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Open Access Publications from the University of California

Estimation of Truck Traffic Volume from Single Loop Detectors Using Lane-to-Lane Speed Correlation


An algorithm for real time estimation of truck traffic in multi-lane freeway is proposed. The algorithm uses data from single loop detectors-the most widely installed surveillance technology for urban freeways in the US. The algorithm works for those freeway locations that have a truck-free lane, and exhibit high lane-to-lane speed correlation. These conditions are met by most urban freeway locations. The algorithm produces real time estimates of the truck traffic volumes at the location. It can also be used to produce alternative estimate of the mean effective vehicle length, which can improve speed estimates from single loop detector data. The algorithm is tested with real freeway data and produces estimates of truck traffic volumes with only 5.7% error. It also captures the daily patterns of truck traffic and mean effective vehicle length. Applied to loop data on I-710 near Long Beach during the dockworkers lockout October 1-9, 2002, the algorithm finds a 32 % reduction in 5-axle truck volume.

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