The State of Level 3 Autonomous Driving in 2023: Ready for the Mass Market?

Autonomous driving technology has come a long way. In recent years, the automotive tech industry has made significant enhancements to the capability and reliability of sensors, cameras, and vehicle-to-everything (V2X) communication, driving road transport toward higher levels on the autonomous driving spectrum, as defined by the SAE’s Levels of Driving Automation.

Source: SAE International

This spectrum has become an internationally recognized classification for automated driving systems. Its six levels can be divided into two broad categories: driver support systems from L0 to L2 (shown in blue), and automated driving systems from L3 to L5 (shown in green). For the past several years, industry players have been working to make the jump from L2 to L3.

From Level 2 to Level 3 Autonomous Driving, a Legal Matter

Clearly, the leap from L2 to L3 is the most significant leap on the spectrum. Whereas L2 is considered as advanced driver support features, L3 marks the beginning of conditional autonomous driving, where drivers can legally take their eyes off the road when conditions are met. Strictly speaking, only vehicles classified as L3 and above are truly autonomous vehicles.

By today, most major automotive OEMs have mastered their technologies for L2 autonomy. As of the beginning of 2023, L2 driver support systems include Tesla’s Autopilot with “Full Self-Driving”, Audi’s Traffic Jam Assist, GM’s Super Cruise, BMW’s Extended Traffic Jam Assistant, Ford’s Blue Cruise, Hyundai’s autonomous driving package, and many more.

Now, a problem arises when OEMs seek to introduce vehicles with Level 3 autonomous driving. Looking at SAE’s autonomous driving spectrum again, the levels of autonomy are not defined by a vehicle’s self-driving capability, but instead by the expected roles of the vehicle and the human driver. For instance, under L2, the human driver must pay full attention to the road even when all driver support systems are on, whereas in L3, the human driver can officially take their eyes off the road when the automated driving systems are switched on.

Therefore, if an OEM wants to officially introduce an L3 vehicle, it must be liable for all potential accidents that occur while the vehicle’s L3 systems are switched on. That is, no matter how advanced and sophisticated the technology inside a vehicle might be, if the OEM is not ready to claim responsibility for accidents caused by its systems, the vehicle can only be classified as high as L2.

The truth is, although the technology for Level 3 autonomous driving might be ready, many OEMs are not yet prepared to officially claim L3 for legal reasons. This explains why Tesla uses the name “Full Self-Driving” to market its L2 driver support systems without mentioning L3 autonomy. Some OEMs use the term “L2+” to show that their technological capabilities have surpassed L2, yet do not claim L3. Hence, the gap between L2 and L3 is more of a legal gap than a technological gap.

Official Certifications Needed for L3 Autonomy

Since L3 is the first level on the SAE’s spectrum to allow drivers to take their eyes off the road, official certifications and approvals are needed before OEMs can claim a vehicle to be L3. These certifications are often issued by regional transport authorities and highway safety agencies.

In May 2022, Mercedes-Benz became the world’s first manufacturer to get approved by German transport authorities to legally operate its L3 Drive Pilot on the country’s public roads, sold as an option on Mercedes-Benz S Class and Mercedes EQS. This means that those with L3 Drive Pilot are legally allowed to eat, draft emails, or watch videos on the Autobahn. Still, given that L3 autonomy is conditional, if the vehicle loses the environmental or locational conditions to operate at L3, it will prompt the driver to take control within ten seconds. If the driver fails to respond in ten seconds, the car will automatically turn on emergency lights and decelerate to a full stop on the side of the road, then unlock the doors in case first responders might need access to the cabin.

At CES 2023, Mercedes-Benz further announced that it has become the first manufacturer to receive L3 certification in the United States, from the state of Nevada. However, since L3 approval is granted at a state level in the US, the system is only considered L3 in Nevada for now. Nonetheless, the OEM says its Drive Pilot is fully ready to deliver L3 autonomous driving in all 50 states.

Is Level 3 Autonomous Driving Coming to the Mass Market in 2023?

Mercedes is the first manufacturer to make the bold move to bring L3 autonomy to the consumer market. Although Honda Legend won the title for the world’s first approved L3 vehicle back in 2021, only 100 limited-edition vehicles were available for lease only in Japan. Honda’s L3 road map suggests it may take much longer to reach the mass market.

There is no doubt that more and more manufacturers will follow Mercedes’ move towards L3 autonomy. Major OEMs like Hyundai-Kia, Stellantis, BMW, GM, and Honda are continuously reporting progress and plans for L3 rollout. However, it is always easy for OEMs to announce plans and schedules but difficult to make the final decision to obtain L3 approval. Even Mercedes’ L3 Drive Pilot is available for the S Class only, and legally approved in very limited regions (Germany and Nevada). Apart from legal concerns, sensitive public reactions toward flaws in automated driving systems make OEMs more reluctant to introduce L3 vehicles on a large scale.

Hence, although the news is filled with press releases and announcements on launching L3 systems, it is unlikely to see L3 vehicles being available to the mass market within 2023. Nevertheless, following the path of Mercedes-Benz, more and more OEMs will likely launch L3 options for their high-end vehicles in limited regions within the year.

Addressing the Challenges Ahead

Achieving Level 3 autonomy is beyond a matter of technological capability, but a matter of confidence – the confidence that OEMs possess towards their automated driving systems. Before OEMs can gain full confidence in taking responsibility for their automated driving systems, several potential risks need to be addressed. One of them is cybersecurity risk.

Since automated driving features are run by software, these software-defined vehicles (SDV) must not be vulnerable to cyberattacks. If a threat actor were to gain access to a vehicle’s embedded systems and applications, they could gain the ability to tamper with driving data and potentially take control over crucial functions of the vehicle.

AUTOCRYPT has always envisioned a world of L3 and L4 autonomy. Since its inception, it has been working with OEMs and software providers to secure the in-vehicle systems and communication endpoints of SDVs through its industry-leading encryption and authentication technologies, offering solutions from vulnerability testing to intrusion detection and protection.

To learn more about how AUTOCRYPT secures the SDV, download the white paper below.

white paper sdv thumbnail

“The changing tides of the automotive industry into more software, and less hardware, indicate that vehicles will be a possible target for cyberattacks. This is why holistic, comprehensive cybersecurity is essential in securing the next generation of SDVs.”

Download White Paper

From EV to Autonomous Driving: A Look Into the Mobility Industry in 2022

2022 was a turbulent year for the mobility industry. As the economy has been recovering back to its pre-pandemic state, we have seen a surge of technological advancements that are shaping the industry.

To commemorate the end of the year we have carefully analyzed the market and gathered four key insights to discuss the biggest trends of 2022 and see what the trajectory for the future of the mobility industry looks like. 

1. The tipping point in EV adoption 

In 2022 we have seen the catastrophic impact of the climate crisis on our planet. The world was struck by extreme heatwaves in Europe, hurricanes across multiple US states, and monsoon floodings in Asia. The intensity of these devastating climate disasters has been increasing as a result of climate change. And as the global climate crisis continues to unfold governments are taking action to tackle the dangers of climate change by rolling out net-zero carbon emission policies to accelerate the road to decarbonization.

One of the largest industries contributing to the climate crisis is transportation, which is responsible for 20% of carbon emissions worldwide. Decarbonizing the mobility and transportation sector is imperative in reaching net-zero goals, and electrifying the roads is the most effective way to do so. Electric vehicles have been at the forefront of the transition in the mobility industry. As the world strives toward net-zero emissions, governments are increasingly pushing for electric vehicle (EV) adoption through subsidies and related policies. Europe and the United States are leading way with regulatory targets of reaching a 50% EV market share by 2030. On the other side of the spectrum, consumers are becoming more environmentally conscious and increasingly willing to make the switch in favor of electric vehicles. And as the technology gets more advanced the supply side is catching up with the demand.

The EV adoption rates are signaling a positive change in the market and bringing us closer to reaching net-zero goals in the transportation sector. However, we are still far from achieving decarbonization and need to take drastic measures in accelerating EV adoption across the board. Continuing to expand the charging infrastructure, supporting change with government policies and subsidies, as well as encouraging innovation are some of the key steps we need to take to meet decarbonization targets.

2. Autonomous driving

Electrification on the roads lays down the groundwork for further innovation opportunities in the mobility industry. To accommodate EV production, manufacturing facilities had to be redesigned and rebuilt from scratch, this allowed OEMs to trial new technologies and software in their vehicles. As the EV market grows, we can see the expansion in related automotive technologies, with innovations ranging from connectivity to autonomous driving.

The buzz around autonomous driving technologies has been around for a while; rightfully so, as autonomous driving technologies are extremely beneficial in increasing road safety and access to mobility. And 2022 was a notable year for the collective movement toward achieving higher levels of autonomy. Currently, major OEMs have achieved Level 3 autonomy, or conditional autonomy, where the vehicle can drive itself under appropriate conditions, but a human driver must always be present in the car. The main technology that allowed us to achieve Level 3 autonomy is Advanced Driver Assistance Systems or ADAS. ADAS uses radars, cameras, ultrasound, and a variety of different software to achieve vehicle automation. While ADAS is an essential element in providing autonomous driving, it is simply not enough to achieve higher levels of autonomy.

Autonomy Levels 4 and 5 entail high levels of autonomy with minimal to no intervention from the driver. To achieve these advanced autonomy levels, we need more comprehensive technologies such as connectivity. At the heart of vehicular communication technologies, we have vehicle-to-everything (V2X) technology that connects the vehicle to the network, infrastructure, other vehicles, and passengers around it. V2X communication utilizes wireless communication between the vehicle and the environment around it to gather real-time data on traffic conditions, road signs, warnings, and much more. V2X technologies are also very beneficial in ensuring road safety as they include connectivity with other vehicles (V2V) and pedestrians on the road (V2P).

This technology can greatly improve the effectiveness and accuracy of existing ADAS technologies and fast-track the path to full automation. 

3. Universal mobility

EV passenger vehicle numbers are growing, but so do the numbers of EV commercial fleets. In the past years, we have seen governments deploy electric buses, trams, and taxis in attempts to decarbonize public transport systems as well as increase access to mobility. Universal mobility entails having access to transportation for all members of society. The ultimate goal is to achieve universal basic mobility (UBM) and democratize the sector so everyone can access safe and efficient transportation. Among the latest technologies aimed to provide UBM are mobility-as-a-service (MaaS), robotaxis, and carsharing services.

The emergence of MaaS is not surprising, as it allows access to transportation for everyone who owns a smartphone. MaaS is currently on the rise with multiple successful cases worldwide, namely Kakao Mobility, Uber, and Lyft. These companies have been able to integrate multiple modes of transportation into a user-friendly mobile application, making transportation easily available to people at the tap of their fingers. 

As MaaS continues to grow businesses will need assistance in rolling out their own mobility services. AUTOCRYPT launched its mobility service solution AutoCrypt® MOVE, integrating its fleet management system with big data analysis and demand-oriented service modeling to help businesses and NGOs easily establish their own mobility services and reach universal basic mobility. 

4. Increasing need for cybersecurity

As vehicles become increasingly automated and connected, the need for effective cybersecurity measures becomes more important. With the proliferation of connected vehicles, hackers have more opportunities to gain access to vehicle systems and potentially cause harm. In addition, the increased use of automation in vehicles means that there are more potential points of failure that could be exploited by malicious actors. 

One of the main reasons for the increasing need for cybersecurity in the automotive industry is the growing number of connected vehicles on the road. Many modern vehicles are equipped with internet connectivity, which allows them to communicate with other vehicles and with external systems, such as traffic control systems and other infrastructure. This connectivity opens new possibilities for vehicle operation and convenience, but it also creates new vulnerabilities that can be exploited by hackers. For example, a hacker who gains access to a connected vehicle could potentially take control of the vehicle’s systems, including its brakes, steering, and acceleration. This could result in dangerous situations, such as collisions or loss of control. In addition, a hacker could potentially access sensitive personal information stored in the vehicle, such as location data or information about the vehicle’s owner. Exactly that happened in January of this year when a researcher was able to hack into 25 Tesla vehicles and gain access to vehicle control and the personal information of car owners. 

Another reason for the increased need for cybersecurity in the automotive industry is the growing use of automation in vehicles. Many modern vehicles are equipped with ADAS and vehicular communication technologies, which can assist with tasks such as lane keeping, automatic braking, and adaptive cruise control. While these systems can improve safety and convenience, they also introduce new potential points of failure that could be exploited by hackers.

Overall, the increasing use of automation and connectivity in vehicles is creating new challenges for cybersecurity. To protect against these challenges, it is important for the automotive industry to develop and implement effective cybersecurity measures. This may include measures such as encryption, secure authentication, and regular over-the-air (OTA) software updates to protect against known vulnerabilities. 

This year has seen positive strides in the mobility industry. The expansion of electric vehicle adoption, autonomous driving, universal mobility, and cybersecurity points to an industry-wide trend toward electrification, decarbonization, and innovation. However, in order to achieve the full potential of the technological shift within the sector we must remember to support this expansion with government policies, investments, and innovation.

As an automotive cybersecurity and mobility solutions provider, AUTOCRYPT offers secure connectivity technologies that support the expansion of the mobility sector. From securing V2X communications to embedded vehicular systems, AUTOCYRPT ensures that all connections are secured before vehicles hit the road. 

Barriers to Autonomous Vehicle Adoption

Autonomous driving has been a futuristic technology we’ve seen in entertainment for decades. In the 2020s, self-driving seems like it is becoming a tangible reality, with manufacturers like Tesla releasing Full-Self Driving (FSD) mode, and other manufacturers eager to follow suit. While manufacturers have quite a way to go before achieving high or full automation (level 4 and 5, respectively, according to the SAE levels of vehicle autonomy), the bigger problem is that though manufacturers may be hard at work developing autonomous technology for future self-driving vehicles, there are still many factors to consider before fully overcoming the barriers to adoption of autonomous vehicles. Here are just a few of these challenges we look through in our blog today.  

1. Technology

There are a variety of factors why we haven’t seen more autonomous vehicles on our roads – technology is one of them. As previously mentioned, though manufacturers may tout “autonomous tech,” it’s still more of a marketing term, rather than technologically reliable. For example, autonomous vehicles rely on sensors like Lidar, Radar, and cameras. These technologies help the car navigate the environment around them, and they should be able to detect buildings, other vehicles, road infrastructure (think traffic signals and road signs) and most importantly, pedestrians. Sensors have to “see” in order to do all of this properly: whether it’s in inclement weather conditions, or in congested urban areas. While the available sensors are continuing to make great advancements in ensuring safety in autonomous driving, we have to ask ourselves what is the level of certainty we require and the level of risk we’re willing to allow.  

2. Public acceptance

In addition to the technology development, there is the issue of acceptance within society. While the majority of the population enjoys seeing futuristic technology on the big screen, it is an entirely different matter when it comes to personal usage. There is still resistance and distrust when it comes to self-driving cars. The Partners for Automated Vehicle Education (PAVE) found that 3 in 4 Americans say that they don’t think autonomous vehicle technology is ready to be mainstream. 48% said that they would never use a self-driving ride service, and 20% believed that AVs will never be safe. This was a 2020 poll, but polls in previous years have shown similar skepticism, and it looks like this attitude might be here to stay unless some major changes occur.  

3. Security

One reason that the public is still wary of autonomous vehicles may be that they don’t fully trust the security of AVs. More connected than its traditional counterparts, an AV is essentially a smartphone on wheels, which means that it is at risk of breaches unless a proper cybersecurity management system protocol is in place. There isn’t a one-stop solution to having a proper cybersecurity management system, but the ISO/SAE 21434 risk assessment system is a good place to start.  

Fortunately, manufacturers will soon be mandated to have a proper cybersecurity system in place. Starting in July 2022, new vehicle models will be required to get cybersecurity type approval for the model before it is allowed to be put on the market.  

4. Standardization and regulations

Ultimately, many of our aforementioned barriers to adoption can be improved upon when there are wider, universal standards put into place by regulators. For example, the UNECE’s WP.29 regulations for cybersecurity will mandate in-vehicle security for new vehicle models next year, and all vehicle models by 2024. With this kind of overarching, nearly-universal regulation in place, the public’s acceptance of connected and autonomous vehicles will continue to grow.  

An added example is the recently published ISO 22737, the first international safety standard for Level 4 automated driving systems. These types of standards help us to have more trust for safety and security, addressing the minimum requirements for technology systems, that previously were unclear.  


Unfortunately, AV adoption isn’t as simple as making a fully autonomous vehicle and putting it on the road. To overcome the various barriers to adoption, many factors need to work hand-in-hand to ensure not only that the vehicles do what they’re supposed to do, but also other societal infrastructure is on the same page. Standards will help move this process along, and we will be sure to keep you updated on the latest standardizations that are developed to keep our vehicles and mobility services secure.  

For more information about our vehicle security solutions, visit  

The Future of the Car: A Paradigm Shift of the Century

A key characteristic of the fourth industrial revolution is that conventional machines and electronics are reinvented or combined into “smarter” all-in-one products, blurring their original definitions. For instance, the smartphone was reinvented by combining a conventional cellphone and a computing device. The smartwatch was created by combining a conventional watch and a computing device. The smart speaker was a combination of a conventional speaker and a computing device. The list goes on. Instead of drawing new things out of scratch, the fourth industrial revolution seems more like an overhaul to our existing world, where we reinvent existing items and redefine their purposes, often by combining them with computing capabilities and connecting them to the cloud. What’s more interesting is how people’s perceptions and attitudes towards these products change as they experience and interact with them. Since these reinvented products tend to serve a variety of purposes that overlap with one another, users have more options available at their hands to do the tasks needed, making daily lives more seamless.

The automotive industry is no exception. However, changes here are less visible as they occur at a slower pace. Perhaps it is because cars are relatively expensive items with longer lifecycles, or because cars directly determine our physical safety, or that cars have been around for much longer compared to other electronic devices and appliances. Indeed, since the world’s first engine-powered vehicle was invented by Carl Benz in 1885, essentially the same car concept has been with us for more than a century now. Yes, the appearance of cars has evolved considerably, but their functionalities and benefits have remained unchanged. For over a century, people have viewed the car as a mode of transportation for people and goods from point A to point B.

With the fourth industrial revolution, we are finally starting to witness a change to the century-old definition of the car. This enormous paradigm shift can be characterized by several seemingly unrelated industry trends.

2000s: Car Tech

For many decades, the only digital technology the average car had was the radio. Yet, starting in the 2000s, new technologies began to emerge, one after the other. From GPS navigation to Bluetooth, hands-free calls to voice command, phone mirroring to video streaming, the car had become a sophisticated computer with countless features.

As people interacted with these new features, their perceptions and expectations changed. These changes made it more challenging than ever for automakers to build a satisfactory car. In the past, a car was judged only by quality, comfort, and performance. Excelling any two of the three aspects would pretty much guarantee success. This was how big and prestigious automakers survived all these years of competition. But even the big names are facing difficulties today because consumers are so used to car tech and demand more and more of these tech features manifested in the most intuitive and useable manner.

The increased demand for car tech signaled the beginning of the paradigm shift; cars were no longer a simple means of transportation, but an experience to enjoy.

2010s: The Growing Popularity of SUVs

This is by far the most visible change that can be easily observed by anyone attentive to the road – sedans are being taken over by SUVs. Almost every automaker worldwide has reduced sedan lineups, favoring prioritization of the rollout of SUVs. Even OEMs that traditionally focus on the niche market are now abandoning sedans and moving to SUVs as an attempt to capture the mass market. Porsche is a typical case where the brand repositioned itself from a sports car brand to a brand focused on luxury SUVs. Even Rolls Royce, Bentley, and exotic makers like Lamborghini are adding SUVs into their flagship lineups.

Statistically, the market share of SUVs has increased dramatically over the past decade. Between 2010 and 2019, the global market share of SUVs in total car sales increased from 17% to 41%, with the figure reaching as high as 50% in the US. In a matter of a decade, SUVs have become the most popular car segment on every continent.

Why are SUVs becoming more popular? While there are many hypotheses, most of them point to a change in the general public’s perception. SUVs can make people feel more powerful, and while sedans are built with performance in mind, SUVs allow for more space and a greater onboard experience, rather than the drive itself. Therefore, since the paradigm of the car is shifting away from driving and more towards the onboard experience, there are simply fewer and fewer reasons to buy sedans over SUVs.

2020s: Environmental Responsibility

For decades, cars have been blamed as a major culprit for climate change and global warming. This forced the industry to seek more sustainable options, going from gasoline to hybrids and now towards electric. The electrification trend is less related to the car itself, but more of a result of external pressure.

Why has the electric car gained popularity in such a short period of time? This can be attributed to multiple reasons, such as better battery technology, success in Tesla’s marketing campaigns, and increased environmental awareness worldwide. But the most critical reason behind this trend is that people are gradually seeing cars as more of an innovative tech than a conventional machine. Since the paradigm shift has already blurred the definition of the car and changed public perception of what a car should be like, it is now a lot easier for people to adopt electric vehicles. It is also easier for EV makers to experiment with bold and exotic designs.

An interesting phenomenon is that the more people interact with electric cars, the more their perceptions of the car will shift towards them. This again further accelerates the process of EV adoption. Based on this effect, it certainly won’t be long before EVs surpass ACE vehicles in sales.

2020s: Autonomous Driving

Autonomous driving has been one of the most controversial topics in the automotive industry due to a wide range of concerns on safety and legality. Now, with the advancement of big data and artificial intelligence, along with the increased stability of the cellular network, the public is now finally ready to trust the car to drive itself. Even though most of the current semi-autonomous vehicles rely on cameras and sensors, this is about to change as V2X technology starts to roll out in newer vehicles. When V2N technology gets adopted by the mid-2020s, many of the vehicles on the road are expected to reach full autonomy.

Again, the public’s increased acceptance for autonomous driving is not only due to technological advancement, but rather, caused by the paradigm shift. Reemphasizing the point that cars are now more associated with their onboard experience rather than the driving experience, people are more willing to let the car do the driving and focus themselves on the cabin experience.

2020s: Mobility as a Service

The paradigm shift has redefined the car to become less of a transportation tool and more of a mobility experience. Now some may ask, what about those who only want a simple transportation tool without having to own a bunch of add-on features? Those needs can be answered by a new market: mobility-as-a-service (MaaS).

For those who choose to not purchase the complete experience and only want a minimalistic ride, MaaS is becoming an appealing alternative to owning a car. With the help of big data and machine learning, ride-hailing and ridesharing services are becoming increasingly popular among those who do not like owning cars. Advanced fleet management systems allow the operator to perfectly match vehicle supply to passenger demand, dispatching the perfect number of vehicles to each area in need, and automatically carpooling those on the same routes. These on-demand services will completely transform public transportation so that people no longer need to look for bus stops and are no longer confined to living near subway lines.

The New Paradigm: A Lifestyle on the Go

In essence, the car is becoming less and less of a transportation tool and more of a mobile home characterized by entertainment, convenience, and comfort. With more and more workers working remotely, people are now having more time and freedom to live and travel to any place they like. The car represents this dynamic lifestyle, offering a private space that feels like home, with all the enjoyment, convenience, and comfort of home. Only automakers that can best adapt to the paradigm shift will survive the 2020s.

When Last Mile Delivery Turns Autonomous – What are the Considerations?

As more of our lives becomes connected to networks and online services, we are finding that previously labor-intensive tasks like getting groceries or using public transportation are becoming streamlined as reservations and payments can be made online, even bringing items to your front door. But with increased connectivity comes greater expectations for faster, efficient, affordable, and secure services and deliveries.

The delivery process may seem straightforward – order your product, the seller arranges products for delivery, and the delivery service brings it to you – the actual process of getting the many different products with different supply chains together in one place, then arrange the transport going from the hub to the final destination. This portion of the trip is called “last-mile delivery” as it’s one of the trickiest parts of the supply chain process. Not only is last mile delivery the part that we as consumers often care the most about, last mile delivery accounts for around 53% of the total cost of shipping and sellers are taking less of a cut as supply chains struggle to meet demand and deadlines.

last mile delivery challenges

(Source: EFT)

Last mile deliveries are often inefficient because of the sheer volume of deliveries necessary with a low drop size. This means that efficiency is virtually impossible with retail sales only going up, especially with a global pandemic.

Taking care of the last-mile challenge

The supply chain management industry experts have been looking for solutions to this dilemma. Many have pointed to models that utilize digital platforms to crowdsource local services to ensure that consumers are able to get what they need. Instead of manually dispatching delivery people to make the trip, platforms will utilize machine learning and AI to quicken this process.

Another solution that many companies are already cashing in on is the concept of autonomous delivery technology, with the market expected to reach 84.72 billion USD by 2030. In order to make last-mile deliveries more efficient and truly door-to-door, development has been focused on autonomous pods, which can navigate more difficult and uneven terrain to ensure completion of delivery.

Smaller pods focus on small, dynamic designs to ensure efficiency in last-mile delivery. This allows for reduced costs in the delivery pod itself, as well as increased security as the vehicles do not actually carry human beings, allowing for more focus on the actual delivery and of the safety of those around them. Especially with the global pandemic, solutions like autonomous delivery allow for contactless service, without driving up costs. Analysts at McKinsey found that semiautonomous and autonomous technology reduce delivery costs on average by approximately 10 to 40 percent.

Autonomous delivery challenges

We can already see this crowdsourcing model mentioned in the previous section in the real world, prevalent in industries like transportation (think ride-hailing apps), food delivery, and retail apps. But this solution isn’t without challenges of its own, as local services still have a high maintenance cost, and with actual human drivers, there’s likely going to be a larger margin of error and limitations.

This is why tech industry experts say that long-term, autonomous driving technology is the answer. Autonomous vehicle technology has made great headway in the last decade – from the testbeds to public roadways — and while use cases are moving from theoretical plans to reality, there’s still a lot of doubt and logistical issues when it comes to application.

Technology and infrastructure limitations

While there are some companies who have gotten the autonomous delivery robot/pod concept to real-world application, there’s still a lot at risk in terms of how the technology works. Passenger vehicles have yet to be at a Level 4 of autonomous driving (according to the SAE regulations), so it’s not completely realistic to expect autonomous pods to be at this level. We need to be careful to ensure that the priority is placed in keeping human beings (pedestrians and vehicle passengers) safe when pods are navigating through streets.

While the technology is being developed, we also must remember that technology can’t be the only thing to change. Cities also need to ensure that current infrastructure supports the autonomous delivery movement, for example, making sure that roads are paved properly and that any obstacles like potholes or cracks are quickly repaired.

Lack of universal standards and liability regulations

To deal with the infrastructure challenges mentioned in the earlier section, there needs to be universal regulations that allow for both services and end users to use services more effortlessly across state or even country-lines.

In countries like the United States where there are differing federal and state regulations, using mobility services like last-mile deliveries with autonomous technologies can be a challenge. For example, in the state of Pennsylvania, autonomous delivery bots are allowed to maneuver their way through sidewalks as well as roadways. They are technically considered “pedestrians” meaning that the bots can move at a maximum speed of 12 miles per hour in a pedestrian area with a load limit of 550 pounds. This isn’t true for all states as some have no regulations regarding delivery systems like this, while others require permits to be issued by the state.

These technicalities can make a major difference when it comes to not only service operations, but also liability frameworks in the case of an accident. As autonomous technology has not yet been perfected, there is risk when it comes to operation no matter how safe the company deems it. A universal standard or regulation will allow for the risk to be minimized, as much as possible.

Risks of security breach

Because of the groundbreaking nature of this technology, many often focus on the issues surrounding the technology itself. However, we must remember that this technology is connected in nature, meaning that thousands of messages containing data are being exchanged each second in each vehicle. With data like PII, vehicle data, as well as access points to connected devices, a successful breach can be a goldmine for malicious actors.

While autonomous delivery vehicles like pods or robots do not carry any passengers, the personal data that they carry, their operations on pedestrian sidewalks, as well as the close nature of door-to-door delivery still carries implications that we must consider before application.

Short and long-term solutions for autonomous delivery

The technology for autonomous delivery bots will continue to progress. But how quickly this happens depends on other factors. In the long run, standards and regulations will have to be made by legislators and committees, which will influence new infrastructure that will enable this kind of technology to have more widespread adoption.

In the short-term, however, both manufacturers of these pods as well as service providers can prioritize security like authentication and encryption, ensuring that the data stays private. Security solutions can be built into the chipsets in the manufacturing stage, protecting data privacy before vehicles, and pods, hit the road. Solutions like these can ensure that vehicles of all sizes protect not just the items carried inside, but also those around them.

The Role of Machine Learning in Strengthening Autonomous Vehicle Security

With Tesla considered one of the best bubble stocks for 2021 (shares soared 743% in 2020 and made Elon Musk the richest person in the world for a few days), the company is at the center of people’s attention as it’s been evolving on a very public stage. While the market indicates an increasing interest in autonomous driving, AAA’s 2019 annual vehicle survey found that 71 percent of Americans are afraid to ride in self-driving vehicles, especially after several high-profile incidents came to light the past few years.

The statistics above suggest that we may still be a few years away from driving fully autonomous cars. For self-driving cars to be fully autonomous, they need to deploy technologies such as RADAR (Radio Detection And Ranging), and LiDAR (Light Detection And Ranging) as well as algorithms to detect and respond to surroundings.

Can Autonomous Vehicles Be More Dangerous Compared to Traditional Vehicles?

Autonomous vehicles can be much more vulnerable than other devices we use in our daily lives as they utilize a combined deployment of various sensors and vehicle-related technologies. It’s known that even a single vulnerability can allow hackers to exploit the entire vehicle – meaning hackers may not only gain access to the operating system but possibly the entire network as well.

What’s more, autopilot has helped set the standard for numerous autonomous vehicles and gave a taste of what self-driving cars will be like in the near future. However, experts at the Tencent Keen Security Lab demonstrated that they could remotely compromise the Autopilot system on a Tesla vehicle. Even though the bug was promptly fixed after the presentation, this situation sheds some light on the potential for exploitation. As autonomous vehicles rely highly on “connectivity” itself, there’s no doubt that hackers see autonomous vehicles as tempting targets that contain countless amounts of data that can be used to exploit the system, which in theory could end up destroying every single aspect of the vehicle.

That is why in-vehicle security and the complexities involved have been the major focus of any discussion about autonomous vehicles. In-vehicle security isn’t just about protecting and securing the autonomous vehicle itself, but rather about mitigating as many risks as possible through the delivery of a comprehensive and holistic approach to automotive driving security.

How Can Autonomous Vehicles be Secured?

In order to secure the whole autonomous driving process, an important fact needs to be emphasized; these vehicles aren’t like the traditional ones out there. The complexity of autonomous vehicles makes it far more difficult to fully secure the vehicle – though it’s not impossible – and the only way to do that is by prioritizing security.

One possible solution is in-Vehicle Security (IVS) which is the car’s first line of defense that helps protect vehicles from external threats, monitors all relevant communications, and responds to any abnormal activity. As a result, deploying IVS is what’s most important in securing the vehicle. IVS needs a reliable Intrusion Detection System (IDS) that provides the security modules needed to guarantee safe communications between Electrical Control Units (ECUs).

Additionally, with the adoption of new regulations, it’s important to make sure that your provider is prepared to meet the requirements of WP.29 along with other industry standards of deploying a system that secures communication between vehicles, devices, and infrastructures.

This is where machine learning comes in.

How Can Machine Learning Enhance the Security of Autonomous Vehicles?

Machine learning is the process of using, storing, and finding patterns within massive amounts of data, which can eventually be fed into algorithms. It’s basically a process of using the data accumulated by the machine or device that allows computers to develop their own algorithm so that humans won’t have to create challenging algorithms manually.

With all the features and applications of machine learning, it’s easy to understand how our collected data are stored and used via a proper platform which in turn analyzes logs and patterns. In this way, this platform can warn and even mitigate risks occurring within the vehicle.

In other words, once the logs are collected and stored, machine learning technology can start analyzing and detecting these logs to see if there are any abnormalities. As machine learning enhances the detection model, it develops algorithms that can be used to detect malware activities and unusual behaviors of the vehicle. This process enhances the driver assistance technology by classifying the right data and patterns through various sensors attached to the vehicle.

Moreover, thanks to the advances in wireless technologies, a vehicular (ad-hoc) network is being formed among moving vehicles or RSUs (Roadside Units) and other communication devices. This network is considered a proprietary system that is seen differently from average computer networks, making it easier to predict the movements of vehicles. Machine learning can be employed in training algorithms from the very beginning to detect malicious exploits by differentiating normal from acute driving behavior which alerts the driver and prevents an attack.

In order to realize this, NXP is taking the lead in manufacturing microcontrollers with AI and machine learning capabilities that can be plugged into the OBD-II port. This not only observes but also allows the device to capture the vehicles’ data patterns to detect and monitor any abnormalities. Once it’s monitored, the microcontroller basically tries to prevent and alert the driver and becomes the replacement for traditional algorithms employed in vehicles.

Autonomous Driving is Not the Distant Future

It’s important to realize that autonomous vehicles that aren’t prioritizing security will cause far more serious consequences that involve physical harm or could even be abused by rogue nations and terrorists that are looking to cause chaos. Therefore, different security technologies must be considered when designing the security architecture from the very beginning.

Also, machine learning can become an essential tool for OEMs, Tier-1 suppliers, or manufacturers that are looking to secure their autonomous vehicle and driving-related resources. After all, the new transportation system will need a total security solution that covers from intelligent transport system to in-vehicle, charging and connections security.

AUTOCRYPT’s Automotive Cybersecurity Solutions

AUTOCRYPT provides a total vehicle security solution that secures all parts of a vehicle by providing various security modules such as firewalls, authentication systems, to secure the vehicle from end to end.

To keep informed with the latest news on mobility tech and automotive cybersecurity, subscribe to AUTOCRYPT’s monthly newsletter.