ITS Support for Pedestrians and Bicyclists Count: Developing a Statewide Multimodal Count Program

It is critical to understand the travel behavior of pedestrians and cyclists on Louisiana’s roadways.  Not only do pedestrian and cyclist counts assist in research for safety, but these statistics are also essential for planners and policymakers when evaluating the usage of roadways and dictating infrastructure spending. Better understanding of overall statewide and location-specific transportation trends ultimately affects long-term planning and investment.  Counting of pedestrians and cyclists using video surveillance and image processing technology has promised to be effective and feasible.  While the research on newer technologies is not as robust as that of traditional ones, there is enough evidence to justify and guide the use of automated video count technology.  This study concentrates on a specific algorithm, which would aid in automatic counting.  This goal is achieved by following a part-based method, which utilizes the Histogram of Oriented Gradient (HOG) technique as well as a latent support vector machine (SVM).  This technique was the preferred algorithm for automation due to its high-speed processing capability and its open source availability.  The accuracy of the HOG algorithm in this study is validated using manual counts of pedestrians and cyclists from the collected video data. The full report is available online at https://www.ltrc.lsu.edu/pdf/2019/FR_598.pdf