Intelligent Control of Long High-Speed Moving Walkways

Research of Indraswari Kusumaningtyas

A continuous transport system such as a moving walkway is a promising alternative of people mover because it continuously provides transport capacity during operation. This characteristic eliminates waiting time for passengers. The latest innovation of this system is the development of accelerated moving walkways (AMWs), which provide higher speed. However, the application of moving walkways is still limited to short-distance travel. In this research, we study the development of long-distance AMWs and their control.

Problem domain

The objective of this research is to develop a concept of long-distance AMWs that implement distributed drives, such as those applied in bulk material belt conveyors. Control is an important issue related to the application of the distributed drives. The behaviour of the passengers who use the AMW will be evaluated to see its influence towards the load distribution in the system, and eventually towards the control.


The passenger behaviour on the AMWs will be simulated using a pedestrian behaviour model. With this model, the load distribution along the AMWs will be predicted. A model of the AMW will also be built to simulate the dynamics of the system due to the load distribution. Based on the dynamics of the system, the appropriate control scheme will be investigated.


To date, a study has been performed to evaluate the feasibility of developing Accelerating Moving Walkways (AMWs) as a low-cost, high-capacity people mover for long-distance travel. A review of the literatures on public transport systems and (accelerating) moving walkways was carried out. It is concluded that long-distance AMWs have competitive characteristics and are feasible to develop. Further research will study the control of the system related to the implementation of distributed drives, taking the behaviour of the pedestrians who use the AMWs into the evaluation.


Indraswari Kusumaningtyas, MSc
Tel: +31-15-2789417
Fax: +31-15-2781397