This paper documents the development of data collection methodologies that can be used to measure truck movements along specific roadway corridors in Washington State cost-effectively. The intent of this study was to design and test methodologies that could provide information to ascertain the performance of freight mobility roadway improvement projects. The benchmarks created would be used to report on speed and volume improvements that resulted from completed roadway projects. One technology tested consisted of Commercial Vehicle Information System and Networks electronic truck transponders, which were mounted on the windshields of approximately 30,000 trucks traveling in Washington. These transponders were used at weigh stations across the state to improve the efficiency of truck regulatory compliance checks. With transponder reads from sites anywhere in the state being linked through software, the transponder-equipped trucks can become a travel time probe fleet. The second technology tested involved Global Positioning Systems (GPS) placed in volunteer trucks to collect specific truck movement data at 5-s intervals. GPS data made it possible to locate when and where monitored trucks experienced congestion. With this information aggregated over time, it was possible to generate performance statistics related to the reliability of truck trips and even to examine changes in route choice for trips between high-volume origin–destination pairs. The study found that both data collection technologies could be useful; however, the key to either technology is whether enough instrumented vehicles pass over the roadways for which data are required.
Signal cycle failure (or overflow) is an interrupted traffic condition in which a number of queued vehicles are unable to depart due to insufficient capacity during a signal cycle. Cycle failure detection is essential for identifying signal control problems at intersections. However, typical traffic sensors do not have the capability of capturing cycle failures. In this article, we introduce an algorithm for traffic signal cycle failure detection using video image processing. A cycle failure for a particular movement occurs when at least one vehicle must wait through more than one red light to complete the intended movement. The proposed cycle failure algorithm was implemented using Microsoft Visual C#. The system was tested with field data at different locations and time periods. The test results show that the algorithm works favorably: the system captured all the cycle failures and generated only three false alarms, which is approximately 0.9% of the total cycles tested.
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