Development of Performance Measurement Models for Two-Lane Roads under Vehicular Platooning Using Conjugate Bayesian Analysis

Abstract

Vehicular platooning is one of the most challenging issues affecting the level of service (LOS) of two-lane roads. This phenomenon has been involved with variables governing performance measures. Thus, to improve the quality of these roads and predict a comprehensive model for future plans under this phenomenon, the present study aimed to evaluate the effect of vehicular platooning variables on performance measures and then identify the critical headways of vehicular platooning associated with the vehicle-gap-acceptance behavior. Multiple linear regression (MLR) and Bayesian linear regression (BLR) models were used to develop performance measurement models that are based on conjugate Bayesian analysis. The vehicular platooning was formed in the threshold of a time headway of 2.4 s. According to a comparative evaluation of the developed models, the best predictive model was found between the traffic flow and the number of followers per capacity (NFPC). In addition, the BLR model showed a higher accuracy rate in predicting NFPC compared with the MLR model due to low errors and high prediction performance. Thus, NFPC was introduced as a surrogate performance measure, which had a premier capability to predict the LOS for unsaturated and saturated traffic conditions compared with the two performance measures from the Highway Capacity Manual (2010), including percent time spent following and average travel speed.