A Seasonal Modelling Approach Capturing Spatio-Temporal Correlations for Dynamic Bus Travel Time Prediction *

2019 ◽  
Author(s):  
B. Anil Kumar ◽  
Avinash Achar ◽  
Dhivya Bharathi ◽  
Lelitha Vanjakshi
Keyword(s):  
Travel Time ◽  
Travel Time Prediction ◽  
Time Prediction ◽  
Temporal Correlations ◽  
Spatio Temporal ◽  
Bus Travel Time ◽  
Modelling Approach

Bus travel time prediction: a log-normal auto-regressive (AR) modelling approach

2020 ◽  
Vol 16 (3) ◽  
pp. 807-839 ◽  
Author(s):  
B. Dhivya Bharathi ◽  
B. Anil Kumar ◽  
Avinash Achar ◽  
Lelitha Vanajakshi
Keyword(s):  
Travel Time ◽  
Travel Time Prediction ◽  
Time Prediction ◽  
Auto Regressive ◽  
Log Normal ◽  
Bus Travel Time ◽  
Modelling Approach

scholarly journals Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Cong Bai ◽  
Zhong-Ren Peng ◽  
Qing-Chang Lu ◽  
Jian Sun
Keyword(s):  
Travel Time ◽  
Dynamic Model ◽  
Kalman Filtering ◽  
Prediction Models ◽  
Support Vector ◽  
Travel Times ◽  
Travel Time Prediction ◽  
Real World Data ◽  
Time Prediction ◽  
Bus Travel Time

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Real time bus travel time prediction using k-NN classifier

2017 ◽  
Vol 11 (7) ◽  
pp. 362-372 ◽  
Author(s):  
B. Anil Kumar ◽  
R. Jairam ◽  
Shriniwas S. Arkatkar ◽  
Lelitha Vanajakshi
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Travel Time Prediction ◽  
Time Prediction ◽  
Bus Travel Time

scholarly journals Multi-output bus travel time prediction with convolutional LSTM neural network

2019 ◽  
Vol 120 ◽  
pp. 426-435 ◽  
Author(s):  
Niklas Christoffer Petersen ◽  
Filipe Rodrigues ◽  
Francisco Camara Pereira
Keyword(s):  
Neural Network ◽  
Travel Time ◽  
Travel Time Prediction ◽  
Time Prediction ◽  
Bus Travel Time ◽  
Convolutional Lstm
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