ارزیابی برخوردهای ترافیکی مربوط به حرکات خارج از لاین موتور سیکلت ها در شرایط ترافیک سنگین Traffic conflict assessment for non-lane-based movements of motorcycles under congested conditions

۱٫ Introduction Motorcycles are the main mode of transportation in several developing Asian countries. The basic difference in the movement of a car and that of a motorcycle relates to lane-based and non-lane-based movements, respectively. A car runs in and seldom changes lanes. However, a motorcycle frequently changes direction, especially under congested conditions. When a road lacks a motorcycle lane, a motorcycle need not follow lane discipline. For example, a motorcycle may travel alongside other vehicles in the same lane [1] or obliquely follow a lead vehicle [2]. Such non-lane-based movements of motorcycles are unique and in- fluence the likelihood of traffic accidents. Hence, in this study, we focus on the effects of such non-lane-based movements on traffic conflict under congested situations. Many researchers have attempted to represent non-lane-based movements by separating them into longitudinal and lateral movements. Because longitudinal movement resembles car following, the traditional car-following model has been used to describe this movement. However, when modeling lateral movement, many different models have been developed on the basis of different assumptions regarding the relationship between longitudinal and lateral movements. Cho and Wu [3] assumed that the lateral position of a motorcycle was determined by the average lateral position of the surrounding vehicles weighted by their longitudinal positions. Minh et al. [4,5] supposed that a motorcycle runs on a “dynamic lane” to follow a lead motorcycle on the same dynamic lane or change lanes to overtake its leader. The width of the dynamic lane was calculated using the linear relationship between the distance separating two vehicles running side-by-side and the average speed. Lan and Chang [6] developed a cellular automation model to simulate two-dimensional motorcycle movements. They set the size of a cell unit to 1.25 m × ۱٫۲۵ m to represent a motorcycle as 2 × ۱ cell units. A motorcycle can then move from one cell to another based on simple moving rules developed for motorcycles, such as carfollowing, lane-changing, or overtaking. Moreover, most models do not consider safety factors such as reaction time, safety distance,  or speed difference related to the description of collision avoidance behavior. Nguyen et al. [14] proposed the concept of a safety space in which longitudinal and lateral movements can be integrated. This model has the potential to evaluate the safety issues of nonlane based motorcycle movements. The safety level of a vehicle is denoted by the number or rate of accidents involved with the vehicle. There are two popular approaches for estimating the safety level of a vehicle: (1) development of safety performance functions that relate the number or rate of accidents to the explanatory variables by using regression analysis, and (2) development of simulation models to calculate the safety level through measures for traffic safety assessment. In the former, correlations among variables are found by analyzing the dispersion and approximated by deriving regression formulas. Neuman and Glennon [7] found correlations among the road environment of road design, infrastructure, and accident causes. Warshawsky-Livne and Shinar [8] found relationships between the reaction time to a brake light and the driver’s gender, age, level of expectancy for the brake light, as well as the number of times that a task was performed. However, this approach requires consensus data on traffic accidents, which are very difficult to collect in most developing Asian countries. In reality, the probability of a traffic