1. Abstract High-resolution vehicle speed profiles obtained from sophisticated devices such as global positioning system (GPS) receivers provide an opportunity to accurately measure intersection delay, composed of deceleration delay, stopped delay, and acceleration delay. Although the delay components can be measured by manually examining the speed profiles or derived time-space diagrams, identifying when vehicles begin to decelerate or stop accelerating is not always a straightforward task. In addition, a manual identification process may be laborious and time- consuming when handling a large network or numerous runs. More importantly, the results from a manual process may not be consistent between analysts or even for a single analyst over time. This paper proposes a new approach to identifying control delay components based on second-by-second vehicle speed profiles obtained from GPS devices. The proposed approach utilizes both de-noised speed and acceleration profiles for capturing critical points associated with each delay component. Speed profiles are used for the identification of stopped time periods, and acceleration profiles are used for detecting deceleration onset points and acceleration ending points. The authors applied this methodology to sampled runs collected from GPS-equipped instrumented vehicles and concluded that it satisfactorily computed delay components under normal traffic conditions. Introduction Measurement of control delay is important for evaluating the performance of signalized intersections. Control delay, in particular the delay components including deceleration delay, stopped delay, and acceleration delay, are not always easy to measure in the field. Global positioning system (GPS) technology provides an opportunity to track vehicle movements even on a second-by-second basis. The utilization of GPS speed data enables researchers to measure the control delay components efficiently and effectively. In this research, a new approach to measuring control delay components is suggested and applied to real-world GPS data. Control Delay Components Typical Vehicle Speed and Acceleration Profiles near Intersections Examination of both acceleration and speed profiles near intersections reveals critical points associated with delay components. Speed Profile with Stopped Delay Speed Profile without Stopped Delay

2. Approach to Identifying Critical Points 1. Smoothing speed profile 2. Generating acceleration profile 3. Identifying critical points related to stopped delay using speed profiles 4. Identifying critical points related to acceleration and deceleration delay using acceleration profiles 5. Compute delay by each component Selected Smoothing Method Local polynomial regression technique: quadratic polynomial and 2-second bandwidth for gaussian kernel Application & Results Data: Real-world GPS data obtained from Commute Atlanta Project (Sampled 14 trips) Sampled 14 Vehicle Trip Trajectories for the Test Site Critical points The suggested approach appropriately detects the critical points. Thus, the approach efficiently computes delay components. Effects of Bandwidth Size Speed profile smoothing is a critical element for the suggested approach as the degree of smoothing directly affects the results of computed delays. Thus, the size of bandwidth, which determines the degree of smoothing, should be appropriately selected. The sensitivity analysis was performed, indicating that a 2-second bandwidth may be adequate. Limitation to the Suggested Methodology The suggested method may not truly detect the locations of critical points under congestion conditions or for closely-spaced intersections. Sensitivity of Delay Computation Results to the Size of Bandwidth Conclusions The suggested methodology, applied to GPS second- by-second speed profiles, efficiently detects critical points of each delay components. However, fine-tuning is required for the method to be applicable to congested conditions and closely- spaced intersections. Falsely detect the onset point of delay