Intelligent Vehicle Counting and Classification Sensor for Real-Time Traffic Surveillance

Real-time traffic surveillance is essential in today’s intelligent transportation systems and will surely play a vital role in tomorrow’s smart cities. The work detailed in this paper reports on the development and implementation of a novel smart wireless sensor for traffic monitoring. Computationally efficient and reliable algorithms for vehicle detection, speed and length estimation, classification, and time-synchronization were fully developed, integrated, and evaluated. Comprehensive system evaluation and extensive data analysis were performed to tune and validate the system for a reliable and robust operation. Several field studies conducted on highway and urban roads for different scenarios and under various traffic conditions resulted in 99.98% detection accuracy, 97.11% speed estimation accuracy, and 97% length-based vehicle classification accuracy. The developed system is portable, reliable, and cost-effective. The system can also be used for short-term or long-term installment on surface of highway, roadway, and roadside. Implementation cost of a single node including enclosure is US $50.

[1]  Enjarla,et al.  Portable Roadside Sensors for Vehicle Counting , Classification , And Speed Measurement , 2015 .

[2]  Boris R. Andrievsky,et al.  Vehicle speed estimation using roadside sensors , 2014, 2014 6th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT).

[3]  Ho Lee Identifying and Correcting Pulse Breakup Errors from Freeway Loop Detectors , 2011 .

[4]  Jinhui Lan,et al.  Vehicle detection and recognition based on a MEMS magnetic sensor , 2009, 2009 4th IEEE International Conference on Nano/Micro Engineered and Molecular Systems.

[5]  Gábor Stépán,et al.  Traffic jams: dynamics and control , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[6]  Kyoung Ho Choi,et al.  Performance of vehicle speed estimation using wireless sensor networks: a region-based approach , 2014, The Journal of Supercomputing.

[7]  Hazem H. Refai,et al.  Versatile real-time traffic monitoring system using wireless smart sensors networks , 2016, 2016 IEEE Wireless Communications and Networking Conference.

[8]  Gyula Simon,et al.  Magnetic-based vehicle detection with sensor networks , 2013, 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[9]  Wei Zhang,et al.  Vehicle Speed Estimation Based on Sensor Networks and Signal Correlation Measurement , 2013, CWSN.

[10]  Hazem H. Refai,et al.  iICAS: Intelligent intersection collision avoidance system , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[11]  Sing Yiu Cheung,et al.  Traffic Surveillance by Wireless Sensor Networks: Final Report , 2007 .

[12]  Fengqi Yu,et al.  A Street Parking System Using Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[13]  Peng Zhang,et al.  Vehicle Class Composition Identification Based Mean Speed Estimation Algorithm Using Single Magnetic Sensor , 2010 .

[14]  Yuchuan Du,et al.  Improved waveform-feature-based vehicle classification using a single-point magnetic sensor , 2015 .

[15]  Pravin Varaiya,et al.  Wireless magnetic sensors for traffic surveillance , 2008 .

[16]  Hazem H. Refai,et al.  Development of Portable Wireless Sensor Network System for Real-Time Traffic Surveillance , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[17]  Guangyou Fang,et al.  Direction identification of a moving ferromagnetic object by magnetic anomaly , 2015 .

[18]  Lawrence A Klein,et al.  SUMMARY OF VEHICLE DETECTION AND SURVEILLANCE TECHNOLOGIES USED IN INTELLIGENT TRANSPORTATION SYSTEMS , 2000 .

[19]  Walid Balid FULLY AUTONOMOUS SELF-POWERED INTELLIGENT WIRELESS SENSOR FOR REAL-TIME TRAFFIC SURVEILLANCE IN SMART CITIES , 2016 .

[20]  Fredrik Gustafsson,et al.  Classification of Driving Direction in Traffic Surveillance Using Magnetometers , 2014, IEEE Transactions on Intelligent Transportation Systems.

[21]  Fengqi Yu,et al.  A Vehicle Parking Detection Method Based on Correlation of Magnetic Signals , 2015, Int. J. Distributed Sens. Networks.

[22]  Kun Liu,et al.  New method for detecting traffic information based on anisotropic magnetoresistive technology , 2013, Other Conferences.

[23]  Ding Nan,et al.  Low-power Vehicle Speed Estimation Algorithm based on WSN , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[24]  Bo Yang,et al.  Vehicle Detection and Classification for Low-Speed Congested Traffic With Anisotropic Magnetoresistive Sensor , 2015, IEEE Sensors Journal.

[25]  Jinhui Lan,et al.  Vehicle detection and classification by measuring and processing magnetic signal , 2011 .

[26]  Wei Zhang,et al.  A Distributed Threshold Algorithm for Vehicle Classification Based on Binary Proximity Sensors and Intelligent Neuron Classifier , 2010, J. Inf. Sci. Eng..

[27]  Li Cui,et al.  Real-time Traffic Monitoring with Magnetic Sensor Networks , 2011, J. Inf. Sci. Eng..

[28]  Roland Hostettler,et al.  Comparison of Machine Learning Techniques for Vehicle Classification Using Road Side Sensors , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[29]  Limin Jia,et al.  Some practical vehicle speed estimation methods by a single traffic magnetic sensor , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[30]  Zygmunt J. Haas,et al.  A Comprehensive Approach to WSN-Based ITS Applications: A Survey , 2011, Sensors.

[31]  Michael Tucker,et al.  Carbon dioxide emissions and global GDP , 1995 .

[32]  Su-Lim Tan,et al.  Road traffic monitoring using a wireless vehicle sensor network , 2009, 2008 International Symposium on Intelligent Signal Processing and Communications Systems.

[33]  Pravin Varaiya,et al.  A Wireless Accelerometer-Based Automatic Vehicle Classification Prototype System , 2014, IEEE Transactions on Intelligent Transportation Systems.