Criteria for Setting Speed Limits to Sri Lankan Highways (Built - Up Areas)

Abstract

Speed of vehicles is the pivotal factor in many of the road traffic accidents. Enforcing a suitable speed limit is a tool for enhancing the road safety. However, in Sri Lanka, the currently available posted speed limits are placed without much scientific investigation. Those limits are merely decided by selecting a vehicle category. According to the Gazette of the Demographic Socialist Republic of Sri Lanka, No.1763/26, June 22, 2012 [1] all vehicles are divided into two vehicle categories and proposed only two-speed limits for built-up areas, i.e., 40 km/h for motor tricycles and special purpose vehicles, and 50 km/h for all other vehicles . However, it is understood that road geometry, roadside friction, vehicle density, accident rates, average daily traffic values, etc., should be considered in deciding the speed limits. In that context, the current study is aimed to investigate the influence of such contributory factors on speed limits. Ten site locations with different geometric characteristics, vehicle compositions, and accident rates were selected in built-up areas. Using speed guns, speeds of randomly selected vehicles were recorded. Totally, 3000 vehicle speeds were collected. Initially, vehicles were divided into four categories as motor-bikes, three-wheelers, light vehicles, and heavy vehicles, and performed ANOVA tests to find out whether there exists any difference in 85th percentile speed values between each vehicle category. The intention was to group the vehicles into similar speed clusters. It was identified that motor-bikes and light vehicles (Car/Van/Jeep: CVJ) can be grouped as one cluster while three-wheelers and heavy vehicles (Buses/ Light good vehicles/Heavy good vehicles) as the other cluster. Next, in order to identify the influential factors towards the speed limit of each cluster, correlation with each factor on the speed was observed. From the results it was found that the speed limits of motor-bikes, three-wheelers, and the light vehicles and heavy good vehicles are heavily correlated with factors such as availability of bicycle lanes, availability of shoulders, availability of parking lanes, availability of centre median, the road markings, situation of two way or one way, and the roadside activities. Finally, a multiple linear regression model for each vehicle category was fitted and validated. The most significant factor in deciding the speed limit in built-up areas is the availability of bicycle lanes with a p-value of 0.000 at 5% level of significance. Roadside activities have a significant negative impact on the speed limit except for motor cycles with a p-value of 0.00 at 5% level of significance. These developed models are useful to review the existing posted speed limits in built-up areas.