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Image: Ford

Taking part in the research were 160 Ford Transit light commercial vehicles, driven and operated in different sectors and by different businesses, from owner-operators to large fleets, plus a fleet of private Fiesta superminis. Over the course of the year – and over 15,000 days of usage between them – these vehicles covered over one million kilometres in and around London; they were fitted with tracking devices to monitor and record location, acceleration, braking, and deployment of hazard warning lights, and delivered a reported 500 million data points.

The data was uploaded to the cloud and sent to Ford’s global data insight and analytics team, who then cross-referenced it against historic accident reports. This enabled the construction of an algorithm to predict the likelihood of future accidents occurring on particular roads or at certain junctions or intersections. Factors such as speed, revs per minute and harshness of braking – i.e. indicating ‘near miss’ scenarios – were considered.

Jon Scott, project lead at City Data Solutions, Ford Smart Mobility Europe, explained that the creation of risk profiles on the road network could “allow a city to proactively identify [areas of risk] and take action to improve road safety for residents and road users… Even very small changes could make a big difference ­– maybe cutting back a tree that has obscured a road sign – whether in terms of traffic flow, road safety or efficiency.”

Benefits for flow, EV charging, modal choice and metrics

FORDCITYDATA_Smart-300x212 Image: Ford

The data collected also yielded valuable insight on how rush-hour traffic congestion could be reduced. The analysis found that by setting out two hours earlier, one of the test fleets of vans could save up to 30 hours in a typical week; and if commercial drivers set out a further 30 minutes earlier, their time saved actually doubled – a reduction of time spent in traffic of up to 60 hours per week. The data team thus created a way to calculate a ‘social benefit’ score for time-shifting of journeys.

“London is a 24-hour city,” said Scott. “We wanted to see if we could use the capital’s roads around the clock to reduce the social and economic impacts of peak-period traffic.”

Although the vehicles in the study were not electric, their mileage, movements and downtime recorded showed where their EV equivalents might best be charged. An eight-month focus on vehicles in the construction industry analysed where they stopped throughout their day, and for how long. The vehicle location and timing data was overlaid with mapping, and the analysis found that where the vehicles stopped the longest, there were no nearby charging points, and very few stops within 100m of existing facilities were for long enough to get a useful top-up. However, the researchers concluded that EV operation across Greater London could be “significantly improved” by installing just 20 rapid-chargers – in the right strategic positions.

The data also helped show which journeys could be quicker if undertaken by other means, whether by public transport, bicycle or walking. The data gathered from the Fiesta fleet was compared to public transport timetables, and an app and heatmap visualisation created. The analysis identified that around 20pc of journeys driven around London could have been quicker by public transport, with distinct spatial patterns: short journeys in the centre of the city and to the east were generally quicker by car, but in well-connected outer areas, public transport was faster.

It also contradicted the popular belief that London’s roads are quieter during the summer and school holidays: while traffic congestion was clearly eased on some roads around schools, other roads saw heightened traffic. This was analysed by comparing speed limits with actual speeds travelled. Roads generally flowed more quickly at lunchtime, but patterns were variable. “Using this vehicle data, we believe it’s possible to accurately monitor and measure traffic flow and provide the city with an opportunity to optimise traffic metrics to identify critical hotspots and target congestion-reduction actions,” said Scott.

Sarah-Jayne Williams, director, Ford Smart Mobility, Ford of Europe, concluded: “The Ford City Data Report is a showcase of what we at Ford can do with connected vehicle data, smart infrastructure, and our analytical capabilities. We are calling on cities to work with us to collectively solve problems…

“This exercise is merely a snapshot of what is possible – imagine the insights that cities could benefit from with the availability of further data from a variety of vehicle types. We are moving into a new decade, one in which 5G, the Internet of Things, vehicle-to-vehicle communications and artificial intelligence will be ubiquitous in all of our lives. It is up to trusted companies – like Ford – to leverage these technologies so we can understand our world and optimise how we can move within it.”