Vehicle detection and tracking by computer vision for intelligent transportation applications.
Date of Award
Master of Science (MS)
Dr. Qiuming Zhu
The vehicle routing problem (VRP) deals with the allocation of vehicles to the customers that have requested products from a main depot. When the postal service, the bus system, or trucking industry plan for their everyday tasks of delivery goods or providing basic transportation needs to people, they are attempting to solve the VRP. However, this can be a daunting task because the VRP is computationally intensive. In this paper, we will address two areas of the VRP that have been relatively unexplored by previous research, yet play an important part in real-world_ applications of the VRP as well as define and create an evolutionary approach based on these ideas. The first area that we will address deals with the lack of real-world data sets when calculating the times between customers. This new implementation will allow the algorithm to calculate the actual time between customers at a given time of day, thus providing a final solution that is closer to a true optimal set of routes. The second addition to the VRP model will be contributed in the area of precedence relationships. These relationships often exist in real-world applications and are necessary in order ��o help the algorithm establish routes that are desired by the customers. The evolutionary approach provides global optimization insight to the problem.
Shi, Peijun, "Vehicle detection and tracking by computer vision for intelligent transportation applications." (2003). Student Work. 3565.
A Thesis Presented to the Department of Computer Science and the Faculty of the Graduate College University of Nebraska In Partial Fulfillment of the Requirements for the Degree Master of Science University of Nebraska at Omaha. Copyright 2003 Peijun Shi