# Jam Mitigation for Autonomous Convoys via Behavior-Based Robotics
###### Abstract
This paper investigates developing an autonomous convoy system that mitigates the effects of jamming attacks. We aim to create an autonomous convoy that does not inherently rely on any Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) network communications by design, creating a highly scalable system that is robust to system error and loss of communications by using only the on-board sensors of each vehicle. A behavior-based robotics architecture is used to facilitate the employment of simpler sensors and reduce the reliance on complex planning with world models. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Title** & **Authors** & **Summary** \\ \hline Path Planning for Multiple & & Perform shape formation \\ Unmanned Vehicles (MUVs) & [PERSON], [PERSON]; [PERSON], [PERSON]; & generation with multiple \\ Formation Shape Generation & Song, Jianhui & unmanned vehicles using \\ Based on Dual RRT & & rapidly-exploring random trees to \\ Optimization [15] & & plan vehicle paths during \\ \hline Research on Self-Organizing & & \\ Behavior-Based UAV & [PERSON], [PERSON]; [PERSON], Li; & information with self-organizing \\ Formation Based on & [PERSON], Niu & behaviors with a quasi-static \\ Distributed Control [16] & & communication topological \\ \hline Autonomous Vehicle Convoy & & Development of a convoy \\ Formation Control with & & \\ Size/Shape Switching for & & \\ Automated Highways [17] & & \\ \hline Behavior-Based Formation & & \\ Control for Multirobot & & \\ Teams [18] & & \\ \hline Decentralized behavior-based & & \\ formation control of multiple & & \\ robots considering obstacle & & \\ avoidance [19] & & \\ \hline A Sequential Composition & & \\ Framework for Coordinating & & \\ Multirobot Behaviors [20] & & \\ \end{tabular}
\end{table} 
Table 1: Prior work in convoying and formation control. The contributions of this paper are as follows:  
* This paper develops control-oriented countermeasures against jamming attacks on autonomous vehicle convoys that are independent of traditional radio anti-jamming techniques. This allows for layers of protection against jamming at both the network and convoy controller level, improving the robustness and performance of an overall convoy system when confronted with jamming. * This paper creates an architecture for behavior-based robotics that is uniquely integrated with the Robot Operating System (ROS) framework. This architecture combined a Motor Schema behavior-based robotics with the ROS navigation stack to a depth that had not previously been seen, paving the path for the greater ROS community to leverage behavior-based robotic architectures. * The jamming-proof motion planning in this paper improves upon the basic Motor Schema approach by integrating it with vector field histogram motion planning, allowing us to avoid the pitfalls of potential field motion planning. The remainder of the paper is organized as follows: Section 2 provides background on autonomous ground vehicle convoys, jammers, and behavior based robotics; Sections 3 and 4 discusses the materials and methods used, including the behavior-based robotics architecture, algorithms, and design of experiment; Section 4 shows the results to quantify the performance differences between autonomous ground convoy systems when jam mitigation is present; and Section 5 contains the final discussions and conclusions.