Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation

Abstract

In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing.