Survey on various lane and driver detection techniques based on image processing for hilly terrain. Issue 9 (1st September 2018)

• Record Type: Journal Article
• Authors: Manoharan, Kodeeswari; Daniel, Philemon
• Is Part Of: IET image processing. Volume 12:Issue 9(2018)
• Page Start: 1511
• Page End: 1520
• Publication Date: 2018-09-01
• Subjects: traffic engineering computing -- road safety -- roads -- road traffic -- road vehicles -- driver information systems; driver detection techniques -- hilly terrain -- vehicular traffic -- traffic management -- travel -- mountainous roads -- Himalayan mountains -- greater risk -- rugged natural setting -- crucial problems -- hilly roads -- existing driver‐assistance systems -- survey probes every lane detection algorithms -- image processing techniques -- assistance features; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.0864
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : As vehicular traffic continues to grow traffic management and prevention of accidents has become a major concern. This problem only gets magnified when travel on the mountainous roads are considered. This study is especially focused toward Himalayan mountains as they pose a greater risk because of their rugged natural setting. This study investigates crucial problems faced on the hilly roads and the challenges in translating existing driver‐assistance systems to such roads. The survey probes every lane detection algorithms, image processing techniques and various assistance features for applicability to hilly roads discussing the pros and cons for each of them. Conclusions are drawn as to deduce the more suitable methods that can be improvised and re‐tuned to adapt them for mountainous roads.