Collaborative Decision Making Across The Airport Process
Within the airport industry, we are at a crucial point in our evolution. The economic recovery means that global air traffic is set to increase and yet many airports, because of capacity constraints or outmoded legacy IT systems, are not in a position to cope with this growth. As an industry, Collaborative Decision Making (CDM) is being embraced as way of gaining the most out of our existing infrastructure.
(Andrew Shanks, Airport Specialist,
A Better Way to Manage Airports: Passenger Analytics
Airport managers increasingly face operational challenges from steady passenger growth, terminal congestion, rising costs, and difficulty in funding infrastructure. These factors are a simple recipe for deficient facilities, poor service, and unhappy passengers. However, the emerging field of passenger analytics is beginning to be applied to airports, with highly encouraging results. Passenger analytics offers new tools and processes to help airport managers make more effective decisions that improve airport performance, make better use of terminals,
Measuring the customer’s journey through London City Airport
London City Airport (LCY) is the only London airport actually in London, handling 3.65 million passengers in 2014. Some 65% of those using LCY are travelling on business. It should take no more than 20 minutes to get from front door to departure lounge, and no more than 15 minutes from tarmac to train. We call it the 20:15 promise — and it is a promise that presents an obvious challenge: how can we know if we were delivering?
Data-Driven Modelling of Pedestrian Crowds (Doctoral thesis)
At the starting point of the work leading to this doctoral thesis, in January 2005, the work on pedestrians was oriented towards computer simulations and evacuation experiments. Since then, there have been many studies on new methods for extracting empirical data of pedestrian movements (mainly based on video analysis, lasers, and infrared cameras), but most of the work is still focused on artificial setups. There is a knowledge gap between these experiments and the understanding of the dynamics leading to and occurring during large crowd disasters.