Traffic Demand Accuracy Study Based on Public Data

Microscopic traffic simulation has a wide range of applications due to its high precision. However, the accuracy of such simulation is influenced by many factors during the simulation establishment process. This paper explores the impact of various factors on simulation results by comparing real-world traffic data, simulated data and simulations configured with different factors. The impact of these factors on simulation accuracy is evaluated by analyzing the traffic volume passing through a congested intersection in each direction. The results indicate that map correction, route iteration, and the inclusion of bus routes significantly affect simulation accuracy. An inaccurate map reduces traffic by 42%, while not-iterated routes prevent 6.6% of vehicles from using their original routes. Omitting bus routes increases the number of trips for private cars by 47%. Conversely, the inclusion of school zones has minimal impact, omitting them only reduces trips by 0.37%. Interestingly, integrating real traffic light data did not enhance simulation accuracy, likely due to discrepancies in junction turning percentages between the simulation and reality. This paper provides guidance for building accurate simulation maps using public data, enabling the creation of relatively precise models with minimal data and effort.