TY - JOUR
T1 - Calibration of nonlinear car-following laws for traffic oscillation prediction
AU - Rhoades, Christine
AU - Wang, Xin
AU - Ouyang, Yanfeng
N1 - The authors would like to thank Profs. Michael H. Zhang (UC Davis) and Serge Hoogendoorn (TU Delft), and other participants at the Symposium Celebrating 50 Years of Traffic Flow Theory (Portland, August 2014) for providing very helpful comments during a symposium presentation. This research was supported in part by the U.S. National Science Foundation via Grant CMMI-0748067.
PY - 2015
Y1 - 2015
N2 - Frequency-domain analysis has been successfully used to (i) predict the amplification of traffic oscillations along a platoon of vehicles with nonlinear car-following laws and (ii) measure traffic oscillation properties (e.g., periodicity, magnitude) from field data. This paper proposes a new method to calibrate nonlinear car-following laws based on real-world vehicle trajectories, such that oscillation prediction (based on the calibrated car-following laws) and measurement from the same data can be compared and validated. This calibration method, for the first time, takes into account not only the driver's car-following behavior but also the vehicle trajectory's time-domain (e.g., location, speed) and frequency-domain properties (e.g., peak oscillation amplitude). We use Newell's car-following model (1961) as an example and calibrate its parameters based on a penalty-based maximum likelihood estimation procedure. A series of experiments using Next Generation Simulation (NGSIM) data are conducted to illustrate the applicability and performance of the proposed approach. Results show that the calibrated car-following models are able to simultaneously reproduce observed driver behavior, time-domain trajectories, and oscillation propagation along the platoon with reasonable accuracy.
AB - Frequency-domain analysis has been successfully used to (i) predict the amplification of traffic oscillations along a platoon of vehicles with nonlinear car-following laws and (ii) measure traffic oscillation properties (e.g., periodicity, magnitude) from field data. This paper proposes a new method to calibrate nonlinear car-following laws based on real-world vehicle trajectories, such that oscillation prediction (based on the calibrated car-following laws) and measurement from the same data can be compared and validated. This calibration method, for the first time, takes into account not only the driver's car-following behavior but also the vehicle trajectory's time-domain (e.g., location, speed) and frequency-domain properties (e.g., peak oscillation amplitude). We use Newell's car-following model (1961) as an example and calibrate its parameters based on a penalty-based maximum likelihood estimation procedure. A series of experiments using Next Generation Simulation (NGSIM) data are conducted to illustrate the applicability and performance of the proposed approach. Results show that the calibrated car-following models are able to simultaneously reproduce observed driver behavior, time-domain trajectories, and oscillation propagation along the platoon with reasonable accuracy.
KW - Car-following Law
KW - Field Validation
KW - Traffic Oscillation
UR - http://www.scopus.com/inward/record.url?scp=84983178105&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983178105&partnerID=8YFLogxK
U2 - 10.1016/j.trpro.2015.07.002
DO - 10.1016/j.trpro.2015.07.002
M3 - Article
AN - SCOPUS:84983178105
SN - 2352-1457
VL - 9
SP - 21
EP - 35
JO - Transportation Research Procedia
JF - Transportation Research Procedia
ER -