Common use of RESEARCH BACKGROUND Clause in Contracts

RESEARCH BACKGROUND. Commercial trucks are an important component of our regional economic activity. As a consequence, freeway usage and performance patterns that affect trucking activities have potentially serious impacts on commercial, industrial, and transport-related business throughout the Puget Sound region. Furthermore, since heavy weights and large turning radii make the characteristics of truck movements quite different from those of passenger cars, the monitoring of freight movements is imperative for successful traffic management, planning, and policy analysis programs. In September 1999, the Washington State Department of Transportation (WSDOT) initiated a research project entitled “Monitoring Freight on Puget Sound Freeways.” Its objectives were to enhance the FLOW system evaluation methodology and supplement the tool set that is now used to analyze vehicle usage and performance on the central Puget Sound freeway network. The methodology and tool set enhancements would enable analysts to produce estimates of the size and performance of freight (truck) movements on Puget Sound freeways and help monitor trends in trucking activities over time. By using vehicle length categories as a surrogate for various categories of trucks, the nature of trucking activities in the region could be estimated. To produce volume data sorted by vehicle length categories, the dual-loop data collected by the WSDOT FLOW system were selected as the main data source for the project. Unfortunately, preliminary tests performed on the dual-loop data indicated that these data were not reliable. Consequently, a part of the project was temporarily suspended until the accuracy of the dual-loop data could be improved or a better data source found. Because dual-loop detectors, if sufficiently accurate, can be extremely cost- effective collectors of real-time vehicle classification and speed data, further research on the existing problem and potential remedies was sought. The current project addressed this concern by performing further analyses of dual-loop data inaccuracies, investigating the types and potential causes of these inaccuracies, and proposing necessary steps to improve data quality.

RESEARCH BACKGROUND. Commercial trucks are an important component of our regional economic activity. As a consequence, freeway usage and performance patterns that affect trucking activities have potentially serious impacts on commercial, industrial, and transport-related business throughout the Puget Sound region. Furthermore, since heavy weights and large turning radii make the characteristics of truck movements quite different from those of passenger cars, the monitoring of freight movements is imperative for successful traffic management, planning, and policy analysis programs. In September 1999, the Washington State Department of Transportation (WSDOT) initiated a research project entitled “Monitoring Freight on Puget Sound Freeways.” Its objectives were to enhance the FLOW system evaluation methodology and supplement the tool set that is now used to analyze vehicle usage and performance on the central Puget Sound freeway network. The methodology and tool set enhancements would enable analysts to produce estimates of the size and performance of freight (truck) movements on Puget Sound freeways and help monitor trends in trucking activities over time. By using vehicle length categories as a surrogate for various categories of trucks, the nature of trucking activities in the region could be estimated. To produce volume data sorted by vehicle length categories, the dual-dual- loop data collected by the WSDOT FLOW system were selected as the main data source for the project. Unfortunately, preliminary tests performed on the dual-dual- loop data indicated that these data were not reliable. Consequently, a part of the project was temporarily suspended until the accuracy of the dual-dual- loop data could be improved or a better data source found. Because dual-dual- loop detectors, if sufficiently accurate, can be extremely cost- effective collectors of real-time vehicle classification and speed data, further research on the existing problem and potential remedies was sought. The current project addressed this concern by performing further analyses of dual-dual- loop data inaccuracies, investigating the types and potential causes of these inaccuracies, and proposing necessary steps to improve data quality.