Volume, velocity, variety, variability, veracity… These words can only be describing one thing – the dimensions of Big Data. The prospect of using Big Data is intriguing and innovative as it offers previously unimaginable advantages in comparison to traditional data sources. Like the Internet, Big Data is another game changer that will revolutionise the way businesses and society operates. Continuous advances in Big Data architecture and technology have increased the potential for businesses and governments to analyse their data, and to use actionable insight to make informed decisions.
Big Data is being used by public agencies and consultancies to answer numerous transportation questions. In addition to estimating origins, destinations and routing patterns, such as where vehicles join and exit roads, the high degree of spatial and temporal accuracy of some data sources makes it possible to precisely pinpoint the location of vehicles. As such, real-time data can be used for incident detection, queue monitoring, congestion alerts, routeing, and planning and performance measurement.
Off-the-shelf and custom products for Big Data offer excellent tools to compare traffic patterns and conditions on roads or geographical areas for road planning and analysis of improvement schemes. Different data sources can also be combined providing invaluable information for transport planners, for example, the ability to assess the level of risk posed by the incursion of HGVs into cycle routes.
Securely stored and correctly understood, Big Data is a treasure trove that can improve day-to-day customer experience and business needs. But with such an enormous amount of data pouring into organisations, the question arises of how to present Big Data in a way that decision makers can understand. Although the promises and possibilities of Big Data are evident, the challenge is extracting the right information, for a reasonable cost and in an appropriate timescale.
As good as it seems, can Big Data succeed as a wholesale replacement of traditional methods in transport planning and operation? Our current challenge is to integrate Big Data analysis into traditional systems in real time, for example to set and adjust thresholds and tolerances to reflect behaviour. In the future we need to see how we can better use Big Data in a cost-efficient manner to prime and monitor operational systems with significant learning capability for operating and managing our transport networks. This will help the systems become far more agile and responsive to changing conditions and be much better at optimising the results.
A lot of work still needs to be done to realise the potential of Big Data; there is no one-size fits all approach to its application and use. Careful consideration needs to be given to which data-sets can be used and how to derive the information sought.
This blog is co-authored by Arcadis’ Olga Feldman and David Threlfall. Olga is the consultant’s big data and land use analytics director, David is its innovative highways technology director. The pair will be expanding on these ideas in an industry briefing session on 16 November, part of the extensive free-to-attend fringe programme at this year’s Highways UK
Olga Feldman and David Threlfall – Directors of Big Data, land use analytics and innovative highways technologies, Arcadis