The estimation of pedestrian traffic in urban areas is often performed with computationally intensive microscopic models that usually suffer from scalability issues large-scale footpath networks. In this study, we present a new macroscopic user equilibrium assignment problem (UE-pTAP) framework for networks while taking into account fundamental properties such as self-organization bidirectional...

Traffic assignment is a crucial phase in transportation planning, involving the distribution of trip data between origin and destination points obtained from surveys across existing or planned road network. This process helps estimate traffic volume on each segment. In this study, we propose model utilizing Logit methodology. As comprehensive path-based model, approach determines probability us...

In this paper, we first develop the concept of the maximum entropy function for equilibrium programming by employing prior distribution information and Kullback entropy. It plays a key role in entropy function method for solving equilibrium programming. After analyze and discuss the relation with the model transformation equivalent applied in mixed traffic assignment problems, and finally we gi...