Lateral String Stability for Vehicle Platoons
2026-06-29 • Robotics
Robotics
AI summaryⓘ
The authors focus on how cars driving closely together (platooning) can stay safe by keeping side-to-side errors from growing down the line of vehicles. While many studies looked at keeping the cars stable front-to-back, this paper studies how errors sideways on the path spread and how that affects safety. The authors introduce a new way to measure these lateral errors using a path-based viewpoint and propose two methods: one using just each car's sensors and another using data shared between cars. They find that relying only on sensors isn't enough to reduce errors safely, but sharing information between vehicles helps prevent the errors from getting worse.
Connected and Automated Vehicles (CAV)PlatooningString StabilityLateral String StabilityPath-Tracking ErrorsOnboard SensingVehicle-to-Vehicle Communication (V2V)Eulerian Arc-Length ViewpointControl StrategiesSafety in Autonomous Vehicles
Authors
Sixu Li, Swaroop Darbha, Yang Zhou
Abstract
Connected and automated vehicle (CAV) platooning promises gains in energy efficiency and traffic throughput and, most critically, in safety. These safety benefits hinge on string stability, which determines how disturbances propagate along a platoon. While longitudinal string stability is well studied, lateral string stability, which governs the propagation of path-tracking errors that can lead to unsafe deviations from the intended path, remains underexplored. Its importance is increasing as autonomous vehicles rely more heavily on onboard sensing and map-free navigation, where sensor occlusion and dense formations amplify safety risks. This paper presents a new framework for lateral string stability that directly addresses safety-critical path-relative tracking errors and enables consistent comparison across vehicles following the same road geometry. Central to this framework is an arc-length (Eulerian) viewpoint, a departure from traditional analyses, that clarifies how tracking errors at a given point on the path propagate from one vehicle to the next. A formal definition of lateral string stability is introduced along with two control strategies: an onboard-sensing-only controller and a novel learn-from-predecessor approach utilizing vehicle-to-vehicle (V2V) communication. We show that onboard sensing alone cannot guarantee attenuation of path-tracking errors, imposing a fundamental safety limitation, whereas V2V communication enables true error attenuation.