Modeling a Functional Form of Fundamental Diagram by Automated License Plate Readers Data: A Case Study in Tehran, Iran

Recently, the traffic control infrastructure and public transport fare records in Tehran have produced massive data. Such data can be analyzed to monitor the city's transportation condition and also to improve its transportation network. Understanding the fundamental features of traffic, including flow, density, and velocity, on important roadways is vital for a reliable traffic control mechanism. Obtaining this data from traffic cameras scattered across the city was the goal of this research. The average speed of cars, as recorded by automated license plate readers (ALPRs), was also obtained, and a relationship for estimating the flow density is proposed that simulates cars' behaviors. The curve plotted by the proposed relationship has about an 25% average speed deviancy from that determined by the probe vehicles for all cameras. This error seems acceptable, considering the limitations of ALPRs and/or diversity of roads.