Analyzing Spatiotemporal Characteristics of Taxi Drivers' Cognition to Passenger Source Based on Trajectory Data

Seeking passengers is a kind of behavior of taxi drivers with clear purposes. They always need to make decisions on where to seek the next passenger after finishing a trip. Experienced drivers are capable to capture passenger source within a short time to reduce no-load time. Most of the existing literatures focus on simulating or analyzing movement patterns of taxi drivers. This research proposes a method of analyzing spatiotemporal characteristics of taxi drivers' cognition to passenger source. Using a seven-day taxi trajectory data set collected in Beijing, an index CLPS is introduced to evaluate taxi drivers' cognitive level to passenger source. Based on this, spatiotemporal distribution of top drivers' cognition to passenger source is explored. The results of the research show that top drivers' cognition to passenger source has obvious spatiotemporal distribution features. This research is expected to provide new ways for understanding human spatial cognition.