There is an increasing demand for application of Intelligent Transportation Systems (ITS) in order to make highways safer and sustainable. Collecting and analyzing traffic stream data are the most important parameters in transportation engineering in enhancing our understanding of traffic congestion and mobility. Classification of the vehicles using traffic data is one of the most essential parameters for traffic management. Of particular interest are heavy vehicles which impact traffic mobility due to their lack of maneuverability and slower speeds. The impact of heavy vehicles on the traffic stream results in congestion and reduction of road efficiency. In this paper, length-based vehicle count and speed data were analyzed and interpreted using one week's data from Interstate 5 (I-5) in the Portland, Oregon (OR) region of the United States (US). I-5 was chosen due to its prominent role in promoting North-South freight movement between Canada and Mexico and its vicinity to the Port of Portland. The objective of this analysis was to find better visualization techniques for the length-based traffic count and speed data. In total, 13,901,793 out of 56,146,138 20-second records were analyzed. The vehicles were classified into two categories. Those that were 20 feet or less were considered as passenger vehicles and those above 20 feet were considered as heavy vehicles. The data consisted of approximately 25% heavy vehicles. Results showed the merit of applying more disaggregate data (5-min polar, and radar plots) for better visualization as against hourly, and 15-min plots in order to capture sudden changes in average speed, heavy vehicle volume, and heavy vehicle percentage.

The goal of this master thesis was to study the theory and to realize an induction loop for railway rolling vehicles, to design and manufacture a functioning prototype of electronic amplifier, which carries out all the requirements. This thesis includes detailed information about the induction loop system, its position and performance, following with the design of the amplifier, execution of the design and with the conclusion of measured parameters for the accomplishment of the required parameters.

This thesis descries the evolution and testing of a fully portable, inductive loop vehicle counter system. As a component of the NFS Embedded Distributed Simulation for Transportation System Management project, the system's cellular modem transmits real-time data to servers at Georgia Institute of Technology. From there, the data can be fed into simulations predicting travel behavior. Researchers revised both the detector circuit, and the temporary, reusable loop pad several times over multiple rounds of field testing. The final tested version of this system demonstrates the efficacy of uncommonly small inductive loops. When paired with a reliable data transmission channel, the system was shown to capture nearly 96% of actual through traffic.