A two-stage short-term traffic flow prediction method based on AVL and AKNN techniques

Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.

Microscopic dynamic simulation model for pedestrian at signalized intersection

Pedestrian's road-crossing model is the key part of micro-simulation for mixed traffic at signalized intersection.To reproduce the crossing behavior of pedestrians,the microscopic behaviors of the pedestrians passing through the crosswalk at signalized intersection were analyzed.A pedestrian's decision making model based on gap acceptance theory was proposed.Based on the field data at three typical intersections in Beijing,China,the critical gaps and lags of pedestrians were calibrated.In addition,considering pedestrian's required space,a modification of the social force model that consists of a self-deceleration mechanism prevents a simulated pedestrian from continuously pushing over other pedestrians,making the simulation more realistic.After the simple change,the modified social force model is able to reproduce the fundamental diagram of pedestrian flows for densities less than 3.5 m-2 as reported in the literature.