Name
Abstract | ||
|---|---|---|
In this paper, we investigate the performance of recently proposed driver-behavior modeling techniques for car-following task based on Gaussian mixture model (GMM) and piecewise auto regressive exogenous (PWARX) algorithms. Both driver-behavior modelings are employed to anticipate car-following driving behavior in terms of pedal control behavior (brake and gas/accelerator pedal operation) in response to the observable driving signals of vehicle behavior (i.e., vehicle velocity and following distance between vehicles). The evaluation is conducted using real-world driving data obtained from several drivers under a variety of driving environments. We illustrate the prediction capability of both representative models as the anticipatory time increases from one to five seconds. Furthermore, we investigate the driver-behavior model adaptation framework as a means to better extract individual driving characteristics when the amount of individual driving data is inadequate. This evaluation provides a valuable understanding driver-behavior models' characteristics of real-world car following and its potential to prevent rear-end collision. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICVES.2009.5400201 | ICVES |
Keywords | Field | DocType |
gaussian processes,autoregressive processes,behavioural sciences,man-machine systems,vehicles,gaussian mixture model,driver behavior models evaluation,observable driving signals,pedal control behavior,piecewise auto regressive exogenous algorithms,real world car following task,rear end collision,vehicle behavior,data models,auto regressive,predictive models,vehicle dynamics,lead | Autoregressive model,Brake,Data modeling,Simulation,Collision,Control engineering,Vehicle dynamics,Gaussian process,Engineering,Mixture model,Piecewise | Conference |
ISBN | Citations | PageRank |
978-1-4244-5442-6 | 9 | 0.83 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| pongtep angkititrakul | 1 | 9 | 0.83 |
| Ryuta Terashima | 2 | 31 | 5.62 |
| toshihiro wakita | 3 | 9 | 0.83 |
| kazuya takeda | 4 | 9 | 0.83 |
| Chiyomi Miyajima | 5 | 345 | 45.71 |
| Tatsuya Suzuki | 6 | 178 | 42.47 |