Quality of Automatic Traffic Volume Counting by Cameras and Impact on the Qualitative Indicators of Traffic

This paper presents research on the collection, analysis, and evaluation of fundamental data needed for road traffic systems. The basis research, planning projections systems are counts collection related to volume type. quality accuracy this very important or optimization. Therefore, purpose is apply advanced methods automatic counting motorized evaluate impact measurement indicators. measurements arising from traditional method through manual will be compared with most cameras. For purpose, an analytical algorithm recognition processing users as a function time day was applied. program written in programming language Python, its effect results qualitative indicators were analyzed using Synchro software model. developed capable recognizing classifying different types vehicles traffic, such motorbikes, motorcycles, cars, pick-ups, trucks, vans buses, well over time. obtained these two models show advantages applying dynamic processes, terms A comparison intervals varying levels visibility presented tables graphs. At nighttime, when poor, discrepancy between around 9.5%. However, good, difference automated 4.87% period 19:00–19:15 3.64% 05:00–05:15. especially noticeable distinguishing vehicle categories, due limitations measuring dimensions vehicles. calculation has minor as: approach LOS, progression factor, v/s, v/c, clearance time, lane group flow, adj. satd, flow delay.