Connected vehicle data is transforming traffic management by providing unprecedented insights into understanding road network behaviour. GHD market leader for digital Theresa Wells says it is only now starting to be used in Auckland.
She says: “Every car manufactured since 2019 has a chip that records almost everything happening in the vehicle. Car manufacturers use this chip to track data such as your speed, when you brake, how harshly you brake, how much you accelerate, and how aggressively you accelerate. It can also record details like the air temperature inside the car and whether the radio was on.”
Carmakers use the data to improve the performance and safety of vehicles. Fleet management organisations like Eroad and Smartrak install similar technology in freight vehicles. When these sources of information are combined, planners have a more complete view of where vehicles are on the roads.
This contrasts with the old way of collecting vehicle data. Wells says: “In the past we would go out and collect the data, you would see people standing on the side of the road counting vehicles. And you’ve probably driven over the black tubes on the road. These are also used to collect data. They can tell whether a vehicle is heavy freight, a bus, car or motorbike. Sometimes they can even detect cyclists. The tubes were put out for maybe two weeks. We were making decisions based on two weeks of the year.”
With the connected vehicle data, Wells and her colleagues can measure what traffic is doing at all times of the year and all times of the day everywhere.
The data doesn’t include every vehicle on the roads. Much of the road fleet is older than 2019. Wells says the average vintage of vehicles in Auckland is around 2014.
“But if you think ahead, in five years the data will cover most vehicles and, in a decade, it will include almost everything.”
Planners and traffic managers are already able to plug in to digital data derived from mobile phones and GPS products like TomTom, but that’s aggregated. Wells says connected vehicle data is much more granular. With, say, Google Maps, planners can see the average speed of traffic on a busy road, but that might include slow-moving cars inching forward and buses whizzing down the transit lane. With connected vehicle data, you get a more complete picture.
“It takes a reading every two metres or every five sectors. With that level of detail our transport engineers know so much more about what is happening.”
Insurance companies and car makers can use the data to understand how their individual customers drive. GHD’s traffic planners get completely anonymised data. “Anything that can be used to identify a car and its driver is wiped, including the place where a journey starts and its ...
destination. Crash data is also wiped. The only way this data set can be successful is if there is total privacy and anonymisation.”
This means traffic engineers and planners can immediately see the effectiveness of safety treatments. “When we reduce speed limits on a road or install a speed camera, we can take a before and after view of what happens. Did the reduction have the desired effect? Did it have the desired effect all along the road or do people slow down then speed up again?
“We know people don’t like speed humps, but we can see whether they are effective. The same with safe speed zones in heavily populated urban centres, near schools or near shops. We know people speed everywhere, but what we care about is whether people slow down from excessive speeds in the areas of highest risk.”
When it comes to improving road safety GHD’s traffic engineers are finding new ways to understand the data. “Now we’re no longer looking at those tubes on the road, which drivers slow down to go over anyway because they can see them.”
Wells says that’s why connected vehicle data is beautiful: “Nobody knows they’re being recorded. It’s capturing real driver behaviour, not what they do when they think someone is watching.”
When captured the data is used in a variety of ways. Wells says it offers many options to improve the way traffic flows through a network, it can be used to make far better decisions about what a traffic network might need to look like in the future.
She says there is so much data that engineers are still exploring possibilities. “It may be used eventually for real-time decision making like deciding when to change traffic lights or the signals used on motorway on-ramps, but for now the focus is on making longer-term changes to the road network, its layout and interventions. We can also work through different scenarios.”
One case looked at what happened when speed humps were installed in an urban centre. Engineers could immediately see where the safety interventions were because they could see vehicle speeds drop off, then speed up.
“We knew drivers would decelerate and accelerate, but for the first time engineers could see that the acceleration and deceleration was rapid and that tells us there’s a carbon emission impact.
“When you put your foot down you burn fuel less efficiently. While the humps work well for safety and speed control, they may not be ideal from other perspectives”.
The improved granularity of connected vehicle data means engineers can get a better understanding of the effectiveness of speed cameras.
There is something traffic engineers call a halo effect, that is, drivers will slow down for a camera, but they will stay slow for a distance beyond the camera before accelerating. Wells says the data can help engineers optimise where they place speed-calming tools like cameras to get the most value from the spending.
Another application is getting the best heavy goods vehicles using freight routes. “You want to keep large trucks moving freely, which is good for the economy, we need to keep freight routes congestion-free, but do we know where those trucks need to travel?
“With better data, engineers can optimise routes and identify where new freight roads may be needed”.
