Passively-generated mobile phone data is emerging as a potential data source for
transportation research and applications. Despite the large amount of studies based on the …

Understanding citizens' main transportation modes at urban scale is beneficial to a range of
applications, such as urban planning, user profiling, transportation management, and …

The aim of this paper is to develop an activity-based travel demand model by receiving
cellular network data. Our contribution is to model the uncertainty of human behaviors and …

In this paper, we investigate the existence and prevalence of comparable dynamics in the
temporal fluctuations for the traffic demands generated by mobile applications. To this end …

Understanding customer mobility patterns to commercial districts is crucial for urban
planning, facility management, and business strategies. Trade areas are a widely applied …

Existing studies on activity location recognition based on mobile phone data has made great
progresses. However, current studies generally assume constant distance threshold when …

Trip end identification based on mobile phone data has been widely investigated in recent
years. However, the existing studies generally use fixed clustering radii (CR) in trip end …

Human mobility prediction is a key task in smart cities to help improve urban management
effectiveness. However, it remains challenging due to widespread intractable noises in large …

In recent years, passively collected GPS data have been popularly applied in various
transportation studies, such as highway performance monitoring, travel behavior analysis …

Understanding customer mobility patterns to commercial districts is crucial for urban
planning, facility management, and business strategies. Trade areas are a widely applied …