In this paper, I discuss the implication of human factor applying SHELL model in the context of accident toll in NSW roads. As well, I discuss how human factor is affected by technology, policies and procedures, the environmental conditions surrounding the driver of vehicles. In addition, how these variables affect risk taking and inappropriate decision-making, which leads to accidents on roads affecting their attitudes, behavior and motivation. The SHELL Model is used to develop road safety strategies to address accident rate reduction on New South Wales Roads.
Abstract
In the context of accident prevention and reduce the likely hood of recurrence of accident in the future, human element is the most adaptable but also vulnerable to influence, which can affect human performance in a given operational condition. In the context of road accident in New South Wales, the risk taking behavior of drivers may be due to psychological and social factors. . For example, peer group pressure, drink driving and perception, hazard perception, other social factors like family environment, traffic congestion, weather condition, road condition, perception of seat belts and its importance, fatigue perception and driving, inappropriate use of technology, driver distractions, licensing systems, law enforcement and penalty system, in appropriate education and training, may affect different driver groups and may affect their risk taking behavior on roads and may be contributing to the incident of accident or may contribute to accident on New South Wales road.
To get a deeper insight in to the accident prevention and recurrence, the SHELL model even though it is developed for Aviation Industry safety prevention and accident reduction it can shed light why human error occur and what factors interact to contribute to accident on roads in New South Wales.
The SHELL model places emphasis on human beings and its interfaces with other parts of a system such as hardware which is the Road and traffic physical system in NSW, procedures, education training and support systems the software and the environment or operational conditions such as weather condition, condition of roads, sign system, traffic congestion, social factors and demographic factors in the context of road accident in New South Wales. That is Shell model is a system approach, which encourages to develop a comprehensive road safety counter measures addressing all the parts of the system and not to focus on one or two factors which contributes to human error and produces in appropriate behavior. This enables to develop effective road safety strategies, which is comprehensive and researched, based and tailor programs to targeted groups of drivers and to high-risk areas. As well, allocate resources in a cost effective manner, which produces maximum reduction in accident rate in New South Wales. In this paper, I discuss in detail how the SHELL model can be applied to develop road safety strategy development based on what factors interact to produce accident based on current research on factors affecting accident on particular driver groups so that to develop targeted strategies based on the findings of these research and consider all elements of the road system as depicted by the SHELL model.
As discussed above, in terms of Live ware in the SHELL model it consists of the risk-taking behavior of drivers such as drink driving and perception, fatigue and fatigue perception. driver distraction behavior such as use of mobile phone when driving and talking with others when driving, speeding behavior, perception and the use of seat belts, driver braking the road rules frequently. The software consists of law enforcement and fairness, penalty and other deterrence methods, fatigue break availability and encouragement methods, driver education methods and procedures, speed limits, support systems. As well, software consists of the use of warning systems and other technology to limit speeding automatically, licensing system. The Hard ware in the Shell Model consists of the actual road infrastructure in terms of freeways, number of lanes. Specific lane uses by different categories of road users, road sign system, pedestrian overpass, linking roads, and roundabouts, Speed bumps, street lights, signal light systems, speed cameras, line markings on road, bridges, tunnels, variety of different sizes and models of motor cars, trucks, vans, motorbikes and bicycles used on the road system and the number of vehicles used on a particular part of the road system. The environment in the SHELL model consist of weather conditions, traffic congestion, road condition, social factors such as family environment, peer group pressure, drug and alcohol usage, age, gender, sex and ethnic factors. driver fatigue
Age. Sex experience and risky driver behavior
Catchpole J (2005) in an article "Learning to take risks: The influence of age and experience on risky driving using traffic offences as measure for risky driving" from Road Traffic Authority of NSW has found that the inexperience drivers with the same age with increasing experience at younger age for males and females commit high risk and low risk offences. However, he has found in his study that males at every age with experience have more probability to engage in high and low risk-driving behavior than females. In addition, within the high risk and low risk the most important driver behavior contributing to these offences are caused by speeding than any other factors like drink driving and other inappropriate driver behavior. On this basis of his findings. he has recommended reducing these high risk and low risk behavior by widespread use of speed and red light enforcement cameras at signalized intersections. As well, he has suggested as a countermeasure from the findings of this research that to have media educational campaigns directed to young inexperienced particularly male drivers as well to have enforcement activities concentrated in times and places where the young inexperienced drivers are prevalent at night-time, weekends and close to sports clubs to reduce traffic offences and accidents of young inexperienced male drivers.
