Kalman filter Based Vehicle Running Data Estimation

Author(s):  
Haifeng Song ◽  
Minjie Zhang ◽  
Kai Feng ◽  
Jianfeng Cheng ◽  
Datian Zhou
2018 ◽  
Vol 1 (1) ◽  
pp. 27-30
Author(s):  
Himal Acharya

This paper estimates the travel time for pedestrian in Kist Medical Hospital- Balkumari route using cell phones’ GPS as probes. Using Google Map’s individual timeline, GPS data was traced for this route. Then, Kalman Filter Algorithm is used to estimate the travel time for pedestrian for that week day. Using algorithm result, statistical tool is used to measure the accuracy of travel time in particular origin-destination pair. Kalman filter algorithm is better approach for travel time estimation since the parameters get updated quickly if there is traffic fluctuation. Based on mean travel time, Kalman filter has better travel time estimation of 16.6 min with the help of historical data in compared to Google Map estimation of 18 min irrespective time of day in above origin-destination pair. Real observation is close to estimated travel time which signifies estimated travel time. Here author manages to compare the mean travel time between Kalman filter estimation and Google map data estimation.


ICCKE 2013 ◽  
2013 ◽  
Author(s):  
Mohammad Hassan Majidi ◽  
Mithridad Pourmir ◽  
Seyed Mohammad Sajad Sadough

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