With increasingly rapid advances in the field of producing modern and autonomous vehicles, the need for intelligent traffic management systems, which take advantage of the vehicle's abilities to sense and communicate, has increased. A considerable amount of literature has been published on managing traffic that includes only autonomous vehicles. However, changing all vehicles to autonomous versions is a long-term process. In the near future, traffic will be a mixture of human-driven and autonomous vehicles. To date, few studies have investigated mixed traffic in intelligent management systems. The main objective of this research is to study the possibility of using a vehicle-mounted camera to sense and collect the required traffic data of the surrounding vehicles in mixed traffic. To achieve this, a vehicle with a monocular camera is used to collect image information for detecting and counting the vehicles in different lanes and estimating their distance and speed on the defined route. The results indicate that our proposed image processing algorithms can acquire the information needed for intelligent traffic management systems.
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