Name
Abstract | ||
|---|---|---|
Robust prediction of pedestrian behavior is one of the most challenging problems for autonomous driving. Particularly, predicting pedestrian crossings at crosswalks is of considerable importance for avoiding accidents on the one hand and not unnecessarily slowing down traffic on the other hand. Traditional model-based motion tracking and prediction approaches have difficulties in capturing abrupt ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TITS.2018.2827956 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
Trajectory,Prediction algorithms,Automobiles,Roads,Safety,Measurement,Task analysis | Computer vision,Pedestrian,Task analysis,Prediction algorithms,Artificial intelligence,Engineering,Match moving,Trajectory | Journal |
Volume | Issue | ISSN |
20 | 2 | 1524-9050 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| benjamin volz | 1 | 4 | 2.14 |
| Holger Mielenz | 2 | 6 | 2.23 |
| Igor Gilitschenski | 3 | 78 | 13.89 |
| Roland Siegwart | 4 | 7640 | 551.49 |
| Juan I. Nieto | 5 | 939 | 88.52 |