Research on influencing factors of travel in underground space based on multi-source data: Spatial optimization design for low-carbon travel

Abstract

The utilization of underground space plays a vital role in saving land, alleviating traffic pressure, and improving the utilization of resources. The combination of walking and metro instead of cars is an effective way to reduce energy consumption and CO2 emissions. However, transfer inconvenience, poor accessibility, lack of vitality, and other phenomena in the underground hinder this low-carbon transportation utilization. This paper aims to improve travel quality and efficiency by optimizing underground space design to reduce CO2 emissions and raise energy efficiency. Taking a typical underground space in Nanjing as an example, multi-source methods such as field measurement, POI, and space syntax are used to quantify the factors affecting underground space travel. Correlations between each factor and the density of passenger flow distribution are discussed. The results show that catering and shopping are the most correlated factors of the pedestrian flow distribution on weekdays and weekends, respectively. Through simulation, the optimized design can increase the passenger flow and reduce CO2 by 277.9 g/Km and 119.1 g/Km per minute on weekdays and weekends, respectively. The design is consistent with the result of 219 questionnaires. This research method has positive significance for developing underground space in other Chinese cities under low carbon background.