Urban Expressway Travel Time Prediction Method Based on Fuzzy Adaptive Kalman Filter

Urban Expressway Travel Time Prediction Method Based on Fuzzy Adaptive Kalman Filter

According to the poor adaptive ability of traditional filter algorithm in the estimation for traffic state and travel time with Kalman filter, an improved fuzzy adaptive Kalman filtering method was proposed. The new interest of observation noise was defined, and the fuzzy logic was used to adjust the importance weights of system noise and observation noise through on-line monitoring the interes...

The Method of Traffic State Identification and Travel Time Prediction on Urban Expressway

This study presented a method of real-time traffic condition identification based on the fuzzy c-means clustering and travel time prediction on urban expressway. The traffic flow characteristics of expressway were analyzed and the traffic flow states were divided into four classes. Then the fuzzy c-means clustering technique was used to classify the sampled historical data and the clustering ce...

Adaptive Kalman Filter Based Freeway Travel time Estimation

Recent advances in vehicle-based surveillance technologies using Global Positioning Systems (GPS) promise high accuracy traffic information; however, their performance in field is insufficient yet mostly due to the lack of the number of probe vehicles. Meantime, the most prevailing traffic surveillance system in the world is the conventional inductive loop detector system although this system o...

Extended Kalman Filter Based Fuzzy Adaptive Filter

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...