In literature, scientists describe human mobility in a range of granularities by several different models. Using frameworks like MATSIM, VehiLux, or Sumo, they often derive individual human movement indicators in their most detail. However, such agent-based models tend to be difficult and require much information and computational power to correctly predict the commutation behavior of large mobility systems. Mobility information can be costly and researchers often cannot acquire it dynamically over large areas, which leads to a lack of adequate calibration parameters, rendering the easy and spontaneous prediction of mobility in additional areas impossible. This paper targets this problem and represents a concept that combines multiple substantial mobility theorems formulated in recent years to reduce the amount of required information compared to existing simulations. Our concept also targets computational expenses and aims to reduce them to enable a global prediction of mobility. Inspired by methods from other domains, the core idea of the conceptional innovation can be compared to weather models, which predict weather on a large scale, on an adequate level of regional information (airspeed, air pressure, etc.), but without the detailed movement information of each air atom and its particular simulation.
Unified Mobility Estimation Model
2021-09-19
2595934 byte
Conference paper
Electronic Resource
English
A unified equilibrium framework of new shared mobility systems
Elsevier | 2019
|A unified framework for scene illuminant estimation
British Library Online Contents | 2008
|A Unified Smart Mobility System Integrating Terrestrial, Aerial and Marine Intelligent Vehicles
British Library Conference Proceedings | 2020
|A unified estimation for scheduled controllers in nonlinear systems
Tema Archive | 2001
|