DocumentCode :
550580
Title :
Mining travel time from smart card fare data
Author :
Gao Lianxiong ; Liang Hong
Author_Institution :
Sch. of Electr. & Inf. Eng., Yunnan Nat. Univ., Kunming, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
5542
Lastpage :
5547
Abstract :
The wide applications of smart card payment techniques in public transit systems provide a new way of collecting travel time information. In this paper, one method is proposed to estimate travel times with smart card fare payment data and bus schedule data. The proposed method first classifies two sequential card swipes to infer if they occur at the same stop with Naive Bayesian Classifier (NBC). Travel time is estimated from the NBC results using Maximum Likelihood Estimation (MLE), Dynamic Programming (DP) and Quadratic Programming (QP) methods. In order to solve the problem with imprecise initial parameters, coordinate descent method is applied, which updates parameters and estimate values alternatively until it converges. An experiment with real-world data is designed to quantify the reliability of this algorithm and the outcomes is contrast with GPS data. It shows that the error of this method is small and the convergence is fast.
Keywords :
Bayes methods; data mining; dynamic programming; maximum likelihood estimation; quadratic programming; smart cards; traffic engineering computing; DP; MLE; NBC; Naive Bayesian classifier; QP; dynamic programming; maximum likelihood estimation; mining travel time; public transit systems; quadratic programming; smart card fare data; smart card payment techniques; travel time information; Dynamic programming; Gaussian distribution; Global Positioning System; Maximum likelihood estimation; Roads; Smart cards; Dynamic Programming (DP); Naive Bayesian Classifier (NBC); Public Transport System; Quadratic Programming (QP); Smart Card Fare System; Travel Time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6000919
Link To Document :
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