A multilane cellular automaton multi-attribute lane-changing decision model

Through exploring driver's lane-changing decision mechanism, we divide the lane changing decision-making process into two stages, i.e. lane-changing motivation and lane-changing decision. The influence attributes of decision-making are classified into two categories, i.e. internal decision attributes and external decision attributes. This paper presents a multi-attribute lane-changing decision model based on analytic hierarchy process after above work, introduces a newly-modified multilane traffic cellular automata model. By means of the numerical simulation under different traffic densities with various lane-line-markings as the external decision attributes the obtained conclusions show that, of a vehicle in system at each update time-step, the average lane changing motivation probability is related directly to the internal decision attributes and the average lane-changing success probability is depend on both of internal and external decision attributes, the distribution of the lane-changing motivation probabilities and the lane-changing success probabilities fully response the variations of lane-line-marking. By and large, the proposed model has ability to analysis the legal implication of each pattern of lane-line-marking set in this paper. Due to the excellent expansibility of analytic hierarchy process frame structure, it should be improved to deal with more external decision attributes synchronously in future research. (C) 2019 Elsevier B.V. All rights reserved.