Heterogeneous CACC Coexistence: Simulation, Analysis, and Modeling
Lorenzo Ghiro, Marco Franceschini, Renato Lo Cigno, Michele Segata

TL;DR
This paper investigates the safety and performance of heterogeneous vehicle platoons with mixed Cooperative Adaptive Cruise Control algorithms through simulation, revealing which combinations are robust and highlighting the need for better modeling frameworks.
Contribution
It introduces the concept of mixed platoons with heterogeneous CACCs and provides a simulation-based analysis of their safety and efficiency, addressing a gap in existing research.
Findings
Some CACC combinations operate safely and robustly.
Certain mixtures show critical safety and comfort limitations.
Heterogeneous platoons impact traffic throughput and safety.
Abstract
The design of Cooperative Adaptive Cruise Control (CACC) algorithms for vehicle platooning has been extensively investigated, leading to a wide range of approaches with different requirements and performance. Most existing studies evaluate these algorithms under the assumption of homogeneous platoons, i.e., when all platoon members adopt the same CACC. However, market competition is likely to result in vehicles from different manufacturers implementing distinct CACCs. This raises fundamental questions about whether heterogeneous vehicles can safely cooperate within a platoon and what performance can be achieved. To date, these questions have received little attention, as heterogeneous platoons are difficult to model and analyze. In this work, we introduce the concept of mixed platoons, i.e., platoons made of vehicles running heterogeneous CACCs, and we study their performance through…
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 · Traffic Prediction and Management Techniques · Transportation Planning and Optimization
