A Parameter Privacy-Preserving Strategy for Mixed-Autonomy Platoon Control
Jingyuan Zhou, Kaidi Yang

TL;DR
This paper introduces a privacy-preserving parameter filter for mixed-autonomy platoon control, protecting human-driven vehicle data while maintaining control performance through innovative distortion and neural network techniques.
Contribution
It proposes a novel parameter privacy filter integrated into leading cruise control, extending to continuous parameters with neural networks, and analyzes its impact on traffic stability.
Findings
Effective privacy-performance trade-off demonstrated in simulations
Neural network estimator enables privacy preservation in continuous parameters
Potential impact on string stability analyzed
Abstract
It has been demonstrated that leading cruise control (LCC) can improve the operation of mixed-autonomy platoons by allowing connected and automated vehicles (CAVs) to make longitudinal control decisions based on the information provided by surrounding vehicles. However, LCC generally requires surrounding human-driven vehicles (HDVs) to share their real-time states, which can be used by adversaries to infer drivers' car-following behavior, potentially leading to financial losses or safety concerns. This paper aims to address such privacy concerns and protect the behavioral characteristics of HDVs by devising a parameter privacy-preserving approach for mixed-autonomy platoon control. First, we integrate a parameter privacy filter into LCC to protect sensitive car-following parameters. The privacy filter allows each vehicle to generate seemingly realistic pseudo states by distorting the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTraffic control and management · Vehicular Ad Hoc Networks (VANETs)
MethodsLipschitz Constant Constraint
