Qijian Gan
Qijian Gan
R&D Engineer at PATH (UC Berkeley)
Bestätigte E-Mail-Adresse bei berkeley.edu - Startseite
Zitiert von
Zitiert von
A kinematic wave theory of capacity drop
WL Jin, QJ Gan, JP Lebacque
Transportation Research Part B: Methodological 81, 316-329, 2015
A kinematic wave approach to traffic statics and dynamics in a double-ring network
WL Jin, QJ Gan, VV Gayah
Transportation Research Part B: Methodological 57, 114-131, 2013
SPIVC: A Smartphone-based inter-vehicle communication system
WL Jin, C Kwan, Z Sun, H Yang, Q Gan
Proceedings of transportation research board annual meeting, 2012
Automatic identification of near-stationary traffic states based on the PELT changepoint detection
Q Yan, Z Sun, Q Gan, WL Jin
Transportation Research Part B: Methodological 108, 39-54, 2018
Calibration of a family of car-following models with retarded linear regression methods
H Yang, Q Gan, WL Jin
Transportation Research Board 90th Annual MeetingTransportation Research Board, 2011
PDE traffic observer validated on freeway data
H Yu, Q Gan, A Bayen, M Krstic
IEEE Transactions on Control Systems Technology 29 (3), 1048-1060, 2020
Analysis of traffic statics and dynamics in signalized networks: a poincaré map approach
QJ Gan, WL Jin, VV Gayah
Transportation science 51 (3), 1009-1029, 2017
Estimation of performance metrics at signalized intersections using loop detector data and probe travel times
Q Gan, G Gomes, A Bayen
IEEE Transactions on Intelligent Transportation Systems 18 (11), 2939-2949, 2017
Validation of a macroscopic lane-changing model
QJ Gan, WL Jin
Transportation research record 2391 (1), 113-123, 2013
Left-lane changes in laterally unbalanced traffic: Estimating number of lane changes with data from lane-based loop detectors
QJ Gan, WL Jin
Transportation Research Record 2490 (1), 106-115, 2015
A methodology for evaluating the performance of model-based traffic prediction systems
G Gomes, Q Gan, A Bayen
Transportation research part C: emerging technologies 96, 160-169, 2018
Field tests of a dynamic green driving strategy based on inter-vehicle communication
H Yang, L Andres, Z Sun, Q Gan, WL Jin
Transportation Research Part D: Transport and Environment 59, 289-300, 2018
Macroscopic modeling and analysis of urban vehicular traffic
QJ Gan
University of California, Irvine, 2014
Incorporating vehicular emissions into an efficient mesoscopic traffic model: An application to the alameda corrido
JDS Q Gan, J Sun, W Jin
University of California Transportation Center, 2011
Arterial Traffic Flow Prediction: A Deep Learning Approach with Embedded Signal Phasing Information
V Chan, Q Gan, A Bayen
Master’s thesis, EECS Department, University of California, Berkeley, 2020
A Graph Convolutional Network with Signal Phasing Information for Arterial Traffic Prediction
V Chan, Q Gan, A Bayen
arXiv preprint arXiv:2012.13479, 2020
Adaptive Coordination Offsets for Signalized Arterial Intersections using Deep Reinforcement Learning
KA Diaz, D Dailisan, U Sharaf, C Santos, Q Gan, FA Uy, MT Lim, ...
arXiv preprint arXiv:2008.02691, 2020
Arterial Traffic Estimation Using Field Detector and Signal Phasing Data
Q Gan, A Skabardonis
Estimation of Arterial Traffic Flow Fundamental Diagrams Using Data from Advance Loop Detectors
Q Gan, S Petryk
Transportation Research Board 98th Annual MeetingTransportation Research Board, 2019
CTM-based optimal signal control strategies in urban networks
WL Jin, Q Gan
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