Our cars are becoming smarter: under the hood, scores of processors manage hundreds of actuators and sensors; tens of millions of lines of software code vigilantly scan, keeping everything running smoothly. Ubiquitous cellphone links, streaming satellite media, and advanced navigation services mean drivers are almost as connected on the go as they are at home.
These onboard technologies have improved cars’ reliability and performance, and made them safer too. Anti-roll-over and anti-lock braking systems, for instance, have avoided tens of thousands of fatalities.
The next frontier of automotive intelligence, however, is shifting beyond the car. Together, cities and OEMs around the world are beginning to experiment with advanced, interactive systems that help drivers commute more safely, quicker, and with less congestion than before.
The first stages of this transformation are taking shape via mobile apps. Digital map makers are in a race to advance the quality of real-time traffic mapping, to help commuters see and avoid congestion before they hit it. San Francisco is one of a growing number of cities that has begun to add wireless sensors to its curbside parking spots to help cut congestion. Via a smart phone app, drivers can quickly locate empty spots, see what they’ll cost, and go straight there, rather than cruise aimlessly.
From these early efforts, automotive engineers, data mavens and urban planners are beginning to recognise that cities have a vital role to play. By tapping into the growing flow of data streaming from cars, cities are learning they can cut congestion and improve road safety.
Eindhoven is a mid-sized city in the south of the Netherlands where city planners are increasingly concerned about the impact of congestion on the convoys of container trucks that flow from Rotterdam, Europe’s largest port, through Eindhoven to Germany and the rest of Europe.
Responding to this anxiety, regional planners turned to mobile technology to collect and analyse the digital performance data from a fleet of test vehicles. The data the system is harvesting is of a humble sort: it includes the countless status signals that pulse through a modern car’s operating system, including everything from the use of hazard lights, to the deployment of anti-skid braking systems. Normally, this data is of interest only to mechanics that hook into data ports. But, by collecting a steady stream of this information in real time, scrubbing it of private information, and analysing it for trends, Eindhoven is learning how to better orchestrate city traffic.
Two years ago, Eindhoven started working with IBM and NXP Semiconductors to wirelessly relay anonymised vehicle performance indicators from about 200 vehicles to a data centre. For a six month trial, some 1.8 billion bits of data were collected from the test fleet, divining trends about road conditions.
A spike in the number of cars deploying their anti-skid systems in a given location on a chilly morning, for example, identified a spot of black ice. A surge of signals of cars turning on their fog lights, likewise, was an early indicator of dangerously low visibility. All in, the system recognised 48,000 such incidents.
But while this use of data is all well and good, the next step is for cities to begin using it proactively to prevent congestion and improve safety. For example, Eindhoven is developing workflows to detect potholes remotely, by tracking signals from cars’ suspension monitoring systems. The city has also successfully tested scenarios where, given a sudden stoppage of many cars at once, authorities can proactively signal inbound drivers’ navigation systems to lower their speed and re-route to avoid the congestion.
The automotive industry has been wildly successful at advancing the intelligence of its vehicles from the inside out and we can now start attacking these problems from the outside in. By developing technologies, standards and applications, OEM and city planners have an even bigger potential to help traffic flow more smoothly and safely.
Kal Gyimesi and Eric-Mark Huitema, IBM
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