Developing highly sensitive and energy-saving sensor with quantum tunneling composites for multiple-parameter traffic detection


Global increase in vehicular volume has seen a surge in traffic congestion, traffic violations, traffic incident and road damage. As such, it is increasingly becoming difficult to ascertain traffic safety and the management of various public facilities. The best way to avert tragedies arising from the aforementioned issues is through the collection of traffic data to help in real-time management and control. Traffic volumes fluctuate continuously thus necessitating the utilization of intricate data collection techniques. To date, traffic detection sensors, such as: inductive loops and video cameras, have been widely deployed, however, their application is limited as the former are susceptible to external electromagnetic interference and the latter have a poor detection accuracy.

Recently, conductive rubber-based composites that depend on the type and morphology of filler particles have been proposed. Presently, spiky spherical nickel powder possessing sharp surface protrusions have proven effective owing to their high pressure-sensitive property. These composites, popularly termed quantum tunneling composites (QTC), despite their excellent attributes, are yet to be utilized in vehicle detection.

In a recent publication, Dalian University of Technology researchers Professor Baoguo Han, Siqi Ding (PhD candidate), Yan Yu and Sufen Dong together with Professor Jinping Ou and also professor Xun Yu at New York Institute of Technology presented a study where they proposed a novel type of traffic detection sensor based on QTCs. Their goal was to develop a vehicle detection system that is all round in terms of data capture and collection. Their work is currently published in the research journal, IEEE Sensors Journal.

In general, the team investigated the performance of the developed QTC sensors for traffic detection by measuring the pressure sensitive response of QTC sensors with different sensitivities to different types of vehicles and different vehicle speeds on an experimental road. In addition, they performed a road test of real-tine traffic on a dual-lane road so as to investigate the feasibility of the QTC sensors for practical applications.

The team reported that the QTC sensors with high sensitivity could accurately detect the passing of different vehicles under different vehicular speeds and test environments. Additionally, the double-rows QTC sensors could measure vehicle speeds easily and precisely. The team also highlighted that with the novel QTC system, it was possible to measure the vehicle speeds with one QTC sensor per lane.

In summary, Professor Baoguo Han and colleagues introduced a novel type of traffic detection sensors based on QTCs and successfully investigated and practically tested in a bid to assess its feasibility for application in traffic detection. Interestingly, the novel system was able to capture a lot of traffic data, including: vehicle presence, vehicle weigh-in-motion, position, vehicle occupancy rate, vehicle count, and vehicle classification in real-time traffic. The QTC sensors were seen to possess high detection precision, fast response and recovery excellent robustness, energy saving, easy installation and maintenance. Altogether, the system could provide an alternative source of data support for traffic control and management among other applications.

Developing highly sensitive and energy-saving sensor with quantum tunneling composites for multiple-parameter traffic detection - Advances in Engineering

About the author

Baoguo Han received his PhD in the field of smart materials and structures from the Harbin Institute of Technology, China, in 2005. He is currently a professor of civil engineering in the Dalian University of Technology, China. His main research interests include cement and concrete materials, smart materials and structures, multifunctional composites, nanotechnology, sensing technology, and structural health monitoring and traffic detection.

He is a member of the editorial board of five international journals and has published 3 books (Self-Sensing Concrete in Smart Structures, Elsevier 2014; Smart and Multifunctional Concrete toward Sustainable Infrastructures, Springer 2017; Nano-Engineered Cementitious Composites: Principles and Practices, Springer 2019), 12 book chapters and more than 150 technical papers. He has hold more than 10 authorized national invention patents. He was invited to the University of Minnesota and has worked as a visiting research scholar there for 3 years. He was also awarded the New Century Excellent Talents in University and the First Prize of Natural Science by the Ministry of Education of China.

ResearchGate, Google Scholar

About the author

Siqi Ding is currently a PhD candidate at the Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong. His main research interests include smart materials and structures, nanotechnology, sensors and structural health monitoring. He has authored 1 book (Springer) and 6 book chapters.

He has published 16 technical papers in reputable journals such as Polymer, Composites Part B: Engineering, Composites Part A: Applied Science and Manufacturing and Construction and Building Materials, and authorized 1 national invention patent. He has delivered presentations in many prestigious international conferences such as Engineering Mechanics Institute Conference 2018 and Sixth International Symposium on Nanotechnology in Construction.

Webpage link

ResearchGate, Google Scholar


Baoguo Han, Siqi Ding, Yan Yu, Member, Xun Yu, Sufen Dong, and Jinping Ou. Design and Implementation of a Multiple Traffic Parameter Detection Sensor Developed with Quantum Tunneling Composites. IEEE Sensors Journal, Volume 15, No. 9, September 2015.

Go To IEEE Sensors Journal

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