<var>What if your car was as vulnerable to hack into as your laptop? The reality is cars today are basically a computer on wheels. According to Car and Driver, 40 percent of a new car&rsquo;s cost is driven by electronic components. The New York Times reported that a modern vehicle could contain more than 3,000 computer chips. Electronics are such an essential part of a car&rsquo;s design that the shortage of semiconductors due to supply chain disruption from the pandemic has impacted auto assembly lines worldwide, creating a lack of new vehicles on the market.</var> 
 
By introducing computer systems into vehicles, hackers have found ways to exploit their vulnerabilities. In 2015, Black Hat security researchers Charlie Miller and Chris Valasek hacked a Jeep Cherokee via its infotainment system. Miller and Valasek exploited how the vehicle autogenerated its Wi-Fi password based on the time when the car&rsquo;s multimedia system would turn on. Through the infotainment system, the hackers could manipulate the air conditioner, the radio, the windshield wipers, and even the transmission. On a road test with Wired magazine, the hackers cut the transmission as the vehicle was driving 70 mph on the highway. This past February, German teenager David Colombo identified a vulnerability in the TeslaMate, a third-party application used by Tesla owners to analyze car performance. By hacking the app, Colombo was able to unlock doors, turn on and off the headlights, and control the radio. He was even able to track in real-time the location of the car. 
 
<img alt="" src="~/getmedia/5329b926-0216-4ace-bdb7-ec2d9631e42a/cyber1@2x.jpg" /> 
<var>&ldquo;We have connected vehicles today that exposed multiple internet access points to the internet. There is the infotainment system, but also smart sensors and various devices connected to smart roads and smart cities,&rdquo; said Francesco Pascale, solution lead of embedded IIoT and device management at Almaviva Digitaltec.</var> 
 
Pascale, along with Marco Lombardi and Domenico Santaniello, professors at the Department of Industrial Engineering at the University of Salerno, recently authored a study on how cyberattacks can be detected in connected vehicles. The study &ldquo;Two-Step Algorithm to Detect Cyber-Attack Over the Can-Bus: A Preliminary Case Study in Connected Vehicles&rdquo; was published in the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. The paper highlights how connected vehicles today receive over-the-air updates, transmit diagnostic information, and provide streaming entertainment options. These vehicle-to-everything connections make many cars vulnerable to being hacked. &ldquo;Some types of cyberattacks can be targeted to take possession of sensitive data, but the most dangerous ones, as seen in past years, can aim to compromise the car motor functions or, even worse, to take possession of it while driving. It is not difficult to think that autonomous vehicles can become attractive targets for hackers in the not-too-distant future,&rdquo; Pascale said. Last year, the European Union Agency for Cybersecurity (ENSIA) published the Cybersecurity Challenges in the Uptake of Artificial Intelligence in Autonomous Driving report, highlighting the security challenges future autonomous vehicles face and how the artificial intelligence systems can be exploited. Possible attack scenarios include tampering with the car&rsquo;s computer vision, jamming or blinding the sensors, hijacking communication channels, and information disclosure. To help identify these attacks, Pascale, Lombardi, and Santaniello propose to analyze the data flow that moves via the communication channels between various electronic control units (ECUs) inside the vehicle CAN-Bus, the internal communication system. Using a two-step algorithm that first performs a spatial-temporal analysis of the data and then a probabilistic analysis, the algorithm can understand if a given stream of data in a particular time box can be considered an attack or not with a certain probability. 
 
<img alt="" src="~/getmedia/f2df193b-96e5-44bb-a29b-ed7445863ad5/cyber2@2x.jpg" /> 
 
&ldquo;This methodology has been expanded to include the recognition of real-world scenarios, such as city traffic, driving on a motorway, extra-urban roads with animals, etc., in order to have even more precision and accuracy in the analysis,&rdquo; Pascale said. The current algorithm is part of the Italian patent n.102021000009548, soon extending internationally. The patent will become part of MinervaS, a startup organization creating solutions for vehicles and energy systems, promoted by the University of Salerno. The global market for automotive cybersecurity is expected to increase significantly over the next decade. The projected market value will reach $5.3 billion by 2026. Drivers want smart and connected cars, providing detailed information about their trips and entertainment while driving. Companies such as SafeRide and Synopsys offer cybersecurity suites that help protect vehicles from cyber threats. According to Pascale, dealing with cyberattacks is a delicate approach. &ldquo;An immediate solution could be to exclude the node that generated the attack from the system (virtually disconnect the ECU from the CAN-Bus). However, this solution is not always applicable because, at times, it could be a node belonging to a critical system such as everything concerning the mechanics of the vehicle; if the attack is carried out while driving, this would involve a risk for the health of people at the internal of the same,&rdquo; Pascale said. Another approach could be to block the vehicle to avoid possible damage automatically. However, the problem with this approach is that if the attack targets a non-critical part, blocking the car may not be warranted. According to Pascale, &ldquo;the right approach would be to consider the weight of the attack with respect to the node that is attacked and evaluate the risk associated with each and on the basis of that foresee targeted actions.&rdquo; As cars become smarter and more connected, cybersecurity will continue to play an essential role in vehicles and their safety. 
 
&nbsp;

New research from the University of Salerno provides methods on how to detect and protect connected vehicles from cyberattacks.

<var>What if your car was as vulnerable to hack into as your laptop? The reality is cars today are basically a computer on wheels. According to Car and Driver, 40 percent of a new car&rsquo;s cost is driven by electronic components. The New York Times reported that a modern vehicle could contain more than 3,000 computer chips. Electronics are such an essential part of a car&rsquo;s design that the shortage of semiconductors due to supply chain disruption from the pandemic has impacted auto assembly lines worldwide, creating a lack of new vehicles on the market.</var> 
 
By introducing computer systems into vehicles, hackers have found ways to exploit their vulnerabilities. In 2015, Black Hat security researchers Charlie Miller and Chris Valasek hacked a Jeep Cherokee via its infotainment system. Miller and Valasek exploited how the vehicle autogenerated its Wi-Fi password based on the time when the car&rsquo;s multimedia system would turn on. Through the infotainment system, the hackers could manipulate the air conditioner, the radio, the windshield wipers, and even the transmission. On a road test with Wired magazine, the hackers cut the transmission as the vehicle was driving 70 mph on the highway. This past February, German teenager David Colombo identified a vulnerability in the TeslaMate, a third-party application used by Tesla owners to analyze car performance. By hacking the app, Colombo was able to unlock doors, turn on and off the headlights, and control the radio. He was even able to track in real-time the location of the car.

Advancing Cybersecurity in Connected Vehicles

<var>Lidar, or light detection and ranging, is a popular remote sensing method used for measuring the exact distance to an object. These imaging systems are increasingly used in the development of autonomous vehicles (AVs). However, final technology implementation cannot yet be achieved because major AV manufacturers are only now starting to select providers for data collection units that can be introduced in commercial vehicles.</var>

One of the biggest unknowns in the development of AVs is how adverse weather conditions challenge the development of safe and reliable advanced autonomous systems for sensing and perception. How does the diffraction of light through rain, fog, and snow limit lidar performance? 
 
Although many AV developers are hopeful that automotive lidar sensors will be safe and effective in all weather conditions, a quantitative analysis of these effects is lacking. Currently, testing for autonomous vehicles is primarily performed in sunny environments. Testing conducted in good weather cannot be assumed to correlate directly with performance quality under extreme weather conditions, which could result in false detection caused by the backscattered intensity, thereby reducing the reliability of the sensor. Thus, the sensitivity of lidar to weather is a major drawback to commercialization. 
 
To help resolve this issue, researchers at Frostburg State University in Frostburg, Md., led by Jamil Abdo, associate professor of mechanical engineering and department chair, tested lidar sensors in adverse weather to understand how extreme weather impacts lidar performance. 
 
<img alt="" src="~/getmedia/b2a54a21-306a-4e32-ba61-9b2045095f9a/selfdriving1@2x.jpg" /> 
<var>The results were presented in &ldquo;Effective Range Assessment of Lidar Imaging Systems for Autonomous Vehicles Under Adverse Weather Conditions with Stationary Vehicles&rdquo; in ASME&rsquo;s Journal of Risk and Uncertainty in Engineering Systems.</var>

<h4>Approach and Methodology</h4>

Abdo and his team designed an experiment to evaluate lidar performance under adverse weather conditions. Data sets were recorded under these conditions to determine the effective range to estimate the maximum range at which the lidar sensors can return points. 
 
The testing set-up and algorithms were developed for two commercial lidar sensors&mdash;Velodyne VLP-32 and Ouster OS1-32. Weather resistance of the set-up was an important consideration. The weatherproof platform was designed so that the sensors units were located about three feet high off the ground. 
 
We wrote programs to interface with these lidar units and to analyze the data,&rdquo; Abdo said. &ldquo;These programs allowed us to count the number of points in a region of space.&rdquo; 
 
The team selected a remote area for testing to ensure that other cars did not drive by, affecting the data. The test was also designed to meet the goals of ease of testing and reproducibility in testing locations. 
 
&ldquo;Even though the western Maryland area around Frostburg is a great location for testing, it was very hard to have a reproducible weather condition,&rdquo; Abdo said. &ldquo;We had to use design-of-experiment techniques to account for nondesirable factors such as noise during the testing.&rdquo; 
 
Abdo decided the best way to test the lidar units was in a worst-case scenario with two cars heading directly toward each other, recreated by driving a car straight toward the test platform. &ldquo;This is the worst-case scenario for car detection as when the car faces the lidar sensor, its cross-section is the smallest with respect to the sensor,&rdquo; Abdo said. 
 
Two types of tests were performed under various weather conditions. The first involved stationary tests where the car stopped every 7.5 meters for a few seconds before driving forward another 7.5 meters. The second method conducted testing with the car moving toward the lidar units at varying speeds of five mph, 10 mph, and 20 mph. 
 
Test results showed that both dense fog and heavy rain severely impacted lidar sensors&rsquo; object detection and operating range detection. Light rain had minimal effect on lidar performance, and snow had no negative impact. 
 
<img alt="" src="~/getmedia/37843adc-af7c-457e-b410-f484b00c2f6c/selfdriving2@2x.jpg" />

<h4>Moving Forward</h4>

Determining the influence of weather on lidar sensor performance is a critical step toward improving the safety levels for autonomous driving under adverse weather conditions &ldquo;because such analyses provide reliable information for adapting vehicle behavior,&rdquo; Abdo said. 
 
The AV industry has already taken notice of Abdo&rsquo;s work. Three major lidar manufacturers have contacted Abdo since he published the team&rsquo;s research/findings in September 2021, he said. The team has also received funds from Maryland Industrial Partners (MIPS) and Intelligent Fusion Company to support the second phase of research activities. 
 
For this work, &ldquo;Lidar performance in rain, snow, fog, smog, and dust will be investigated using dynamic sensors and moving targets,&rdquo; Abdo stated. &ldquo;We also plan to explore object tracking&mdash;for example, other vehicles and any potential obstacles&mdash;with lidar systems.&rdquo;

Explore how adverse weather conditions can impact autonomous vehicles&rsquo; lidar cameras.

<var>Lidar, or light detection and ranging, is a popular remote sensing method used for measuring the exact distance to an object. These imaging systems are increasingly used in the development of autonomous vehicles (AVs). However, final technology implementation cannot yet be achieved because major AV manufacturers are only now starting to select providers for data collection units that can be introduced in commercial vehicles.</var> 
One of the biggest unknowns in the development of AVs is how adverse weather conditions challenge the development of safe and reliable advanced autonomous systems for sensing and perception. How does the diffraction of light through rain, fog, and snow limit lidar performance?

How Self-Driving Cars See in Extreme Weather

Interview with Luca Capriotti

Luca Capriotti, former president of the International Youth Nuclear Congress, shares his passion for nuclear energy and beliefs that it can become a viable, safe power source to be used globally and responsibly in the future.

The Future of Power is Nuclear

Infographic: Sodium-Cooled Fast Reactor

&nbsp;
<div class="infogram-embed" data-id="_/GNZqhKYA24E6kz9OqOfZ" data-title="Infographic-RD Pulse-v02" data-type="interactive">&nbsp;</div>

<var>Most nuclear reactors in operation today use water as a coolant, but one promising alternative looks to replace water with liquid sodium. Sodium can be heated to high temperatures before boiling, which means that a sodium-cooled reactor can operate at atmospheric pressure and can use a thinner reactor vessel. These reactors also will produce less radioactive waste. Explore the diagram of a sodium-cooled fast reactor below.</var>

July-September 2022

In This Issue

article

Advancing Cybersecurity in Connected Vehicles

article

How Self-Driving Cars See in Extreme Weather

Get exclusive news from the engineering world

Q & A

The Future of Power is Nuclear

infographic

Sodium-Cooled Fast Reactor

Follow us!