Commercial floating car data (FCD) is being increasingly used as a traffic data source due to its lower cost despite concerns about its reliability. This paper focuses on the evaluation of FCD speed quality as a surrogate measure for arterial speed from different aspects. First, FCD speed is compared to video-based traffic data, collected from a specific urban road segment and assumed as ground truth in (a) descriptive evaluations, (b) speed estimation, and (c) level of service estimation. Regression analysis carried out to derive transformation function between two datasets showed a nonlinear relation with a high correlation coefficient of 0.82. Working with data along an urban corridor of 3.6 km also showed that despite some outliers, FCD was capable of detecting peak-hour queue formations as well as incident related ones. Use of transformation function on FCD speeds helped to increase its potential in urban traffic monitoring.

This study investigates the effects of variable queue lengths and green times on discharge flow rates at real-time managed intersections in Mersin, Turkey. For this purpose, traffic flow data were collected at two different signalized intersections during morning peak hours for two days. The traffic data including the time headways, queue lengths for each cycle were derived from video records via MATLAB coding while the signal timing data were obtained from Mersin Metropolitan Municipality. The impact of variable queue lengths and green times on discharge flow rate were evaluated separately via analysis of variance (ANOVA) tests. The results indicated that time headways of the first vehicles in the queue were statistically larger than the time headways of the remaining vehicles in the queue (p-value0.05). Furthermore, the effect of the variable green time on discharge flow rate revealed that the significant difference was only observed for the first twelve seconds of the green time.

As urban traffic challenges intensify, the growing interest for fully actuated control systems in intersection management is on the rise due to their capacity to adapt to dynamic traffic demands. These systems play a crucial role in sustainable traffic solutions, significantly reducing delays and emissions and enhancing overall system efficiency. The optimal performance of these systems relies on effectively facilitating vehicle discharge at the saturation flow rate throughout the green period. This study introduces a new parameter, lane inefficiency, evaluating vehicle discharge effectiveness by comparing saturation flow rate with instantaneous discharge for each green period. It provides a comprehensive assessment of green utilization for specific lanes. This study also explores the impact of signal control system parameters and traffic flow characteristics on lane inefficiency using principal component analysis (PCA) and multiple linear regression models. This approach holistically evaluates how both signal control system and traffic flow parameters collectively influence efficient green period utilization. The findings emphasize the impact of critical factors on lane inefficiency, including green time, the proportion of total unused green time to green time, total unused green time, the percentage of heavy vehicles in departing traffic, the ratio of effective green time to cycle time, the total time headways of the first four vehicles, and queue length. Decision makers need to pay due attention to these parameters to enhance intersection performance and foster a more sustainable urban transportation network.