SUMMARY
Abstract. The car following behaviour of a driver is the process of following the drivers to ?create an adjustment in the leading vehicle behaviour. In a condition, where ?the traffic volume is ?light or in a free-flowing situation, the selection of drivers in relation to ?speed is typically limited by ?some factors such as weather conditions, lighting, and road ?geometry features. In this paper, ?car following headways was analysed based on ?operating speed and time of headway with ?this multilane road?. ?Road? 40 in Kuwait was used as a case study, and the data was collected at the road using device named RTMS Sx-300 which is known as a ?radar device particularly used for monitoring traffic. The data was gathered between the periods ?from 29th December 2018 to 5th January 2019 within winter. MATLAB code was written to analyse and classify the gathered data. Then, the models were built using R-software. The study depicts that nearly 24.87% of the vehicles move 60 to 69 kilometres ?per hour. Additionally, the vehicles were segmented ?according to different kinds i.e. Truck, ?Small, Medium and Large Sized Cars, in order to ?find the impact of following pattern on the ?vehicle average. It has been found that no ?significant association remains amidst the type of ?following pattern and the headway. The finding of this studies complies ?with conclusions drawn by many existing explorations, which declare that just the ?weather, driver’s mood and road conditions influence vehicle headway. Ultimately, a ?liner regression of data was developed to calculate a liner equation that shows the ?headway average as an element of speed for sixteen diverse following pattern. It has ?been recognized that an association could be supposed in medium-sized and small-sized ?vehicles. It has been observed that headway average could be placed in a linear equation ?for large, medium, and small as well as truck vehicles. It is worthy to denote that when ?data is bigger, the exactitude of a study enhances. Findings from each model of liner regression has more than ?80% confidence level. The model of regression are deliberated as statistically ?significant where, the R (square) figures lies amidst 0.99 till 0.6. As per the findings, ?speed is the key influencing factor for headway value. The type of car does affect ?headway with drivers behind Heavy Good Vehicles and cars at the similar speed. ?According to the data, cars are identified to keep more headway when behind Heavy ?Good Vehicles in contrast with when behind other cars. These results will help the drivers to understand their behaviour that are ?associated ?with car crashes. Thus, increase ?road ?safety awareness and reduce traffic congestion in Kuwait.