TY - JOUR
T1 - Traffic state estimation using floating car data
AU - Sunderrajan, Abhinav
AU - Viswanathan, Vaisagh
AU - Cai, Wentong
AU - Knoll, Alois
N1 - Publisher Copyright:
© The Authors. Published by Elsevier B.V.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Agent-based simulations
KW - Simulation and modelling of transportation systems
KW - Traffic state estimation
UR - http://www.scopus.com/inward/record.url?scp=84978517753&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2016.05.521
DO - 10.1016/j.procs.2016.05.521
M3 - Conference article
AN - SCOPUS:84978517753
SN - 1877-0509
VL - 80
SP - 2008
EP - 2018
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - International Conference on Computational Science, ICCS 2016
Y2 - 6 June 2016 through 8 June 2016
ER -