Abstract: Heuristic decision making, spatial cognition, and community recognition theory are combined to describe the relationship between route selection and road network structure. The community structure algorithm based on module gain is used to deconstruct the road network structure, describe people's cognitive process, and establish the corresponding path selection algorithm. Taking the road network within the central area of Changsha city as an example, the proposed path selection method is used to deconstruct the road network and calculate the path selection sets for the static road impedance (distance) and dynamic road impedance (speed). The questionnaire survey and taxi GPS data are used to extract the actual path selection trajectories, and the theoretical computation results and the actual survey results are compared. When the static road resistance is used, the consistency rate is 85%, when the dynamic road resistance is used, the consistency rate is 73%. These results show that the proposed model integrating spatial cognition and community recognition can describe people’s route choice process better. The model has a better accuracy for static road resistance-based route choice. The results of this study can be a reference for urban planning and traffic planning.

Key words: urban traffic, route choice, spatial cognition, community recognition, module gain