Congestion has long been a concern to transportation operation and planning. Various methods and technologies have been developed and applied in detecting congestion. This study focuses on using bus as probes to indicate recurrent congestion on urban roadway networks.
In this study, bus speeds are used to reflect indications of congestion. Bus speed data collected over “homogeneous days” are pooled in order to find indications of recurrent congestion. Bus speeds collected during a time period at each location are compared to bus speeds collected during other time periods (or during the whole day) at the same location. For practical purposes, the entire bus route investigated for the purpose of method development, validation, and demonstration is discretized into 10 meter spatial sections, and time of day is discretized into 30 minute time intervals. Each 10 meter long spatial section and 30 minute duration time interval constitutes a space-time cell for which existence or absence of an indication of congestion is determined.
Three different methods are used to determine the existence or absence of an indication of congestion for each space-time cell. Two of the three methods, the Mean Based method and the Median Based method, apply traditional statistical tests. The other method, the Low Speed Threshold (LST) method, is developed in this study.
An empirical study based on Automatic Vehicle Location (AVL) data collected using The Ohio State University (OSU) Campus Transit Lab (CTL) is conducted to evaluate the three methods. The indications of congestion produced by the three methods are then compared to a priori expectation of recurrent congestions along the route.
The Mean Based method produces few indications of recurrent congestion. It misses space-time cells where recurrent congestion is expected. The Median Based method and the LST method produce similar general patterns in terms of where and when recurrent congestions are indicated. However, there exist some differences between the Median Based method and the LST method in terms of the specific locations where and specific times when recurrent congestions are indicated.
A systematic analysis and comparison based on the Median Based method and the LST method is conducted. Based on the empirical analyses and a priori expectation of recurrent congestions along the route, the LST method seems more appealing than the Median Based method (and the Mean Based method) for determining indications of recurrent congestion. Although the empirical results produced by the LST method are encouraging, more research is necessary before concluding that the LST method could be used to detect recurrent congestion on a widespread basis. A sensitivity analysis of the parameters used in this study is suggested for future research. Other traffic related elements such as speed limits, bus trip running times, and schedule adherence might also be utilized to improve the recurrent congestion detection methods.