Using GPS-based AVL data to calculate and predict traffic network performance metrics: A systematic review

Automatic Vehicle Location (AVL) is becoming an important tool in Intelligent Transportation Systems (ITS) in the past few years, as it is an effective way of collecting and transmitting data regarding the vehicle's trip for real-time or future use. A methodology for analyzing the state of the art regarding the application of these systems is proposed in a form of a systematic literature review, by identifying and systematizing possible transportation network performance metrics that can be calculated or predicted using GPS-based AVL systems and inferring tendencies observed throughout the literature regarding techniques used and sensor data source and usage. As a result of this research, several performance metrics were identified, with Travel Time and Average Speed being the most recurrent ones. The conclusions reveal an increase in the number of publications and research projects regarding this topic over the years, as well as a promising potential of this type of technology, with buses and taxis being the most used probe vehicles.