In the traffic operations world, accurate performance measures are some of the most valuable commodities. Achieving this accuracy requires that network-based roadway sensors are allocated in locations beneficial to traffic operations. However, with the budgetary restrictions most transportation agencies face, these roadway sensors cannot be placed as thoroughly as required for top-notch accuracy, requiring these agencies to select a limited number of installments that produce the most optimal accuracy. On most occasions, this optimal allocation is difficult to find. Traffic bottlenecks are one of the leading causes of freeway delay, thus warranting that additional sensors be placed nearby where traffic conditions are most turbulent. By doing so, the accuracy of performance measures can be refined. This paper develops a model for optimally locating roadway sensors (loop detectors) for performance measuring purposes. This model maximizes total benefit by allocating loop detectors relative to a bottlenecks location and is constrained by monetary and spatial limits. Benefit is determined to be the variation of average speed between any two eligible detector-allocating locations over a given time period. Using the cell transmission model on a pipeline freeway, this paper demonstrates the models successful ability to place detectors near known bottlenecks. On a case-study network with bottlenecks in unknown locations, the model successfully allocates loop detectors to locations where bottlenecks are most likely occurring. This paper concludes that the presented program could be a very assistive tool to transportation agencies looking to place additional loop detectors for bottleneck detection purposes.
Samenvatting