AUTONEWS

Why pedestrian deaths keep rising: AI spots rare crash patterns where targeted fixes could save lives

On average, car crashes cause more than 40,000 deaths per year in the United States. Technologies like seat belts, advanced airbags, and automated braking systems have improved car driver and passenger safety, but pedestrian deaths due to crashes have actually increased by 48% over the last decade, reaching about 7,500 fatalities in 2022. Transportation researchers comb through police crash reports to identify infrastructure countermeasures that will help in the greatest number of cases. However, sometimes improving the average situation isn't enough.

"By using traditional analysis methods that focus on the average, most studies on pedestrian safety overlook crashes that are rarer but may cause disproportionately high-risk injuries," said Zeinab Bayati, a Ph.D. student in the Department of Civil and Environmental Engineering (CEE) at the University of Tennessee, Knoxville.

The most common pedestrian crashes occur during the day and at intersections, but such crashes also usually result in comparatively minor injuries. High-risk injury scenarios—those in which pedestrians are much more likely to be seriously injured or killed—are less common but still vital to consider, said Bayati's doctoral advisor, CEE Beaman Professor Asad Khattak.

"Let's say it's nighttime, there's torrential rain, and maybe the pedestrian and the person who is driving are both under the influence of alcohol," said Khattak. "Those kinds of situations result in more dangerous crashes, but they are so far outside the average that researchers might even remove them from the data set as outliers to make the general trends clearer."

Using AI methods, Bayati and Khattak have developed a novel framework that analyzes pedestrian crash data and sorts events into meaningful groups. Their research, published in the journal Accident Analysis and Prevention, reveals that safety measures aimed at the most common crashes might not save the most lives.

"We identified that the rare cases are indeed the more fatal cases," Bayati said. "That is very important. We want to see what's going on behind this pattern."

AI reveals commonalities in outliers...Bayati and Khattak used an unsupervised clustering algorithm to analyze the factors involved in more than 10,000 police-reported pedestrian crashes. Each report includes detailed information like the speed limit, lighting conditions, road surface conditions, and pedestrian position at the time of the crash.

They then directed the AI to divide the crashes into three categories relating to their distance from the core, or the cluster of "average" scenarios. While only 8% of core cases were fatal, nearly 37% of cases in the furthest edge category involved fatalities.

Analyzing the factors involved in those life-threatening "outlier" crashes reveals the types of interventions that may be most effective at saving pedestrian lives.

"You can check the history of different locations and look for trends that lead to most crashes there," Bayati explained. "We have had a lot of crashes that happened on road shoulders, so we can consider installing sidewalks, speed bumps, or crosswalks in those locations to give pedestrians the opportunity to walk in safety."

Strategic interventions save lives...Part of what makes the edge cases so dangerous—and so rare—is that they occur when many risky factors coincide. That also means it is harder to design interventions against them.

For example, installing a sidewalk along an unlit stretch of a rural roadway will only make it safer during the day. Darkness was a common factor in the highest-risk crashes Bayati and Khattak analyzed, indicating that installing lighting with a sidewalk would lead to an even greater increase in safety.

These complex and rare scenarios can also be used to improve autonomous vehicle safety by exposing failure modes unlikely to appear in routine driving data. Autonomous cars need to be able to reliably sense pedestrians on the road shoulder even in darkness, for example.

"Nighttime crashes or freeway crashes require a lot of different kinds of countermeasures that are harder to implement," said Khattak. "That might be another reason why safety improvements tend to focus on the most prevalent problems, like at urban intersections."

Bayati hopes that this study will create a better understanding of how pedestrian risk is distributed across a transportation system and result in more impactful safety interventions.

"Pedestrian safety is a very important topic. It affects everyone," she said. "I would be happy to have even a small role in creating a safer transportation system."

AI identifies rare flaws by detecting subtle deviations in large volumes of data that would go unnoticed by human experts. In critical areas such as healthcare and engineering, this technology allows for targeted corrections before problems become fatal. Methods for Identifying Rare Faults To find these "invisible" patterns, AI uses specific approaches:

Anomaly detection (Unsupervised Learning): Algorithms such as Isolation Forest isolate data points that deviate significantly from the norm without needing previous examples of failure. This is vital for detecting new or ultra-rare defects.

Transfer learning: Because data on rare flaws is scarce, models are first trained on large, common datasets and then fine-tuned to recognize the specific signals of rare conditions.

Increased synthetic data: Generative models create "fictitious but realistic" data to expand small datasets, allowing AI to learn failure patterns that rarely occur in real life.

Challenges and the "human factor"...Despite its accuracy, AI in high-risk environments requires human oversight. The opacity of some models ("black boxes") can lead to mistrust or error if the doctor or engineer does not understand the logic behind an alert. Therefore, the use of explainable AI (XAI) is essential for experts to validate machine suggestions before acting.

Provided by University of Tennessee at Knoxville

AUTONEWS

See why Felipe Massa's LaFerrari is no ordinary LaFerrari

Although Felipe Massa never won a Formula 1 World Championship with Ferrari (despite briefly believing he would in 2008), his time with the Scuderia left an indelible mark on Maranello. This affection was even reflected in one of his road cars, the Ferrari LaFerrari he bought during his last year in Italy.

Massa – as is typical of Ferrari drivers – didn't miss the opportunity to get his hands on one of the 499 units of the pinnacle of the Italian brand's sports car range at the time, the LaFerrari. He requested it during his last season at Ferrari and the car was delivered to him during his time at Williams, with a message inside: "Grazie Felipe" (Thank you, Felipe).

It was a thoughtful gesture from Luca Cordero di Montezemolo himself, one of his biggest supporters, who kept him on the team for eight seasons, even though the Brazilian was almost always overshadowed by his teammates, especially Michael Schumacher, Kimi Raikkonen, and Fernando Alonso. The team boss wanted to leave this message for his protégé on a plaque located between the seats, as a sign of respect.

Although he didn't win a title, Massa took home a beautiful souvenir from Italy: his personalized LaFerrari. He didn't opt ​​for the Corsa red paint for the body (although he used it in some details, such as the front splitter, side skirts, mirror supports, and brake calipers), but rather for black (including the Alcantara interior). The wheels are FXX-K, an option available only at Ferrari Atelier, and the front and rear diffusers are made of carbon fiber.

The LaFerrari was a sufficiently advanced car and, of course, with performance that met the needs of a Formula 1 driver (top speed exceeding 350 km/h and acceleration from 0 to 100 km/h in less than 3 seconds).

It was one of Maranello's first hybrids, combining an 800-horsepower V12 engine with an additional 163-horsepower electric motor. Although it didn't exactly qualify as a hypercar (more than 1,000 horsepower), the LaFerrari was a worthy representative of Ferrari against the Porsche 918 Spyder or the McLaren P1.

The Brazilian kept the car for seven years and drove 3,000 of the nearly 4,000 kilometers now on the odometer. Its next owner, a client residing in Denmark, is now auctioning the vehicle through RM Sotheby's, to the delight of a wealthy collector... probably a Formula 1 fan.

Its third owner will also be able to boast the signature of its illustrious original owner. This, coupled with the natural appreciation of one of the jewels of Ferrari's recent history, leads the company to expect an offer between 4.5 and 5 million euros for this supercar.

That's practically triple the price of one and a half million for which it was put up for sale in Spain.

Watch the video below of Felipe Massa driving his LaFerrari(Monaco license plate: MC3223) through the streets of Monaco back when he was still a Williams driver.

Autonews and Mundoquatrorodas

AUTONEWS

Why electric cars have so many accidents: Statistics show a worrying trend

The sudden acceleration and abundant power are overwhelming for many drivers. That's why electric cars are involved in a particularly high number of traffic accidents. Data from the insurance company AXA from 2022 shows that drivers of electric cars cause 50 percent more collisions that result in damage to their own vehicles than owners of cars with internal combustion engines.

Namely, most electric cars, especially high-performance models, have very high torque that is available without waiting even with light pressure on the accelerator pedal. This can lead to unexpected and sudden acceleration that the driver may no longer be able to control.

The result is not only a higher number of accidents but also different types of accidents. The greatest risk of accidents with electric cars occurs during acceleration, not braking. This is particularly the case with large cars with powerful engines, which of course cost significantly more than smaller and less powerful models. As a result, the damage in an accident is also very expensive.

Crash tests conducted by the insurance company have revealed another weakness of electric cars: the undercarriage. For example, it can be easily damaged if the car accidentally drives over an obstacle. The battery is mounted above the undercarriage. Although it is very well protected by special body reinforcements, this protection is limited to the front, rear and sides, but not the underside.

The undercarriage is clearly the Achilles heel of electric cars, because the battery has no additional protection there. Drivers should be aware of this.

The insurance company is calling on car manufacturers to take measures and better protect their cars, for example with undercarriage protection panels that would prevent battery damage and major fires.

The truth is, the fear of electric car fires is far greater than the actual risk. Only five out of 10,000 electric cars catch fire. That's a rate of 0.05 percent, so the risk of damage from a mink bite, for example, is 38 times higher.

Electric vehicles are gaining rapid popularity as drivers look for environmentally friendly ways to reduce their transportation costs...In 2013, automakers sold nearly 500,00 hybrid vehicles and 100,000 electric vehicles in the United States. In the United States, new electric car registrations totalled 1.4 million in 2023, increasing by more than 40% compared to 2022.

Electric vehicles offer several benefits compared to gasoline-powered vehicles. Marketing of EVs focuses on these benefits without discussing the potential risks of the new technologies. While electric vehicles do offer benefits to drivers and passengers, as well as to surrounding community air quality, they also pose risks during a crash - risks that automakers are just beginning to understand.

EV-Related Accidents in the US and South Carolina...While electric vehicles are becoming more popular, new EV registrations still made up less than 7 percent of all new vehicle registrations at the start of 2023. In total, EVs make up about one percent of all cars on US roads.

To date, statistics on EV accident injuries and deaths indicate that these vehicles are neither significantly more nor significantly less safe than gasoline-powered vehicles. EVs do, however, have unique parts and features that make different types of accidents more common - and that make certain kinds of crashes or crash damage more dangerous. For example:

-New EV owners are three times more likely to cause a crash, partly because they aren’t used to the vehicle’s instant acceleration. 

-33 percent of all EV crashes involve cyclists and pedestrians - a rate 1.5 times higher than gas-powered vehicles. 

-Occupants of an EV have a 40 percent lower risk of injury in a crash, but the vehicle has a 50 percent higher risk of damage - indicating that the forces of the accident are pushed onto others outside the vehicle, increasing their injuries.

-Hybrid vehicles have a 3.14 percent chance of catching fire in any given crash - over twice the risk in a gasoline-powered vehicle and 100 times the risk of a fully electric vehicle. 

Some EVs on the market weigh more than twice the weight of the average passenger vehicle - weighing in at 9,000 pounds instead of the average 4,289 pounds, according to the Environmental Protection Agency (EPA).

Higher weights can mean more traffic deaths. In 2021, 42,915 people died in traffic crashes - a rise of over 10 percent from 2020 and the highest number recorded since 2005. 

Electric vehicles are 37 percent more likely to hit pedestrians than gas-powered ones unless the EV has a noisemaking device installed to alert pedestrians to its presence at low speeds. 

Adding auditory signals to quiet EVs at low speeds is expected to save 2,400 lives annually.

Recent studies and insurance data indicate a "worrying trend" of higher accident rates among electric vehicles (EVs) compared to internal combustion engine (ICE) vehicles, with some insurers reporting up to 50% more collisions among certain EV groups.This trend is generally not due to faulty technology, but rather a combination of driver behavior, vehicle physics (weight), and unique driving dynamics.Here is a breakdown of why electric cars are seeing higher accident statistics in 2026(below):

1. Instant torque and rapid acceleration

-The cause: Electric motors deliver maximum power instantaneously, unlike gasoline engines which require revs to build power.

-The result: Drivers, particularly those new to EVs, often misjudge this acceleration, leading to "sudden acceleration" accidents, specifically during starting phases and parking, says the Steinberg law firm.

-Data: A 2024 study noted that new EV owners cause crashes at three times the rate of experienced drivers.

2. High-speed potential of heavy vehicles

-The cause: EVs are significantly heavier than their conventional counterparts due to battery packs, yet they often have much higher horsepower.

-The Result: A 2026 report indicates that high-performance EVs are associated with a surge in fatal crashes, with AXA Switzerland  noting that luxury, high-powered EVs cause roughly twice as many accidents as standard cars.Increased 

-Force: The added weight means more momentum and higher forces involved in a crash, increasing the severity of injuries to others, according to the NTSB.

3. One-pedal driving and regeneration

-The cause: Many EVs utilize "one-pedal" driving, where lifting off the accelerator causes rapid deceleration to regenerate energy.

-The result: This different, often abrupt, deceleration profile can confuse following drivers, leading to a higher rate of rear-end collisions.

4. "Silent" operation and pedestrian risk

-The cause: EVs are nearly silent at low speeds, which is a particular hazard in urban settings.

-The result: Data from the National Highway Traffic Safety Administration (NHTSA)  suggests EVs are nearly 40% more likely to cause accidents involving pedestrians compared to conventional vehicles, though new noise-emitting regulations (AVAS) are being implemented to mitigate this, says Barcan and Kirby Solicitors.

5. Increased repair costs and sensitivity

-The issue: EV batteries are frequently located at the bottom of the car, making them vulnerable to damage from road debris or accidents.

-The result: Mitchell International  reports that EV collision repairs cost 20% more than conventional cars. Even minor, low-speed impacts can damage the battery, leading to high-cost claims or the car being written off entirely.

Autonews

CITROEN

Citroen Saxo VTS: The brand's compact sports car turns 30

Thirty years ago, Citroën made its mark in the world of compact sports cars with the Saxo VTS. Far from being just an urban car with a flashy emblem, it translated a clear vision: to offer enthusiasts a true 'kart for the streets' - reliable, accessible and made for fun. Three decades later, Citroën celebrates the anniversary of the small French sports car that managed to combine driving pleasure and performance within everyone's reach.

To understand the origins of the Saxo VTS, you need to go back to the AX. Launched in 1986, the AX consolidated Citroën in the compact sports car segment with the AX Sport and AX GTi versions, thanks to its precise dynamic behavior and excellent power-to-weight ratio. Introduced in February 1996, the Saxo took over the position left by the AX as the brand's entry-level model. That same year, the Saxo VTR debuted, equipped with a 1.6-liter 8-valve engine producing 90 hp. Soon after, the model destined to continue the legacy of the AX GTi arrived: the Saxo VTS, powered by the TU5J4 1.6-liter 16-valve engine, with 120 hp.

Although the general lines of the Saxo were developed by the Italian designer Donato Coco, the sports version was the responsibility of a young talent. In 1996, Gilles Vidal's first mission at Citroën was precisely to develop the visual kit for the VTS. A meticulous job, marked by widened fenders carefully integrated into the side skirts and wider bumpers. On the rear fenders, the extension goes from the wheel arch to the door cutout, sliding elegantly under the side protection trim.

The Saxo VTS knows how to hide its true nature very well. With a discreet look – marked only by the 16V emblem on the rear fenders, the chrome exhaust tip, and exclusive alloy wheels – it doesn't explicitly announce its capabilities. However, under the hood, the TU5J4 engine delivers 120 hp at 6,600 rpm, with a rev limiter at 7,300 rpm. Paired with a 5-speed manual transmission with a shorter final drive ratio and weighing only 935 kg, the VTS reaches a top speed of 205 km/h and accelerates from 0 to 100 km/h in less than 10 seconds.

But it's the chassis that truly makes the difference: the front responds with surgical precision, the power steering is well-calibrated, and the rear adopts a looser behavior, ready to slide as soon as the driver demands more from the car. On winding roads, the Saxo VTS outperforms much larger and more powerful models. Front brakes with ventilated discs complete the package of a small sports car designed for pure driving pleasure.

The Saxo VTS never rested on its laurels. At the end of 1997, a first update reorganized the sports family, and the 16-valve model once again sported the ‘16v’ emblem, previously used on the ZX. This was also the moment when Citroën expanded the VTS offering. Although the 120 hp 16v version remains the true object of desire, the sporty look and refined chassis of the VTS were now combined with more accessible engines, attracting a wider audience in search of dynamic and visually sporty performance, without necessarily prioritizing maximum performance. The VTS line then began to offer the 90 hp 1.6i engine (previously exclusive to the VTR), the 100 hp 1.6i, and even the 75 hp 1.4i.

In 1999, a significant restyling modernized the front, with almond-shaped headlights, a higher hood, and a grille with large chevrons. The VTS was updated without losing its identity. Produced until June 2003 at the Aulnay-sous-Bois factory, before giving way to the C2, the Saxo VTS ended its run after seven years of success.

As soon as it arrived on the market, the Saxo VTS proved in competitions what was already perceived in everyday use. Whether in rally, rallycross, circuit races, or even on ice, the small Citroën proved to be an extremely effective, accessible, and versatile machine.

Citroën Sport built a true competitive ecosystem around it: Saxo Cup, Saxo Challenge, Saxo Rallycross, and Saxo Glace, each with its own regulations, allowing as many drivers as possible to take their first steps in motorsport with a car developed for that purpose. Notably, these categories required the use of the production engine, demonstrating that the Saxo VTS chassis was, in itself, a true competitive weapon.

This competitive environment served as a school for an entire generation of drivers. Names like Patrick Henry, Yoann Bonato, Marc Amourette, and Pierre Llorach took their first steps in this universe before going on to much broader careers. The Saxo VTS, therefore, was not just a racing car, but also a true school of sports driving. In 2001, Sébastien Loeb and Daniel Elena won the WRC Junior world title aboard a Saxo Super 1600.

30 years later, a model that withstands the test of time...Today, the Saxo VTS has become a legitimate collector's item. Well-preserved examples are increasingly rare, and enthusiasts do not hesitate to cross France to find a model in good condition. The name Saxo VTS still appears on the entry lists of French regional rallies, proof of its extraordinary longevity in motorsport. Celebrating its 30th anniversary, Citroën pays homage to a model that, in its own way, embodied the spirit of the brand: creative, accessible, and incredibly efficient. The Saxo VTS is the story of a small car that you never thought was small.

by Autonews

AUTONEWS

The CT5-V Blackwing F1 Collector Series celebrates Cadillac’s first season in F1 with more power than ever

Cadillac is celebrating its first season in Formula 1, and this weekend marks the team’s first race on American soil at the Miami Grand Prix. To celebrate, Cadillac has launched a limited edition CT5-V Blackwing with even more power.

The CT5-V Blackwing F1 Collector Series features an upgraded supercharger developed in collaboration with GM Motorsports. This increases the power of the 6.2-liter V8 engine from 668 hp and 890 Nm to 685 hp and 910 Nm of torque.

Cadillac will offer the sports sedan exclusively with a six-speed manual transmission. Each car also comes with the Precision Package, which includes a number of upgraded suspension components, carbon-ceramic brakes and Michelin Pilot Sport Cup 2 R tires.

Each car is painted in “Midnight Stone Frost,” with Carbon Flash Metallic wheels, gloss black badging, a monochrome logo, and Harbor Gray Metallic brake calipers. The lower body features “Switchblade Silver” stripes.

The vehicle also features plenty of Formula 1 and FIA branding, including an F1 logo embossed on the lower front doors. The rear spoiler features both logos, while the FIA ​​logo adorns the sills.

Inside, the sills read “Cadillac Formula 1” and there are F1 graphics embossed on the seats. The six-speed shifter has a special F1 medallion. Under the hood, the compressor cover includes an F1 logo and a laser-engraved FIA logo.

Cadillac will begin production of the car in mid-2026, and it will be for the United States and Canada. Production is limited to just 26 examples, with a price tag of around $150,000.

Autonews

AUTONEWS

For autonomous robots, not all rules are equal

From driving cars to flying drones, as autonomous robots take on more responsibility, they also face more human-like dilemmas—including what to do when rules collide.

For a self-driving vehicle, this conundrum might pop up when a pedestrian suddenly steps off a curb and into its path. By swerving to avoid them, the car will also have to briefly veer over the road's clearly marked center line. Is this a justifiable infraction? What if it leads to a collision with an oncoming car?

Similarly, a drone might need to decide whether to fly through a narrow gap between two buildings or take the long way around to reach its destination. Neither option is perfect, but can the drone weigh the different risks that each path presents?

Tichakorn Wongpiromsarn, associate professor of computer science at Iowa State University, said these everyday scenarios reflect a growing reality: autonomous systems must make judgment calls and not just follow the rules.

"Robots are increasingly expected to operate without human intervention in situations where some rules may have to be bent," Wongpiromsarn said. "What's been missing is a principled way to justify these decisions."

This gap is what motivated Wongpiromsarn and fellow researchers Konstantin Slutsky, assistant professor of mathematics at Iowa State, and Emilio Frazzoli, professor of dynamic systems and control at ETH Zürich, to develop a new framework that helps autonomous systems make these decisions in a way that's transparent, predictable and defensible.

In a series of publications that culminated in a study published by IEEE Transactions on Robotics, Wongpiromsarn, Slutsky and Frazzoli introduce a new formal system—known as "rulebooks"—designed to help autonomous systems rank and reconcile competing goals.

Addressing common flaws...In robotics, Wongpiromsarn said there's concern around the fact that today's autonomous systems are often optimized using a single mathematical cost function that blends all goals—such as safety, legality, efficiency and passenger comfort—into one score using weighted trade-offs.

How does this work? Simply put, engineers give each of these goals a weight (or value), meaning how important that goal is relative to the other goals. A robot then calculates a total score for every possible action and picks the one with the best score.

It's an approach that works well, Wongpiromsarn said—until it doesn't.

"The problem is that this approach treats all goals as if they can be balanced against each other, even when they shouldn't be," Wongpiromsarn said.

For example, if "efficiency" is weighted too high, the robot might drive too aggressively. And while engineers can adjust the weight to make the robot behave more cautiously, that doesn't fix the underlying problem, Wongpiromsarn explained.

"In this scenario, safety is being treated as just another factor to trade off," she said. "If safety truly comes first, you can't capture that with a single weight. Safety shouldn't be balanced against other goals; it should be a hard limit that the system never crosses."

Another problem is that this trade-off is hidden inside the system. "Because it's all blended into one number, it's difficult to see why the robot chose what it did or whether the priorities were balanced correctly," Wongpiromsarn said.

Wongpiromsarn said designers may also divide system goals into "hard" and "soft" constraints, with "hard" constraints taking priority no matter the cost. But this practice, she noted, exposes another basic flaw: what should a system do when a "hard" constraint—such as preventing harm—simply can't be satisfied?

For example, in the earlier scenario during which a pedestrian suddenly steps in front of a self-driving car, the vehicle is left with two choices: attempt to brake and potentially hit the person, or swerve to avoid the person and potentially collide with an oncoming car. In this scenario, the safety constraint is impossible to fulfill.

A hard-versus-soft framework offers no guidance—it can only declare the situation unsolvable, even though the vehicle must still act, Wongpiromsarn said.

Tichakorn Wongpiromsarn, associate professor of computer science at Iowa State University, has devoted much of her career to the development of autonomous vehicles, both in academia and industry settings. Credit: Tichakorn Wongpiromsarn

New rulebooks framework uses rankings, not weights...Wongpiromsarn said the research team's new rulebooks framework avoids these issues by ranking goals instead of blending them together.

"In our framework, each rule represents a specific goal—avoiding collisions, following traffic laws and so on—and the system clearly defines which rules come first, which are tied and which can't be directly compared," she said.

Ultimately, this gives autonomous systems a principled way to compare unavoidable violations and choose the least harmful option, Wongpiromsarn said.

"This approach lets robots behave more like people," Wongpiromsarn said, noting the importance of creating frameworks that reflect "how people actually reason about what's right and wrong, safe and unsafe, and acceptable and unacceptable."

"People typically follow the most important rules first and only consider lower-priority goals once the critical ones are met or proven impossible," she said.

Slutsky said the researchers' rulebook structure also allows for gradual specification of priorities.

"This means you don't have to decide all of a robot's priorities at once," he said. "Some base priorities can be set by law, and then the company building the robot can add more priorities later—as long as they stay consistent with the base priorities."

For example, if a law said "avoid harming humans or property" is the top priority for self-driving cars, that law would be a non-negotiable "must" for manufacturers. However, that same law doesn't specify whether "stay in your lane" is more or less important than "stay away from the curb," Slutsky said, which "allows manufacturers to choose how to rank those two goals—as long as both have lower priorities than 'avoid harming humans or property.'"

"Our hope is that this approach supports compliance without over-restricting," Slutsky said. "Everyone follows the same core rules, but companies still have the freedom to innovate and design their own behavior."

Why this matters right now...Autonomous robots already face situations where it's impossible to follow every rule, and regulators recognize this.

"With the rulebooks framework, we're not computing just one 'best' action," Wongpiromsarn said. "We're identifying all actions that are optimal under a prioritized set of rules."

This difference, she said, makes it possible for engineers, regulators and even courts to ask a crucial question: Did the robot behave in line with the rules we said mattered most?

"That capability is especially important for post-incident analysis," Wongpiromsarn said. "After a crash, near-miss or regulatory review, understanding a machine's reasoning can be as important as the outcome itself."

The study also shows that rulebooks can serve as a common language for many different robot-control methods. Logical rules ("if a pedestrian is present, always yield"), optimization goals ("minimize travel time") and constraint-based approaches can all be expressed within the same framework, eliminating the need to choose between competing mathematical philosophies or technical systems.

"In our tests, we showed that our algorithms can efficiently generate plans that respect complex priority structures and even outperform standard planning methods in situations where those methods break down," Wongpiromsarn said.

The implications also go beyond robots, the researchers said, noting that as artificial intelligence systems continue to take on more decision-making in areas like transportation, coordination, health care and public safety, the need for systems that can justify their choices will only grow.

"The rulebooks concept offers a way to encode societal values, legal norms and organizational policies directly into machine decision-making," Wongpiromsarn said.

"It won't solve every ethical dilemma facing autonomous systems, but it may help ensure that when machines make hard choices, they do so according to priorities humans can understand and even hold them accountable for."

The fact that the rules for autonomous robots are not uniform is mainly due to the fact that they operate in contexts with completely different levels of risk, purposes, and physical environments.

Here are the main reasons for this variation(below):

1. Context and operating environment...The rules are shaped by the environment in which the robot operates. A robot vacuum cleaner inside a house needs few regulations, as the risk of harm is low. On the other hand, an autonomous car on a highway or a surgical robot in a hospital operates under very strict rules, as any mistake can be fatal.

2. Sectoral and ethical differences...Different sectors require distinct ethical approaches:Military: The debate on Lethal Autonomous Weapons Systems (LAWS) focuses on "who is responsible" for a life-or-death decision.Industrial: Focuses on workplace safety and the interaction between humans and heavy machinery (cobots).Social: Companionship or service robots deal with privacy and data protection laws (such as the LGPD in Brazil or GDPR in Europe). 

3. Lack of a single international treaty...There is no "World Constitution of Robotics." Each country or economic bloc (like the European Union with the AI ​​Act) is creating its own laws. This generates a mosaic of norms that vary according to the culture and political priorities of each region.

4. Complexity of civil liability...The question of "who pays the price" if something goes wrong changes everything. In some cases, the responsibility lies with the manufacturer; in others, with the programmer or even the owner. As technology evolves faster than the law, the rules are adapted as new problems arise.

5. The myth of "Asimov's laws"...Many people think of Isaac Asimov's Three Laws of Robotics (a robot may not injure a human being, etc.). While great for fiction, they are too vague for real engineering. Programming "do no harm" is extremely difficult in logical terms, as "harm" can be interpreted in a thousand different ways. 

Provided by Iowa State University 

AUTONEWS

Smart motorways were halted over safety concerns—what's the future for digital roads?

For many people, the rollout of smart technology across the UK's road network has been clouded by fears about the removal of traffic-free safety lanes. Traditionally, motorway hard shoulders offered motorists a safe haven into which they could steer stricken vehicles.

But amid growing traffic numbers, the rationale for smart motorways (part of the UK government's wider digital roads plan) was to free up these extra lanes to traffic. During a breakdown, the remote monitoring system could then quickly reinstate a temporary hard shoulder while the broken down or crashed vehicle was removed.

However, since the first official smart motorway system was introduced on the M42 near Birmingham 20 years ago, the public has repeatedly raised concerns that being stranded in a live lane rather than on a hard shoulder can be more dangerous.

In 2020, BBC Panorama reported that 38 people had been killed on smart motorways in the preceding five years. Since then, campaign groups have continued to highlight fatal collisions on smart motorway stretches where broken-down vehicles have been struck in live traffic.

In April 2023, the government's rollout of more smart motorways in England was halted by then-prime minister Rishi Sunak on the grounds of both safety and cost. However, existing smart motorways remain in operation and continue to receive safety upgrades.

The National Highways' most recent stocktake on smart motorways in England, published in December 2024, stated: "Overall, in terms of deaths or serious injuries, smart motorways remain our safest roads."

But the same year, another Panorama investigation found nearly 400 instances where safety technology had lost power on smart motorway stretches between June 2022 and February 2024.

As part of a National Highways-funded research program, I and other researchers at Cardiff University have worked with drivers and transport-sector experts to explore how people feel about the future of the UK's road network. We investigated their concerns not only around safety but also surveillance and data collection.

Sense of uncertainty...The UK's digital roads strategy entails much more than smart motorways. Even after the hiatus on building new smart motorways in England, there is still a growing ecosystem of digital and data-driven technologies embedded across the UK road network. These include roadside sensors to monitor traffic flow, cameras to detect incidents and infrastructure that communicates with control centers.

The aim is not automation for its own sake, but earlier detection of problems, faster response, smoother traffic flow and fewer serious incidents. Artificial intelligence and predictive analytics form part of this system.

Our study shows that most people are not resistant to these innovations on the roads. Many people we spoke to welcomed technologies that promise to improve safety or reduce congestion.

However, what unsettled many of them was the sense of uncertainty they felt about the rollout of these systems.

Some participants worried that data generated through digitally connected vehicles and road infrastructure could eventually "be used by insurance companies to penalize drivers."

Others raised concerns that "systems designed for traffic management might gradually expand into broader forms of surveillance."

One participant described the possibility of geolocation data revealing patterns of "my daily or weekly movement in the case of a data breach, which is dangerous."

Another wondered whether automated sensing technologies might distract drivers who feel compelled to "avoid the sensor that records what I am doing."

In general, people did not reject technological change out of hand. Rather, they want clearer safeguards around how these systems are governed, who can access the data they generate, and how accountability will be maintained as transport infrastructure becomes increasingly "intelligent." Their concerns center on questions of fairness, trust and accountability.

Technology trade-offs...Over the past 20 years, smart motorway schemes are estimated to have cost UK taxpayers billions of pounds.

The M4 smart motorway upgrade alone, between junctions 3 and 12, cost around £848 million. Recent safety reviews have committed a further £900 million to retrofit additional emergency refuge areas and improve detection systems on existing stretches.

But the costs are not only financial. There are also social and institutional costs: public confidence, legitimacy and the burden placed on road users to trust systems they did not choose and may not fully understand.

Understanding these trade-offs is important for the public. Smart road infrastructure represents a major public investment to address genuinely risky situations: broken-down vehicles, sudden congestion, poor visibility or secondary accidents caused by delayed response.

Much of this happens invisibly, which is precisely why transparency matters. When people do not understand what systems are doing, silence is easily interpreted as secrecy. Multiple parliamentary and audit reports have raised questions about whether the smart motorway rollout was too rapid, or communication to the public was inadequate—or both.

Some countries have taken a more explicit approach to public engagement around transport innovation. In Sweden, for example, the national road safety strategy, Vision Zero, was introduced as part of a broad public policy framework that placed societal consent and safety at the center of infrastructure design.

In the UK's third road investment strategy (2025-2030), smart roads will probably become more interconnected, more predictive and more automated.

Digital twins—virtual models that replicate real roads and infrastructure so planners can test scenarios before implementing them—will play a larger role in planning. Increased data sharing may allow more integrated services across multiple modes of transport. AI and analytics could increasingly support operational decisions.

But the controversy around smart motorways wasn't just about design choice. It reflects a deeper public concern: what happens when safety depends on systems people can't see or easily understand?

To answer this, the systems that run smart roads need to be open and trustworthy, safe and reliable in the eyes of those who rely on them every day.

Usage examples of the future for digital roads(below):

Predictive maintenance & digital twins: Using virtual replicas to simulate traffic, monitor structural health with sensors, and predict failures before they happen.

Autonomous vehicle integration: Road infrastructure that communicates directly with smart cars to optimize traffic flow and safety.

Intelligent traffic management: Real-time data adjustments to congestion, weather, and accidents to optimize traffic, such as dynamic lane usage.

Automated Repair Vehicles: Utilizing robotic vehicles for road maintenance, which can enhance safety during construction.

Data-Driven Safety Upgrades: Using cameras and IoT to immediately detect accidents and adjust signals, enhancing incident management.

Synonyms for Digital Roads:

-Smart roads

-Intelligent transportation systems (ITS)

-Connected infrastructure

-Intelligent roadways

-Digital twins of road networks

Key future trends and challenges(below):

Sustainability: Designing road networks that prioritize environmental efficiency.

Safety & security: While smart technology is aimed at improving safety, concerns exist regarding privacy, data breaches, and reliability of Automated Systems.

Operational shifts: Transitioning from reactive maintenance to preemptive intervention to extend asset life.

Provided by The Conversation