Transportation

A co-evolution agent-based model for systems of cities and transportation networks integrating top-down governance through game theory

The evolutionary theory for systems of cities at the macroscopic scale proposed by [1] suggests the existence of co-evolutionary dynamics in the trajectories of cities and their environment. In particular, transportation infrastructure connecting cities can in some cases co-evolve with them [2]. Understanding such processes is crucial for sustainable planning at large scales. The issue of the interplay between bottom-up emergence of urban dynamics and top-down planning of infrastructures is in that context relevant to study.

Analysis and modeling of flight delays in air traffic systems

The increase of flight delays in recent years which resulted from the rapid development of the civil aviation industry have become a worldwide challenge in recent years. Thus, it is of great importance to understand the origin and mechanism of flight delays in the complex socio-technical air traffic systems, a problem that attracted much attention recently [1,2,3]. Here, we apply a comprehensive analysis of the delay distributions and propose a mathematical model that could help to improve the understanding of delay cascades and the accuracy of flight delay predictions.

Optimal assignment of buses to bus stops in a loop by reinforcement learning

Bus systems involve complex bus-bus and bus-passengers interactions. In this paper, we study the problem of assigning buses to bus stops to minimise the waiting time of passengers.

A co-evolution agent-based model for systems of cities and transportation networks integrating top-down governance through game theory

Analysis and modeling of flight delays in air traffic systems

Optimal assignment of buses to bus stops in a loop by reinforcement learning

Partners

Twitter

Facebook

Contact