Automatic Social Behaviour Detection of Driver in Context Environment of Tier 2 City

Nowadays, Tier 2 cities in India are mostly suffering from accidents because of excess and improper utilization of space among congested roads causing some impact on social as well as physical behaviour of driver with improper traffic signal monitoring, various distractions including use of mobile phones while driving, casual or zigzag drive of the young aged peoples. These are the context aware situation combining human error causes increment in accidental situations. In such cities approximately 70 % of the accidents are caused by human error, from which the major factor involved in accident is the action of driver towards social rule i. e. nothing but drivers social behaviour. So, for automatic monitoring of drivers behaviour toward social rule, preventing driver from doing secondary activity while driving, to remove the manual burden of traffic police and therefore to prevent peoples from accidents the approach is proposed in this paper on automatic detection of human error, which makes the use of powerful search technique i. e. particle swarm optimization and other image processing tools to gain the optimized solution towards traffic problems