Vehicle Onboard Analytics and Road Perception
Digital magic or where the rubber meets the road
Quite literally, where the rubber meets the road is a critical spot for safe mobility. But with smart sensor fusion and cloud-based connectivity services, there is huge potential to increase safety without adding expensive, error-prone hardware to tomorrow’s vehicles.
Let us consider a typical vehicle user in the mobility landscape of tomorrow.
Figure 1. Drivers very often fail to focus on the details of the tire and wheel, which can lead to safety issues that should not be ignored. As technology evolves and cars become more and more autonomous, even less focus will be on the car.
Before starting her journey, our driver will of course check the tire pressure on all four wheels. Or will she? Most car owners fail to do this.
Correct tire pressure is not only a matter of lower fuel consumption and CO2 emission, but also important for personal safety as various investigations have shown . For these reasons, tire pressure monitoring is already a legal requirement in the US, the EU and China just to name the three largest markets . Future mobility scenarios, with ridesharing and ADAS, make it even more important to assist the vehicle user as well as the fleet owner with low-pressure warnings. So-called direct systems, using a sensor in each tire with a wireless connection to a receiver in the vehicle, have proven to be expensive for the end-user to maintain and replace when failure occurs, or batteries finally die.
By using a system for tire grip indication, the driver can receive a warning as they are passing over a slippery area. If the service is connected drivers can also get a warning before they enter the hazardous area, meaning speed can be reduced even before the slippery spots.
Using friction data together with an ACC will allow dynamic setting of the distance to the vehicle in front. When the road is slippery, the distance to other vehicles will increase. When the grip is good, the distance can be decreased. Using friction data together with an AEB will greatly increase safety. The distance to other vehicles will be dynamic, increasing safety and saving lives. Today, if a road is slippery, cars are not taking that into account when starting an automatic brake. It is likely that the braking will begin too late. For the cars of the future, with TGI data, this can reduce the numbers of crashes.
Road Surface Information continuously sends vital road information to vehicles – such as a road roughness and friction, as well as road surface alerts. The data is gathered by millions of regular passenger vehicles where our algorithms are smartly fusing anonymized information from existing sensors in the car.
While the data gathered using RSI can be vital to the driver of the car in question (or the car itself), the real benefits come from using RSI in a connected vehicle cloud. Millions of cars are collecting vital road information in real-time – providing a descriptive or even predictive map layer of any road segment.
We mentioned hazards before but having insights into road roughness or potholes can avoid damage to the suspension, wheels, or other parts of the vehicle. Car damage is one thing, but poor roads lead to many accidents that could have been avoided if the driver had been aware.
In 2021, over 1.7 Million connected vehicles are monitoring the road surface continuously, and the number keeps growing every day. This means more and more advanced functions can be developed, increasing the safety on roads everywhere. For the cars of the future, having insights on the road surface will be necessary to decide when autonomous functions are turned on or off.
Our driver got home safely despite the slippery road. But in the background, the fleet owner received a report that the vehicle was probably equipped with summer tires, and a reminder to check the tread wear.
When using a carpool vehicle, do you know that the vehicle is in good condition, or do you just blindly expect the vehicle to be safe? As car sharing is becoming a more natural part of our lives, we also need to put more faith in others or check every time before going for a ride. Would you notice if the tires are unsuitable for the season? Or would you recognize if the tread wear is getting so low that it could be a danger.? With a system that recognizes and warns if the tires are in bad shape or unsuitable for the weather, you get extra security and peace of mind. This is also useful for fleet owners who want to keep their fleet in best condition, without overdoing it. Tire Insights is expected to be a valuable contributor to the NIRA product portfolio within the upcoming years.
Prompted by the Tire Insight reminder, the fleet owner changes to winter tires before our driver’s next trip. The bolts on one of the wheels have not been sufficiently fastened, and our driver hears a strange noise. Or does she? Listening to music and playing phone games while trusting the ADAS system, she might be less likely to notice how the vehicle behaves on the road. If she knows how this vehicle model is supposed to “sound” at all, what is normal and what is not.
Luckily the Loose wheel Indicator gives an immediate warning, and our driver can get the bolts fastened well before she is in any real danger.
With autonomous vehicles and car sharing there is a risk that the knowledge about the specific vehicle as well as focus on driving is slowly shifting. By shifting focus there will be a higher risk of missing out what is happening and discover small mis sounds. Loose Wheel Indicator is an in-vehicle software algorithm that alerts the driver before a loose wheel risks damaging the vehicle or becoming a hazard for someone else. An alarm is issued within minutes – leaving plenty of time for the driver to safely stop the vehicle.
Loose wheels most often originate from improperly torqued bolts. When not properly torqued the bolts may start to rotate and unscrew themselves. This may lead to damaged rims -or even worse, a detached wheel if not noticed in time. The loose wheel indicator uses analysis of the wheel speed signals to detect loose wheels. In case of a loose wheel certain frequencies will be amplified and can be tracked by the algorithm. By comparing frequencies that get affected by loose wheels to non-affected frequencies, the output gets normalized which makes it easy to adjust to different fleets. Until now the algorithm has been activated in 650 thousand vehicles, and thus far it has been compatible with all rims and tires applied.
Here, we will leave our imaginary future friend, who has safely reached her chosen destination. This was a story from the future, but where are we today?
As a matter of fact, most of these functions exist already. This is not a far-fetched scenario, but very likely to be your experience within a few years or less.
Director NIRA Dynamics AB
Sources & References:
 TNS Sifo Consumer Study on Tire Pressure Maintenance and TPMS among vehicle owners and vehicle maintenance responsibles, Sweden 2012, n=1003
 https://www.nhtsa.gov/sites/nhtsa.gov/files/fmvss/TPMSfinalrule.pdf, https://www.nhtsa.gov/sites/nhtsa.gov/files/fmvss/TPMS-2005-FMVSS-No138.pdf , https://unece.org/DAM/trans/doc/2008/wp29grrf/TPM-02-02e.pdf
 FMVSS 138 (http://federal.elaws.us/cfr/49CFR571.138); UN R141 (https://unece.org/transport/vehicle-regulations-wp29/standards/addenda-1958-agreement-regulations-141-160); GB 26149-2017 Cat. II