Genetic Programming for Estimating Passenger Car Equivalent in Unsignalized Intersections

Abstract

The study concentrates on two different Genetic Programming approaches for determining Passenger Car Equivalent(PCE) values and observing the impact on capacity estimation at urban unsignalized intersections. Considering heterogeneoustraffic conditions, a new PCE value is introduced to encompass sustainable modes of public transit vehicles, specifically Slow-moving three-wheelers (SM3W), commonly known as E-Rickshaws. Since PCE value is considered an important parameter forcapacity calculations, the present study considered 14 unsignalized intersections located in Ranchi city of India. An automaticplate recognition system is employed to have the count of vehicular traffic. The methodologies include Age layered populationstructure genetic programming (ALPSGP), and the Offspring selection genetic programming (OSGP) approach that incorporatesstatic and dynamic variables. Based on the significance test and ranking of the Genetic programming (GP) models, the OSGPmodel is recommended as the most appropriate model for heterogeneous traffic. Sensitivity analysis reported that laggingheadway (����) is the most contributing factor in PCE estimation. The PCE value of SM3W is found to be 0.81 and that could beincorporated as a new classification of vehicles in Indo-HCM. It is observed that evaluated capacity based on OSGP’s PCEvalues performed admirably in both normal and congested traffic situations.