D. Miklušis “Traffic flow characterization using passive electronic sensors” doctoral dissertation defense

Author, Institution: Donatas Miklušis, Kaunas University of Technology

Science area, field of science: Technological Sciences, Electrical and Electronics Engineering, T001

Scientific Supervisor: Prof. Dr. Vytautas Markevičius (Kaunas University of Technology, Electrical and Electronics Engineering, T001)

Dissertation Defense Board of Electrical and Electronics Engineering Science Field:
Prof. Dr. Elena Jasiūnienė (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering, T001) – chairperson
Prof. Dr. Vaidotas Barzdėnas (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering, T007)
Prof. Dr. Hab. Arūnas Lukoševičius (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering, T001)
Prof. Dr. Michal Prauzek (Technical University of Ostrava, Czech Republic, Technological Sciences, Transport Engineering, T003)
Assoc. Prof. Dr. Reimondas Šliteris (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering, T001)

Dissertation defense meeting will be at Rectorate Hall of Kaunas University of Technology (K. Donelaičio 73-402, Kaunas)

The doctoral dissertation is available at the library of Kaunas University of Technology (Gedimino 50, Kaunas)

Annotation: The increasing urbanization of cities leads to an ever-expanding road infrastructure and an increase in the number of motor vehicles. In order to use available resources as effectively as possible, intelligent monitoring of traffic flows and modernization of road infrastructure are necessary. The main task of intelligent traffic flow management systems is to accurately characterize traffic flows, i.e., to measure traffic flow volume and speed, and to perform classification. Data collection systems have three main functional requirements: to capture the direction of movement, to measure the speed and length of the vehicle, and to perform classification tasks. Passive electronic sensors, such as micro-electromechanical systems (MEMS) accelerometers, anisotropic magneto-resistive (AMR) and piezoelectric polyvinylidene fluoride (PVDF) sensors, are very suitable due to their unique advantages, such as low sensitivity to climatic and lighting conditions, less intervention in the road surface during their installation, relatively low installation costs, small dimensions, low power consumption, and compatibility with the Internet of Things (IoT) concept. In this work a sophisticated monitoring station equipped with passive electronic sensors and innovative processing algorithms was investigated. A recognition methodology incorporating detection criteria and correction algorithms tailored for distorted magnetic signatures is proposed. Furthermore, with help of industrial partners, a semi-permanent traffic flow characterization system of combined sensors was presented and realized. The latter incorporates AMR magnetic field sensors installed at 0.3 m distance apart alongside MEMS accelerometers and PVDF strips. Extensive tests in real traffic scenarios during winter and summer conditions in Lithuania have demonstrated the robustness of the system and its compatibility with low-power wireless sensor networks.