Executive Summary : | The World Health Organization states road crashes as the 9th leading cause of deaths in 2015. The WHO also recognizes the fact that albeit developing and lower-middle income countries own approximately half of world's vehicles, 90% of the world's fatalities on the roads are reported by them. According to the National Crime Records Bureau, India, 4,64,674 road accidents were recorded in the year 2015 responsible for 1,48,707 fatalities & 4,82,389 injuries of people. Among these accidents, a total of 75.3% fatal road accidents are caused by human factors. Two wheelers alone have 29.3% of total road accidental deaths among all other vehicular accidents.
Literature is evident of the reduction in driving performance due to the interference of human behavioral factors with respect to reduced reaction time, increase in unintended lateral deviations and other lateral performance measures like lateral excursions, which indicate the loss of driver control over the vehicle and in turn exposing the driver to crash risk. The previous studies on safety analysis rely widely on the crash statistics, but the difficulties in collecting such data, and its inability to measure the effect of desired countermeasures or introduction of advancements which are currently absent in the traffic management system; a popular alternative approach to collect data for research is using a simulator. In the same lines, this study also targets to analyze crash severity and risk factors to motorcycle riders using a motorbike simulator. Therefore, the purpose of the current research is to investigate the underlying risk factors associated with human attitudes and alertness towards driving and safety of themselves as well as the other road users.
This study aims at presenting the causes and potential situations of human behavior in different scenarios of motorcycle-vehicle and motorcycle-road user interactions on different road facilities like intersections, rural highways, and urban arterials. This can be studied using questionnaire surveys or through interviews of motorcyclists involved and responsible for the safety critical instances in the past. In recent times, simulators provide the privilege to test typical human behaviors at micro levels of vehicle and driver interaction without any actual risk of crash or injury. However, attempts have also been made to study motorcyclist behavioral aspects in a naturalistic environment by subjecting to controlled riding conditions. Keeping in view the high ownership rate of two wheelers in India, the study has provided the platform for the recent emergence of driving assistance systems and detection models (e.g., driver alcohol detection, drowsiness detection systems) for Powered Two Wheelers. These models can be applied as vehicle collision avoidance alert systems to help in reducing potential risks due to drowsy driving or help in policy making and amendments to reduce behavioral contribution in road traffic crashes. |