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Big data is often talked about in the abstract. We can now collect huge numbers and apply clever algorithms, so we think the answers must always be better and can be taken straight from the new technology. But the devil is in the detail.

With data collection and algorithms running on auto pilot, they can end up averaging a huge quantity of measurements down to a few numbers. Errors and unwanted information can be buried within a mass of records. Big data sets, make it easier to force a correlation that isn’t necessarily accurate.


One of the biggest changes for traffic engineers and transport planners (and many other walks of life) in the last decade has been the enormous increase in the amount, nature and availability of data which includes a wealth of data coming from non-traditional sources.


After reading this chapter, you should be able to: recognise the need for traffic surveys; become familiar with characteristics of significant traffic survey types; recognise the strengths and weaknesses of common survey methods and technologies.


Wisdom in the traffic planning and management sense should be something that gives insight and fosters processes that lead to the best community benefits, not just give an answer to satisfy a short-term need.