Name
Abstract | ||
|---|---|---|
In this paper, we propose a novel approach to recognize the awareness or the unawareness that a driver has of a pedestrian appearing on the road in front of the vehicle. Based on the theory of situation awareness and the collected driving data from the on board sensors, a suitable Hidden Markov Model (HMM) is used to model the “Driver Awareness of Pedestrian” and the “Driver Unawareness of Pedestrian”. These behaviors are then recognized by using a maximum-likelihood decision method. A real-time validation taken on a driving simulator shows that the model and the output decisions are accurate and efficient. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ITSC.2014.6957823 | ITSC |
Keywords | Field | DocType |
behavioural sciences computing,driver information systems,hidden markov models,maximum likelihood estimation,pedestrians,road vehicles,hmm,driver awareness,hidden markov model,maximum-likelihood decision method,pedestrian,road vehicle,driver behaviors modeling,pedestrian safety,situation awareness,alertness,behavior,real time information | Computer vision,Pedestrian,Driving simulator,Real-time data,Situation awareness,Simulation,Decision model,Artificial intelligence,Engineering,Hidden Markov model,Alertness | Conference |
Citations | PageRank | References |
1 | 0.38 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| minh tien phan | 1 | 3 | 1.11 |
| fremont | 2 | 1 | 0.38 |
| i thouvenin | 3 | 1 | 0.38 |
| mohamed sallak | 4 | 3 | 0.77 |
| Véronique Cherfaoui | 5 | 150 | 16.92 |