 2004 .

[53]  M. Bierlaire,et al.  A discrete choice pedestrian behavior model for pedestrian detection in visual tracking systems , 2004 .

[54]  Steven E Shladover,et al.  Effects of Traffic Density on Communication Requirements for Cooperative Intersection Collision Avoidance Systems (CICAS) , 2005 .

[55]  F. Bu,et al.  Pedestrian detection in transit bus application: sensing technologies and safety solutions , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[56]  M. Mahlisch,et al.  A multiple detector approach to low-resolution FIR pedestrian recognition , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[57]  Bernt Schiele,et al.  Pedestrian detection in crowded scenes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[58]  K.Ch. Fuerstenberg,et al.  Pedestrian protection using laserscanners , 2005 .

[59]  Richard Bishop,et al.  Intelligent Vehicle Technology and Trends , 2005 .

[60]  Nanning Zheng,et al.  Pedestrian detection using sparse Gabor filter and support vector machine , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[61]  Arturo de la Escalera,et al.  Pedestrian Detection for Intelligent Vehicles Based on Active Contour Models and Stereo Vision , 2005, EUROCAST.

[62]  Kuntal Sengupta,et al.  Framework for real-time behavior interpretation from traffic video , 2005, IEEE Transactions on Intelligent Transportation Systems.

[63]  P. Prasanna,et al.  Probabilistic signal interpretation methods for a thermopile pedestrian detection system , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[64]  Paul A. Viola,et al.  Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.

[65]  Tarak Gandhi,et al.  Vehicle mounted wide FOV stereo for traffic and pedestrian detection , 2005, IEEE International Conference on Image Processing 2005.

[66]  M. Szarvas,et al.  Pedestrian detection with convolutional neural networks , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[67]  Osama Masoud,et al.  A collision prediction system for traffic intersections , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[68]  S. Singh Review of Urban Transportation in India , 2005 .

[69]  Michel Bierlaire,et al.  Behavioral Priors for Detection and Tracking of Pedestrians in Video Sequences , 2006, International Journal of Computer Vision.

[70]  F. Suard,et al.  Pedestrian detection using stereo-vision and graph kernels , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[71]  Joachim Schäfer,et al.  Structural Hood and Hinge Concepts for Pedestrian Protection , 2005 .

[72]  L. Andreone,et al.  SVM-based pedestrian recognition on near-infrared images , 2005, ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005..

[73]  David R. Ragland,et al.  Observations of driver time gap acceptance at intersections in left-turn across-path-opposite-direction scenarios , 2005 .

[74]  Xia Liu,et al.  Pedestrian detection and tracking with night vision , 2005, IEEE Transactions on Intelligent Transportation Systems.

[75]  Hideki Hashimoto,et al.  Pedestrian-behavior-based mobile agent control in intelligent space , 2005, IEEE Transactions on Instrumentation and Measurement.

[76]  Marc-Michael Meinecke,et al.  SAVE-U: First Experiences with a Pre-Crash System for Enhancing Pedestrian Safety , 2005 .

[77]  Tarak Gandhi,et al.  Distributed interactive video arrays for event capture and enhanced situational awareness , 2005, IEEE Intelligent Systems.

[78]  M. Szarvas,et al.  Real-time Pedestrian Detection Using LIDAR and Convolutional Neural Networks , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[79]  Y. W. Xu,et al.  A Cascaded Classifier for Pedestrian Detection , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[80]  Mohan M. Trivedi,et al.  Multimodal Stereo Image Registration for Pedestrian Detection , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[81]  M. Trivedi,et al.  Analysis and query of person-vehicle interactions in homography domain , 2006, VSSN '06.

[82]  Tarak Gandhi,et al.  Vehicle Surround Capture: Survey of Techniques and a Novel Omni-Video-Based Approach for Dynamic Panoramic Surround Maps , 2006, IEEE Transactions on Intelligent Transportation Systems.

[83]  A. Broggi,et al.  Low-level Pedestrian Detection by means of Visible and Far Infra-red Tetra-vision , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[84]  Yan Zhang,et al.  Robust Moving Object Detection at Distance in the Visible Spectrum and Beyond Using A Moving Camera , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[85]  M. Bierlaire,et al.  Capturing interactions in pedestrian walking behavior in a discrete choice framework , 2006 .

[86]  Tarak Gandhi,et al.  Pedestrian collision avoidance systems: a survey of computer vision based recent studies , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[87]  Dariu Gavrila,et al.  An Experimental Study on Pedestrian Classification , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[88]  A. Broggi,et al.  Pedestrian Detection using Infrared images and Histograms of Oriented Gradients , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[89]  Dariu Gavrila,et al.  Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle , 2007, International Journal of Computer Vision.

[90]  G. Wanielik,et al.  Obstacle Detection and Pedestrian Recognition Using A 3D PMD Camera , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[91]  Michel Bierlaire,et al.  Discrete Choice Models for Pedestrian Walking Behavior , 2006 .

[92]  G. Wanielik,et al.  Motion-based pedesvtrian recognition from a moving vehicle , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[93]  Ignacio Parra,et al.  Pedestrian Detection Using SVM and Multi-Feature Combination , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[94]  Tarak Gandhi,et al.  Looking-In and Looking-Out of a Vehicle: Computer-Vision-Based Enhanced Vehicle Safety , 2007, IEEE Transactions on Intelligent Transportation Systems.

[95]  S.J. Krotosky,et al.  A Comparison of Color and Infrared Stereo Approaches to Pedestrian Detection , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[96]  Mohan M. Trivedi,et al.  On Color-, Infrared-, and Multimodal-Stereo Approaches to Pedestrian Detection , 2007, IEEE Transactions on Intelligent Transportation Systems.