Page 82 - Linkline Yearbook 2018

customers, increases the wear on assets and slows down the network. At peak times, traffic flows unevenly, and buses and trains become increasingly delayed at each stop as the crush of passengers trying to get on board stops swift arrivals and departures. In other words, congestion creates more congestion.
But with everyone diverted, these messages can create new bottlenecks elsewhere. Similarly, while motorists’ satnavs try to divert them around traffic jams, the different providers
– lacking coordination or predictive capabilities – simply divert everyone in the same direction thereby creating new queues on minor roads that are even less able to cope with demand.
Technology and data requirements
Technologies have made significant advances in recent years but infrastructure capacity remains stretched. Focussed investment in tools has significant potential to improve journey times, travellers’ experiences, and investment returns across all of our major cities and our national transport networks.
One such technology has been developed by a company called StreetLight Data. An unimaginable amount of data exists on people's online and e-commerce activity but there is virtually no information about how people commute, shop and travel in the real world. Given how important transportation is for quality of life, pollution, the economy and climate change. StreetLight Data was started to unlock barriers to data-driven transportation, urban design, and commercial planning. We already know much of the data and the underlying capacity of the transport infrastructure but the dots need to be joined to find the solution to planning which will allow for the variables of future transport planning. But important questions have to be asked of the data. How much of this data for instance relates to people on shopping trips/work commutes etc? What percentage of trips are for ‘spur of the moment’ business, family or other
reasons? What impact will the use of electric and driverless cars have in the future?
In Dublin alone we already have established databases serving Leap card, tolling, tolling tags, data from car parks, electronic street parking, city bikes cards, bus cards and rail cards, taxi hailing apps etc. These are all powerful data assets: contact details for many commuters, plus an insight of their typical travel patterns. Now is the time to invest heavily in tools and resources to analyse data and tailor customer communications. The growth of data collection in respect of individual customers together with multiple engagement channels and the use of individual customer accounts allows transport operators to segment travellers experiencing congestion or delays and suggest to each group a different way to reach their goal. Using emails, SMS and apps, operators can offer passengers incentives if they take a particular route, travel at a particular time, or use a particular mode. And with real-time data coming in on recipients’ behaviour, operators can quickly adjust their messages to focus on the most effective incentives and the most responsive travellers.
Transport for London (TfL) is currently investigating the use of mobile phone network data to track increases in road traffic in real time. Along with the growth in ‘connected cars’ – which transmit data on their movements and satnav destination – this will soon provide transport managers with enhanced tools to predict and respond to the formation of traffic jams in real-time.
Knowing the purpose of the customer journey is a more challenging issue but one that is of importance to address in order to manage demand both optimally and equitably. A family of four travelling on holiday with a car full of luggage are unlikely to change mode of travel; however an individual travelling for a business meeting is potentially more likely if he/she has relative certainty of not missing that meeting. The problem lies in collecting this data and, currently, most
82 The CharTered InsTITuTe of LogIsTICs & TransporT
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