Traffic state estimation using floating car data

• Main Authors: Sunderrajan, Abhinav, Viswanathan, Vaisagh, Cai, Wentong, Knoll, Alois
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Computer science and engineering; Traffic State Estimation; Simulation And Modelling Of Transportation Systems
• Online Access: https://hdl.handle.net/10356/89720; http://hdl.handle.net/10220/47120
• Institution: Nanyang Technological University

There is an increasing availability of floating car data both historic, in the form of trajectory datasets and real-time, in the form of continuous data streams. This paves the way for several advanced traffic management services such as current traffic state estimation, congestion and incident detection and prediction of the short-term evolution of traffic flow. In this paper, we present an analysis of using probe vehicles for reconstructing traffic state. We employ detailed agent-based microscopic simulations of a real world expressway to estimate the state from floating car data. The probe penetration required for accurate traffic state estimation is also determined.