Safe following distance predictive model incorporating vehicle heterogeneity on selected urban expressway / Wardati Hashim - Hashim, Wardati (2019)
With more demands due to the development progress, freight transport seems to grow rapidly around the world. The scenario lead to the high frequencies of heavy vehicle (HV) being on the road which provide a remarkable influence on the traffic flow and following behavior. This research focus on the safe distance following model with a function of headway. Most of the established models did not take into consideration of the heterogeneous condition of traffic but only determined from a car following another car. Furthermore, those models mainly did not include other important parameter such as relative speed, acceleration and deceleration rate. Therefore, the objective of the research is to propose another safety following distance model with a function of time headway that will address the shortcomings of the existing models. The research proposed the model through the analysis of empirical data which was collected using video recording method from a high point located on the bridge across three (3) expressway located in the vicinity of Klang Valley, Malaysia. Then the data was reduced using a specific software name TRAIS. Multiple linear regression of MINITAB 16 was used to estimate the model. This study separate into four different vehicles interaction namely as car-following-car (C-C), car-following- heavy vehicles (C-HV), heavy vehicle-following-car (HV-C) and heavy vehicle-following-heavy vehicle (HV-HV). The results indicate that drivers‘ behavior is significantly different for different vehicle being driven and/or followed. The results show that car has the shortest headway when following other car among other vehicle interaction while HV has the highest headway when following other HV. Results also indicate that the increase of speed will lead to the decrease of time headway. Furthermore, other variables which are relative speed and acceleration/ deceleration seem to have influence on the time headway, which by right improving the finding of other established model in determining the time headway for safe following distance. There is also no significant difference between the empirical and the predicted value, thus indicating that the developed model may contribute to predict the safe following distance in accordance to vehicle interaction. This finding however considered only the traffic parameters as influential factor, on a non-congested urban expressway. Study on the influence of geometric design and on other type of road of during congested time is recommended in the future.