Performance Evaluation of a Lane Correction Module Stress Test: A Field Test of Tesla Model 3

Jonathan Lancelot, Bhaskar P. Rimal and Edward M. Dennis
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Jonathan Lancelot: The Beacom College of Computer and Cyber Sciences, Dakota State University, Madison, SD 57042, USA
Bhaskar P. Rimal: The Beacom College of Computer and Cyber Sciences, Dakota State University, Madison, SD 57042, USA
Edward M. Dennis: The Beacom College of Computer and Cyber Sciences, Dakota State University, Madison, SD 57042, USA

Future Internet, 2023, vol. 15, issue 4, 1-18

Abstract: This paper is designed to explicate and analyze data acquired from experimental field tests of a Tesla Model 3 lane correction module within the vehicle’s Autopilot Suite, a component of Tesla OS. The initial problem was discovered during a nominal drive of the Tesla Model 3, where after a random number of lane correction events, the lane correction module shuts down, issues a visual disable warning on the touchscreen, and control of the vehicle is given to the driver until the next drive. That development was considered problematic, as the driver can be caught off guard or may be medically disabled and unable to respond. During a controlled stress test, a more severe issue was discovered. After a random number of lane correction events, the lane correction module shuts down without warning, then stays activated after the test driver corrects the vehicle’s trajectory. This is considered a fatal error in the system and adds a dangerous element to an otherwise standard feature in a modern automotive vehicle. The results established that the number of events needed to trigger a fatal error without warning is unpredictable. Our results also demonstrate that the system is inconsistent.

Keywords: cybersecurity; physical security; human security; human safety; electric vehicles; Internet of Things (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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