01472419

Component

The objective of this paper is to present and evaluate an automated road-users classification procedure. The classification is based on the analysis of the motion pattern attributes associated with the trajectories of each road-user type; vehicles, pedestrians and cyclists. A novel approach for features selection is proposed where singular spectrum analysis identifies the main harmonics (speed variation) characterizing the movements trajectories. A constraint-based decision procedure is then applied on the selected features to categorize the road-users. Performance evaluation of the proposed classification is presented. Validation of the procedure is undertaken using real world data set collected at a newly designed mixed traffic roundabout in Greater Vancouver, British Columbia. Satisfactory results were demonstrated and evaluated through performance measures with a reported classification accuracy of around 80 percent. The goal of this research is to improve the understanding of road-users behavior in order to enhance the riding condition and provide an efficient and safe commuting environment. The main benefit of this research is to apply classification as a first step in the activity and behavior recognition of road-users in traffic scenes.

This paper was sponsored by TRB committee ABJ35 Highway Traffic Monitoring.

01470560

13-2894

English

20p

2013

Transportation Research Board 92nd Annual Meeting

Digital/other

Figures; References; Tables

Automatic vehicle classification; Roundabouts; Transportation modes; Vehicle mix

Vancouver (Canada)

Highways; Operations and Traffic Management; Pedestrians and Bicyclists; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2013 Paper #13-2894

TRIS, TRB, ATRI

Feb 5 2013 12:36PM