Smart city solutions to traffic jams

As the Government makes a transport announcement aimed at easing congestion in Auckland with light rail, Farah Hancock looks into what role technology can play in managing road traffic

Smart city technology could be the key to squeezing efficiency out of Auckland’s clogged roads.

With land for new roads hard to secure, a 10-year draft transport plan is emphasising the need to make existing roads as efficient as possible.

Improving traffic light coordination and introducing congestion charging are some of the technology-focused solutions in Auckland Transport’s draft Regional Transport Plan.

Auckland’s traffic lights already react to real-time data. Overseas systems operating in smart cities take this one step further, using artificial intelligence to analyse large amounts of data to predict traffic and avert traffic jams before they happen.

The draft plan does not go as far as suggesting a smart city approach for Auckland, but it does include $180 million dedicated to network performance. Items listed include the synchronisation of traffic signals and “BIG DATA real-time multi modal network performance and congestion monitoring system”. 

Auckland Transport spokesperson, Mark Hannan, said this covers a range of technologies including big data, machine learning and artificial intelligence used to manage the transport network and respond in real time. 

"We are also working to better predict when issues will occur based on conditions (like weather) and historical analysis of data."

Auckland’s traffic lights

Auckland’s traffic management system operates with a mix of automated tools and people-making decisions. It can’t predict traffic jams yet, but it does automatically adjust lights for some situations.

Data comes from sensor pads at intersections and on motorways, cameras, and GPS signals from buses.

Auckland Transport’s city centre network operations team leader, Mitchell Tse, said the Sydney Coordinated Adaptive Traffic System (SCATS) used by Auckland Transport tries to even out traffic at intersections to avoid backlogs.

“It’s constantly counting. Every time a car goes past the sensor it will calculate how many vehicles went and compare that with all the other approaches. If one approach has more traffic than the other it will say, ‘Hey, I need more time’ and take some time away from the approach that doesn’t have as many cars.”

The system is also able to give buses running behind schedule a green light in key bus corridors.

“Where certain parameters are met, if the bus is running late, we track the bus through GPS, it will send a message back through the system and say, ‘Service 104 is two minutes late’ it approaches the intersection and it will identify this bus is running late. It will bring the phase forward to get the bus through, or if it’s already green, we’ll hold that phase for the bus to come through the intersection.”

The same SCATS system is used to drip-feed vehicles onto motorways where on-ramps have signals.

When accidents happen, Auckland Transport’s operations centre are alerted by monitoring police radio, and CCTV cameras which monitor key roads.

“In the event of an incident, a crash, a fire callout, or even just a breakdown, we are able to manage the signals, or adjust the phasing to suit,” said Tse.

If detours are needed, the operations centre will adjust traffic signal phasing to manage the load the diversion creates.

The draft transport plan mentions a trial of “infrastructure to vehicle communications” which could mean that in the future drivers of passenger and commercial vehicles could be notified of incidents or congestion on their routes.

Lessons from abroad

In China, the unlikely saviour for the city of Hangzhou’s congestion has been provided by Alibaba, China’s super-sized version of Trade Me.

Alibaba has branched into cloud computing and with the ability to crunch enormous amounts of data has created an artificial intelligence system called City Brain which automates traffic management.

Since City Brain was implemented in Hangzhou 18 months ago, the average car speed during journeys has increased by 11 percent.

With hundreds of thousands of cameras throughout the city the system is able to predict traffic flows 10 minutes ahead of time. It adjusts traffic lights patterns to even out congestion and can send text messages to drivers suggesting they use a different route.

Accidents and breakdowns are responded to and cleared more quickly, enabling traffic to keep flowing.

The system, aimed at improving life for Hangzhou’s nine million residents, has been so successful it has been bought by Macau and Malaysia, which plans to implement it in its capital Kuala Lumpur.

Alibaba is not the only brand making a foray into city management.

Huawei’s smart city product, Nervous System, is soon to be implemented in Duisburg, Germany to manage IT infrastructure including traffic. In the United States, Dallas has selected Ericsson to install their Connected Urban Transport product.

Google too, is entering the smart city market but in a different way.

Sidewalk Labs is designing 12 acres of Toronto’s waterfront from scratch. Named Quayside, the future city's vision document includes mention of autonomous transit shuttles, bikeshare stations and heated sidewalks to make walking and cycling in icy weather safer.

Congestion management in the city is not expected to be an issue. Built “from the internet up”, entire areas of Quayside will be closed to passenger vehicles.

Public submissions on the draft Regional Land Transport Plan are open until May 14.

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