An improved micro model for stochastic traffic load simulation with consideration of axle load and microscopic behavior

Abstract

Simulating the stochastic traffic load has been an important issue for bridge condition evaluation. This paper proposes an improved cellular automaton for stochastic traffic load simulation with consideration of axle load and microscopic interaction. The cells, neighbors, transition rules and boundary conditions in the improved model are all redefined. The cell length can be manually defined with any value. The vehicle load can be precisely simulated using axle load if the cell length is set small or using concentrated load when a large cell length is defined. Acceleration based transition rules are proposed, and different acceleration for each vehicle can be computed to more reasonably simulate the microscopic behavior. The feasibility of the proposed model is validated through comparisons on traffic flow simulation and load effect quantification with in-field weigh in motion data and other models. The results indicate that the proposed model improves the existing models both in vehicle load simulation and traffic flow simulation and can be used for stochastic traffic load simulation for bridges with any length.