NDLI: Automated class identification of modes of travel in shared spaces: a case study from India

Content Provider	IET Digital Library
Author	Zaki, Mohamed H. Sayed, Tarek
Abstract	This paper presents a classification approach for road-user modes of travel. The classification does not assume well organized, and lane disciplined traffic. Instead, it relies on specific characteristics intrinsic for each road-user to predict the corresponding class. The classification relies on extracting the geometric and movement characteristics of road-users. As such, it is possible to classify road-users in shared space facilities and sites with high level of non-compliance. The classification is a multi-step procedure. First, movement features are used to discriminate between motorized and non-motorized road-users. Then, complementary features based on road-user geometry are added to differentiate between vehicles, rickshaws, powered two-wheelers, and buses. Experiments are performed on a video data set from a shared facility in New Delhi, India. A performance analysis demonstrated the robustness of the proposed classification method with a correct classification rate of up to 90 percent. By considering the movement attributes, the approach is tolerant to considerable variations in road-user physical details which often arises from choices of camera positions and partial occlusions. The research is part of the long-term goal to develop an automated video-based road safety and data collection system for developing countries.
Starting Page	765
Ending Page	773
Page Count	9
ISSN	1751956X
Volume Number	12
e-ISSN	17519578
Issue Number	Issue 8, Oct (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/12/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2017.0099
Journal	IET Intelligent Transport Systems
Publisher Date	2018-04-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automated Class Identification Automated Video-based Road Safety Camera Positions Complementary Features Computer Vision And Image Processing Technique Data Collection System Feature Extraction Geometric Extraction Image Classification Image Recognition India Lane Disciplined Traffic Multistep Classification Procedure New Delhi Partial Occlusions Road Safety Road-user Geometry Road-user Mode Road-user Movement Characteristic Sensitivity Analysis Shared Space Facilities Traffic Engineering Computing Video Cameras Video Dataset Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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