Developing a model to determine the number of vehicles lane changing on freeways by Brownian motion method

Abstract

Abstract Lane change maneuvers are essential on car trips. Drivers change lanes to follow the desired route to reach their destination or improve their driving condition or level of service. To change lanes, a driver must consider several factors that affect safety. Due to the lack of appropriate data and consequently the lack of appropriate models to determine the number of lane-changes on the road (as an influential factor in accidents), this study attempts to collect proper data in a new way. Thus, the Qazvin-Karaj freeway was selected as the case study. After installing the imaging cameras and performing the image processing, SPSS and Expert Design statistical software were used to model development. The Brownian motion model was also used to construct the driver change lane model. The results showed that logarithmic model number 2 reported a better coefficient of determination than other models with a value of 0.472. Then models 3 and 9 were ranked with R 2 of 0.451 and 0.442, respectively. Also, the Expert Design model with R 2 (0.786) could have a better fit. The value of the response variable (Nch + 0.52)0.74 was obtained three-dimensionally against the changes of distance from the front vehicle (Df ) and distance from the rear vehicle (Db ). Variable values of distance from the front car and distance from the rear vehicle have more effective values on the number of lane changes than left and right distance values. The observed and Brownian data had a slight mean difference (0.018), and also, the standard deviation was so small. Also, the correlation in this data pair is 0.912, which is a suitable value and indicates a slight difference between the outputs of the Brownian model and the observations.