Stellantis Investigating Multi-access Edge Computing for Use in Future Vehicles
In the future, drivers of Stellantis vehicles could employ technology that reacts far more quickly than current driver-assist systems thanks to the use of Multi-access Edge Computing, or MEC.
For Stellantis, MEC could collect data from red light or speed cameras to notify the driver about what they can’t see, such as upcoming driving hazards, pedestrians or approaching emergency vehicles. Such notifications are a result of Stellantis engineers working with HAAS Alert’s Safety Cloud, a digital warning system that triggers when an emergency vehicle activates their lights. The alert would come through the vehicle’s Uconnect system.
“Improved hardware and expanded software expertise have opened new opportunities for Stellantis with safety systems being one of the many areas we focus on,” said Mamatha Chamarthi, head of Software Business and Product Management, in a statement.
Read the article at The Detroit Bureau.
The Chevy Bolt Recall is Burning Up What’s Left of GM’s EV Good Will
General Motors plans to launch 30 new electric vehicles by 2025, and aspires to sell only zero-emissions vehicles by 2035. But through bad politics, bad investments, and now most notably, a massive recall of the all-electric Bolt - thanks to around a dozen reported fires - the advantage once held, has been squandered.
The Bolt’s production shutdown has been extended until mid-October, due to the lack of LG replacement batteries. GM has recalled all Bolts made to date — nearly 150,000.
In the meantime, GM gave Bolt owners something else to worry about this week, as it advised them to park at least 50 feet away from other vehicles. That’s in addition to the previous guidance owners have received, including parking away from their homes, not charging overnight, not charging above 90 percent, or letting their vehicle’s battery drain below around 70 miles of range.
Read the article at The Verge.
Smarter In-Car Cameras Can Detect Every Dumb Thing You’re Doing While Driving
Several automakers offer features where a camera inside a vehicle monitors the driver and sets off alerts when it detects them starting to fall asleep. Researchers have developed an even smarter in-car camera system that can figure out exactly what a driver is doing, potentially improving the safety of semi-autonomous driving features.
The new system uses AI-powered image recognition to construct a digital skeleton of the driver that provides enough details for the system to interpret what exactly the driver is doing, while additional object recognition keeps tabs on the location of items like smartphones or coffee cups.
When the two systems are paired, a vehicle is able to determine if a driver is paying attention to the road, or distracted with other activities like texting, eating, or even interacting with other passengers in the vehicle. By keeping tabs on what the driver is doing, a semi-autonomous driving system can determine how distracted they are, and potentially how long it will take them to return their focus to driving, and take that into account before handing control of the vehicle back to them.
Read the article at MSN.
Electric Robotaxis Might Not Provide the Greener Travel Everybody Expects
Despite the emissions problems all-electric robotaxis they might solve, new research suggests electrified self-driving fleets could, at least in some cases, exacerbate pollution problems.
An analysis found ride-hailing services cause 69 percent more pollution than the trips they replace, largely because of “deadheading” miles that accumulate when vehicles drive around without passengers.
“Automated vehicles can be part of a clean, equitable transportation system as long as they are run on zero-emission electricity, lead to widespread pooling of trips and are deployed in coordination with frequent, reliable and accessible mass transit,” Elizabeth Irvin, a senior transportation analyst with the Union of Concerned Scientists, wrote in support of California Senate Bill 500.
Read the article at The Car Gossip.
Using Data to Reduce Driver Risk
FMW Editorial Staff
In order to reduce driver risk and help drivers change behavior, look at the information that's coming in.
And, these days, the more data, the better! Motor vehicle violations and license-checking information. Past crash and collision incident information. And, especially, telematics. Combined and normalized, the aggregate data provides terrific insight into risk.
Only after data is collected and the picture fully formed, can a potent action plan be developed. that targets drivers, departments, or the organization.
A focused approach is more efficient because a company can reduce broad-based training to drivers that they may or may not need. Finally, the personalized approach is more successful in rectifying a specific driver performance or behavioral problem.
At the driver level, an action plan can address training. At the departmental or enterprise levels, issues such as culture, scheduling, or job performance metrics can be addressed.
