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.
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