Grouped travel time estimation in signalized arterials using point-to-point detectors

•To investigate the group and multistate properties of arterial travel times with the data from point-to-point detectors.•To propose an adaptive clustering method for estimation of travel times in signalized arterials.•To show how to effectively recognize between normal and anomalous travel times. Travel time, an essential parameter in Advanced Traffic Management Systems and Advanced Traveller Information Systems, has been studied for decades of years, especially on freeways. However, the traffic flows in signalized arterials are more complex and stochastic, which enables arterial travel times to be multistate due to the interruptions from signal controls. Therefore, the signal effects need to be considered in the estimation of arterial travel times. In this paper, a grouped travel time estimation method is proposed to consider the signal interruptions and estimate the arterial travel times on a more micro level. With the data obtained from point-to-point detectors, the method analyzes vehicles’ traffic states before signals and recognizes those vehicles sharing the same states in both upstream and downstream signals as vehicle groups. Then the estimation problem is formulated as a clustering process to recognize the vehicle groups, and the grouped travel times are represented by the centers of vehicle groups. The field tests under ten different scenarios show that the grouped travel times can capture the multistate properties of the travel times in signalized arterials and represent the observed travel times of most vehicles within minor deviations.