Bayesian Inference on Network Traffic Using Link Count Data: Rejoinder

1998 ◽  
Vol 93 (442) ◽  
pp. 576 ◽  
Author(s):  
Claudia Tebaldi ◽  
Mike West
Keyword(s):  
Bayesian Inference ◽  
Network Traffic ◽  
Count Data ◽  
Link Count

scholarly journals Origin–Destination Flow Estimation from Link Count Data Only

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5226
Author(s):  
Subhrasankha Dey ◽  
Stephan Winter ◽  
Martin Tomko
Keyword(s):  
Real World ◽  
Count Data ◽  
Road Traffic ◽  
Physical Space ◽  
Simulated Data ◽  
Accuracy Score ◽  
Travel Times ◽  
Estimation Model ◽  
Flow Estimation ◽  
Link Count

All established models in transportation engineering that estimate the numbers of trips between origins and destinations from vehicle counts use some form of a priori knowledge of the traffic. This paper, in contrast, presents a new origin–destination flow estimation model that uses only vehicle counts observed by traffic count sensors; it requires neither historical origin–destination trip data for the estimation nor any assumed distribution of flow. This approach utilises a method of statistical origin–destination flow estimation in computer networks, and transfers the principles to the domain of road traffic by applying transport-geographic constraints in order to keep traffic embedded in physical space. Being purely stochastic, our model overcomes the conceptual weaknesses of the existing models, and additionally estimates travel times of individual vehicles. The model has been implemented in a real-world road network in the city of Melbourne, Australia. The model was validated with simulated data and real-world observations from two different data sources. The validation results show that all the origin–destination flows were estimated with a good accuracy score using link count data only. Additionally, the estimated travel times by the model were close approximations to the observed travel times in the real world.

scholarly journals Bayesian Inference from Count Data Using Discrete Uniform Priors

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e74388 ◽  
Author(s):  
Federico Comoglio ◽  
Letizia Fracchia ◽  
Maurizio Rinaldi
Keyword(s):  
Bayesian Inference ◽  
Count Data ◽  
Discrete Uniform

OD Count Estimation Based on Link Count Data

2008 ◽  
pp. 217-226 ◽  
Author(s):  
Yi Jin ◽  
Dongchen Jiang ◽  
Shuai Yuan ◽  
Jianting Cao ◽  
Lili Wang ◽  
...  
Keyword(s):  
Count Data ◽  
Link Count ◽  
Count Estimation

scholarly journals Bayesian inference on quasi-sparse count data

Biometrika ◽  
2016 ◽  
Vol 103 (4) ◽  
pp. 971-983 ◽  
Author(s):  
Jyotishka Datta ◽  
David B. Dunson
Keyword(s):  
Bayesian Inference ◽  
Count Data
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