Fuzzy Rule-Based Travel Time Estimation Modelling: A Case Study of Surat City Traffic Corridor

2020 ◽  
pp. 183-198
Author(s):  
Krishna Saw ◽  
Bhimaji K. Katti ◽  
Gaurang J. Joshi
Keyword(s):  
Travel Time ◽  
Fuzzy Rule ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Rule Based ◽  
Traffic Corridor

Reconstructing Vehicle Trajectories to Support Travel Time Estimation

2018 ◽  
Vol 2672 (42) ◽  
pp. 148-158 ◽  
Author(s):  
Zheng Li ◽  
Robert Kluger ◽  
Xianbiao Hu ◽  
Yao-Jan Wu ◽  
Xiaoyu Zhu
Keyword(s):  
Sample Size ◽  
Travel Time ◽  
Input Data ◽  
Time Estimation ◽  
Smartphone Application ◽  
Primary Objective ◽  
Travel Time Estimation ◽  
K Nearest Neighbors ◽  
Probe Vehicle

The primary objective of this study was to increase the sample size of public probe vehicle-based arterial travel time estimation. The complete methodology of increasing sample size using incomplete trajectory was built based on a k-Nearest Neighbors ( k-NN) regression algorithm. The virtual travel time of an incomplete trajectory was represented by similar complete trajectories. As incomplete trajectories were not used to calculate travel time in previous studies, the sample size of travel time estimation can be increased without collecting extra data. A case study was conducted on a major arterial in the city of Tucson, Arizona, including 13 links. In the case study, probe vehicle data were collected from a smartphone application used for navigation and guidance. The case study showed that the method could significantly increase link travel time samples, but there were still limitations. In addition, sensitivity analysis was conducted using leave-one-out cross-validation to verify the performance of the k-NN model under different parameters and input data. The data analysis showed that the algorithm performed differently under different parameters and input data. Our study suggested optimal parameters should be selected using a historical dataset before real-world application.

scholarly journals Accuracy of Travel Time Estimation Using Bluetooth Technology: Case Study Limfjord Tunnel Aalborg

2014 ◽  
Vol 13 (3) ◽  
pp. 166-191 ◽  
Author(s):  
Bahar Namaki Araghi ◽  
Kristian Skoven Pedersen ◽  
Lars Tørholm Christensen ◽  
Rajesh Krishnan ◽  
Harry Lahrmann
Keyword(s):  
Travel Time ◽  
Time Estimation ◽  
Travel Time Estimation

Short-term travel time estimation: A case study

2015 ◽  
Author(s):  
Emad A. Mohammed ◽  
Charan Aulakh ◽  
Diwakar Krishnamurthy ◽  
Christopher T. Naugler ◽  
Behrouz H. Far
Keyword(s):  
Travel Time ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Short Term
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