Electronics and Semiconductors

How hacked self-driving cars could impact traffic

05 March 2019
When just a few vehicles are hacked, more areas of Manhattan in this scenario become inaccessible from the other. When somewhere between 10 to 20 percent of vehicles are hacked in rush hour, it becomes even worse. Source: Georgia Institute of Technology

Self-driving cars have yet to debut in the automotive market, but that isn’t stopping research from being done on the possibility of problems emerging from these connected vehicles becoming simultaneously disabled by criminals.

Safety in self-driving vehicles has become a paramount concern after the death of a pedestrian who was struck by a self-driving Uber in Arizona last year. Since then, concern over the safety of these vehicles has reached a fever pitch with numerous automotive OEMs announcing plans to focus on safety first as well as government regulations established to sort out the safety issues of autonomous driving before the cars come to market.

Now, a study from the Georgia Institute of Technology has examined how a large-scale hack of self-driving cars might affect an urban setting.

Researchers used agent-based simulations to investigate how hacks could impact traffic flow in New York City. Georgia Institute of Technology along with Multiscale Systems Inc. developed a mathematical approach based on the statistical analysis of networks to quantify how these scenarios would play out in New York in real time.

Compromised vehicles do not behave like compromised data. The vehicles present physical danger to not just the occupants but to the overall traffic flow in an urban environment. The team found that even with a small-scale hack, affecting only 10% of vehicles in Manhattan, could cause citywide gridlock and hinder emergency services. Larger scale hacks have yet to be quantified but could go beyond just individual collisions, researchers said.

Based on the findings, the team was able to develop a risk-mitigation strategy to prevent mass urban disruption from compromised self-driving cars. This includes using multiple networks for connected vehicles to decrease the number of cars that could be compromised in a single intrusion. If only 5% of self-driving cars were connected to the same network, the chances of citywide fragmentation would be low. When faced with this compartmentalized multi-network architecture, a hacker intent on causing large-scale disruption would be required to execute multiple simultaneous intrusions, making it much more difficult to orchestrate such an attack and less likely for one to occur.

"Connected cars are the future," said Skanda Vivek, a postdoctoral researcher in the Peter Yunker lab at the Georgia Institute of Technology. "They hold tremendous potential for positive impact economically, environmentally, and, for former drivers no longer frustrated by congested commutes, psychologically. Our work is not in opposition to the future of connected cars. Rather, the novelty of our work lies in identifying and quantifying the underlying cyber-physical risks when multiple connected vehicles are compromised. By shining a light on these technologies at an early stage, we hope we can help prevent worst-case-scenarios."

To contact the author of this article, email PBrown@globalspec.com


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