Hans van Lint
Hans van Lint
Full Professor Traffic Simulation and Computing, Delft University of Technology
Geverifieerd e-mailadres voor tudelft.nl
TitelGeciteerd doorJaar
Accurate freeway travel time prediction with state-space neural networks under missing data
JWC Van Lint, SP Hoogendoorn, HJ van Zuylen
Transportation Research Part C: Emerging Technologies 13 (5-6), 347-369, 2005
3672005
Travel time unreliability on freeways: Why measures based on variance tell only half the story
JWC Van Lint, HJ Van Zuylen, H Tu
Transportation Research Part A: Policy and Practice 42 (1), 258-277, 2008
2602008
Improving a travel-time estimation algorithm by using dual loop detectors
JWC Van Lint, NJ Van der Zijpp
Transportation Research Record 1855 (1), 41-48, 2003
2072003
Freeway travel time prediction with state-space neural networks: modeling state-space dynamics with recurrent neural networks
JWC Van Lint, SP Hoogendoorn, HJ van Zuylen
Transportation Research Record 1811 (1), 30-39, 2002
1622002
Online learning solutions for freeway travel time prediction
JWC Van Lint
IEEE Transactions on Intelligent Transportation Systems 9 (1), 38-47, 2008
1612008
Reliable travel time prediction for freeways
JWC Van Lint
Netherlands TRAIL Research School, 2004
1592004
A robust and efficient method for fusing heterogeneous data from traffic sensors on freeways
JWC Van Lint, SP Hoogendoorn
Computer‐Aided Civil and Infrastructure Engineering 25 (8), 596-612, 2010
1532010
Monitoring and predicting freeway travel time reliability: Using width and skew of day-to-day travel time distribution
JWC Van Lint, HJ van Zuylen
Transportation Research Record 1917 (1), 54-62, 2005
1502005
Real-time Lagrangian traffic state estimator for freeways
Y Yuan, JWC Van Lint, RE Wilson, F van Wageningen-Kessels, ...
IEEE Transactions on Intelligent Transportation Systems 13 (1), 59-70, 2012
1492012
Routing strategies based on macroscopic fundamental diagram
VL Knoop, SP Hoogendoorn, JWC Van Lint
Transportation Research Record 2315 (1), 1-10, 2012
1302012
Predicting urban arterial travel time with state-space neural networks and Kalman filters
H Liu, H Van Zuylen, H Van Lint, M Salomons
Transportation Research Record 1968 (1), 99-108, 2006
1182006
Bayesian committee of neural networks to predict travel times with confidence intervals
CPIJ van Hinsbergen, JWC Van Lint, HJ Van Zuylen
Transportation Research Part C: Emerging Technologies 17 (5), 498-509, 2009
1152009
Fastlane: New multiclass first-order traffic flow model
JWC Van Lint, SP Hoogendoorn, M Schreuder
Transportation Research Record 2088 (1), 177-187, 2008
1142008
Prediction intervals to account for uncertainties in travel time prediction
A Khosravi, E Mazloumi, S Nahavandi, D Creighton, JWC Van Lint
IEEE Transactions on Intelligent Transportation Systems 12 (2), 537-547, 2011
1042011
Reliable real-time framework for short-term freeway travel time prediction
JW Van Lint
Journal of transportation engineering 132 (12), 921-932, 2006
952006
Traffic dynamics: Its impact on the macroscopic fundamental diagram
VL Knoop, H van Lint, SP Hoogendoorn
Physica A: Statistical Mechanics and its Applications 438, 236-250, 2015
922015
Short-term traffic and travel time prediction models
JWC Van Lint, C Van Hinsbergen
Artificial Intelligence Applications to Critical Transportation Issues 22 (1 …, 2012
822012
Genealogy of traffic flow models
F van Wageningen-Kessels, H Van Lint, K Vuik, S Hoogendoorn
EURO Journal on Transportation and Logistics 4 (4), 445-473, 2015
812015
A genetic algorithm-based method for improving quality of travel time prediction intervals
A Khosravi, E Mazloumi, S Nahavandi, D Creighton, JWC Van Lint
Transportation Research Part C: Emerging Technologies 19 (6), 1364-1376, 2011
812011
Bayesian combination of travel time prediction models
CPIJ van Hinsbergen, JWC Van Lint
Transportation Research Record 2064 (1), 73-80, 2008
712008
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Artikelen 1–20