Name
Abstract | ||
|---|---|---|
This paper first reports a data acquisition method that the authors used in a project on modeling driver behavior for microscopic traffic simulations. An advanced instrumented vehicle was employed to collect driver-behavior data, mainly car-following and lane-changing patterns, on Swedish roads. To eliminate the measurement noise in acquired car-following patterns, the Kalman smoothing algorithm was applied to the state-space model of the physical states (acceleration, speed, and position) of both instrumented and tracked vehicles. The denoised driving patterns were used in the analysis of driver properties in the car-following stage. For further modeling of car-following behavior, we developed and implemented a consolidated fuzzy clustering algorithm to classify different car-following regimes from the preprocessed data. The algorithm considers time continuity of collected driver-behavior patterns and can be more reliably applied in the classification of continuous car-following regimes when the classical fuzzy C-means algorithm gives unclear results |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TITS.2006.883111 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
continuous car-following regime,car-following behavior,classical fuzzy c-means algorithm,driver-behavior data,data acquisition method,regime classification,kalman smoothing algorithm,different car-following regime,consolidated fuzzy clustering algorithm,behavior measurement,preprocessed data,car-following stage,fuzzy clustering,kalman filtering,data acquisition,microscopy,state space model,clustering algorithms,kalman filters,pattern recognition | Computer vision,Fuzzy clustering,Simulation,Fuzzy logic,Data acquisition,Traffic simulation,Kalman filter,Smoothing,Acceleration,Artificial intelligence,Engineering,Cluster analysis | Journal |
Volume | Issue | ISSN |
8 | 1 | 1524-9050 |
Citations | PageRank | References |
25 | 2.96 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoliang Ma | 1 | 182 | 18.51 |
| Ingmar Andreasson | 2 | 25 | 3.30 |