Du, Yingzi, 1975-Jiang, PinggeKing, BrianRizkalla, Maher E.2015-01-052015-01-052013https://hdl.handle.net/1805/5606http://dx.doi.org/10.7912/C2/2507Indiana University-Purdue University Indianapolis (IUPUI)Pedestrian and vehicle interaction analysis in a naturalistic driving environment can provide useful information for designing vehicle-pedestrian crash warning/mitigation systems. Many researchers have used crash data to understand and study pedestrian behaviors and interactions between vehicles and pedestrian during crash. However, crash data may not provide detailed pedestrian-vehicle interaction information for us. In this thesis, we designed an automatic pedestrian tracking and status analysis method to process and study pedestrian and vehicle interactions. The proposed pedestrian tracking and status analysis method includes pedestrian detection, pedestrian tracking and pedestrian status analysis modules. The main contributions of this thesis are: we designed a new pedestrian tracking method by learning the pedestrian appearance and also their motion pattern. We designed a pedestrian status estimation method by using our tracking results and thus helped estimate the possibility of collision. Our preliminary experiment results using naturalistic driving data showed promising results.en-USpedestrian detectionpedestrian trackingpedestrian status analysisnaturalistic driving dataPedestrian traffic flow -- Research -- Analysis -- EvaluationPedestrian accidents -- ResearchLocation-based services -- ResearchMotor vehicle drivers -- Safety measuresPedestrian areas -- ResearchTransportation engineering -- Research -- Safety measuresTraffic accidents -- ResearchMotor vehicles -- Automatic location systemsHuman engineering -- Safety measuresHuman-computer interaction -- ResearchUser-centered system design -- Research -- Safety measuresPedestrian facilities designThesis