One of the objectives of transportation engineers is to maximize safety in road networks while preserving their appropriate efficiency. This could be done by improving the existing projects or enhancing design standards for new transportation components. Another important use of traffic safety studies relates to the investigation of changes taking place in the existing safety level as the characteristics of road system changes, and studies before and after the changes. In general, the safety equipment and safety analysis methods are divided into two groups: passive and active. Passive safety systems have been developed only to respond to vehicle accidents and are effective for this purpose. Such systems protect drivers and passengers against injuries in accidents (Lundgren and Tapani, 2006). Passive safety systems include items such as seatbelts and air bags. Active safety systems help drivers prevent accidents. In other words, such systems reduce the probability of the occurrence of situations where the use of passive safety systems becomes necessary, and thus they provide the passengers with a greater degree of protection. Two examples of such systems are Advanced Driver Assistance System (ADAS), and Vehicular Ad-hoc Networks (VANETs) (Hamid, 2006). Such divisions also exist in road safety assessment methods, and these methods, too, divide into the two active and passive categories. In the passive approach, which has been used for a long time, the objective is to identify black spots by using the number of accidents and statistical models such as the Bayesian model (Hirst et al., 2004). In contrast, the active approach has been developed to assess safety without the use of accident data, and by using other criteria which have a considerably greater number of occurrences. In so doing, the Traffic Conflict Technique (TCT) has been introduced. A conflict is an observable situation where two vehicles or more approach each other in a way that they will collide with each other if they do not change their direction, reduce their speed, etc. (Gousios and Garber, 2009). The criterion for recognizing conflict is the use of safety indices. The safety indices are performance criteria used to identify situations with high probability of collision without recourse to accident statistics (De Leur and Sayed, 2010; An and Harris, 1996). The most common type of collisions in freeways is the rear-end type which usually takes place when the dense flow is being transferred to the free flow, or vice versa (Olmstead, 2001). Studies show that the majority of rear-end collisions take place during the day (76.5%) and in a straight part of the road (90%) (Kipling et al., 1993). The US National Highway Traffic Safety Administration (NHTSA) reported that rear-end collisions, with a frequency of 1.5 million cases a year, comprise 23% of the total number of vehicle collisions in the US (NHTSA, 2002). In Iran, too, 20% of the accidents occurring each year are of the rear-end type. Besides fatalities, the occurrence of rear-end collisions in freeways leads to the reduction of the capacity of freeways and the increase of density. Considering the seriousness of rear-end collisions, great efforts have so far been made to plan and implement effective measures to develop vehicle safety equipment and analyze and assess accidents. Since the occurrence of many rear-end collisions is due to human error (detection and delay errors) (Michael et al., 2000; Treat et al., 1979), the use of Vehicular Ad-hoc Networks (VANETs) as active safety systems could play an important part in reducing such human errors. In this paper, we attempt to assess the effects and role of Vehicular Ad-hoc Networks (VANETs) in enhancing road safety and reducing the number of rear-end collisions in freeways by reducing drivers’ reaction time in facing critical situations. (Author/publisher)
Abstract