Page 81 - Linkline Yearbook 2018

‘Data Dawn’: Making Up for Lost Time in Transport Planning
Getting Big Data and commuter usage to plan and help us build the transport networks of the future will go some way to making good on the shortcomings of the past. Linkline Journal reports.
Quality infrastructure underpins national prosperity. Let’s say that again - quality infrastructure underpins national prosperity.
The Cross City Luas project officially opened earlier in December, another small piece in Ireland’s growing commuter network and another step on the way to a more prosperous future for us all. The long slow grind of getting Ireland’s transport infrastructure up to speed has not been without its challenges. One point often made here is our lack of foresight and planning on infrastructure, and it hasn’t been easy recently on an economic front either.
The launch of the new Luas route also heralds in a new era in transportation behaviour. Commuting and transportation behaviour, both private and commercial, is changing rapidly. The factors that ultimately influence all of this are shifting dramatically and creating new challenges for planners. Household composition characteristics are changing, younger generations are more likely to live in high density housing, buying less cars and homes than their parents, and are delaying having children. Combine this with the current difficulties of getting appropriate accommodation in Ireland and it can all lead to a very complicated picture on which transport operators need to project the future.
But Travel Demand Modelling, as it’s known, is getting easier by the day as more and more commuters begin to digitally interact with whatever transport service they use. Planners have historically relied on old or remodeled data to design their project. They never had real-time data to evaluate performance after a project was completed. The use of
sensors or surveys were labour intensive and expensive. If planners wanted to make performance-based improvements as they implemented policy or infrastructure changes, they often had to start from scratch with data collection. This could create flaws if the targeted commuters or transport network had seasonal variations, changing populations/ workforce or new technologies such as ride-sharing (e.g. Uber) impacting on the infrastructure’s usage.
Our cars, our trains and trams, our bikes, buses and taxi apps are not only beginning to sync to a diverse number of networks. These are giving us vast quantities of data that can help plan, interpret and visualise solutions. This is where Big Data comes into its own. There is a massive volume of geospatial information created by mobile phones, GPS devices, connected cars and commercial vehicles, fitness trackers, tolling usage, city bikes and more. All of these devices ping mobile phone masts and satellites while on their journeys, creating location and movement records as well as time of travel and length of journeys. With the right software, these records are then mapped into useful information that can aid planners on building the smart transport network of the future that responds to the demands of the commuters’ usage.
Transport providers across the globe are witnessing growing demand that is exceeding capacity but are often unable to build additional infrastructure as a result of lack of space and/or funding. Passenger information has significantly improved in recent years, with announcements, websites, emails and app notifications alerting people to hold-ups and suggesting alternative routes. Congestion and delays annoy
The CharTered InsTITuTe of LogIsTICs & TransporT 81
DATA DAWN