A collaboration with a UK Infrastructure Provider and KPMG
Ensuring high levels of customer satisfaction on the UK road network is a key strategic challenge for this client. Using journey time as a proxy for customer satisfaction, the Data Spark team were challenged to characterise different incident types and the effects these may have upon journey times.
How did we help:
In this pilot study, the team focussed on 12 moths of data for one stretch of a UK motorway, the team categorised each incident and determined the effect particular types of incidents had upon journey time both during and outside of rush hour.
- Incidents are highest cause of journey time delays, this is followed by rush hour, sporting events, and the dark
- Apart from traffic collisions, all other types of incidents tend to have a greater impact on increasing journey time during non-rush hour than rush hour
- During rush hour, congestion was found up to on average 3 km upstream of the incidents. During non-rush hour, congestion was found up to on average 4 km upstream.
"The Data Spark programme was really beneficial for us and we have learnt a lot. The joint KPMG and Imperial team challenged our existing data sets and developed new insight, we hadn’t previously considered. This refreshing approach is something which we will be looking to explore further as we work through the outputs from the Data Spark programme."
Senior Customer Insight Manager