# Jam Mitigation for Autonomous Convoys via Behavior-Based Robotics
## 4 Results
As seen in Table 4, the utilization of the FLJM assemblage also improved convoy performance across both path plans when compared to the basic convoy controller under random jamming. When following the squared loop path, using the FLJM assemblage decreased the average MAE by 31.62% for follower 1 and 23.67% for follower 2. Improvement was exhibited with the roundabout path as well, where the average MAE was decreased by 61.85% and 13.33% for follower 1 and follower 2, respectively. While the utilization of the FLJM assemblage yielded similar performance across both the constant and random jammers, the performance improvements when compared to the basic convoy controller were less significant under random jamming attacks. This is due to the nature of random jammers, which alternate between a jamming and sleeping state. Rather than missing all the convoy leader's waypoints in a jamming zone, as in the case of constant jamming, the follower vehicles would periodically receive network transmissions from the jamming zone under random jamming, allowing for occasional transmission of waypoints inside the jammed area. This can be seen when comparing the  
Figure 18: Plot of the paths taken by the followers under random jamming on the square path for (**a**) follower 1 and (**b**) follower 2; and on the roundabout path for (**c**) follower 1 and (**d**) follower 2.  
basic convoy controller paths in Figures 17 and 18. In Figure 17, the basic convoy controller followers stop outside of the jamming zones and only restart following when the convoy leader exits the constant jamming zone. In Figure 18 however, the followers are able to break into the random jamming zone and follow the occasional waypoints they receive when the jammer is sleeping. These results demonstrate that the value of using jamming mitigation techniques increases accordingly with the severity of the jamming attack. As previously stated, constant jamming is considered the worst-case jamming scenario with the most damaging impact, so the potential benefits afforded by using the FLJM assemblage is greater when compared to a random jamming attack, as seen in the experimental results described here. While the results described here were focused on the constant and random jammer attack model developed for this effort, the performance benefits provided by the FLJM assemblage would be realized even when applied to other attacker models. Various other attacker models have focused on reactive jammers with assumptions of global eavesdropping, zero-delay jamming startup, and unbounded frequency jamming [9; 48]. With these attacker models, the FLJM assemblage performance would match that of our constant jammer, given that the reactive jamming occurs instantaneously when entering the jammed areas and disrupts all communications, which closely aligns with our model for constant jamming. Other attacker models have additional parameters for their reactive jammers, such as jamming range, triggering range, and multiple jammer nodes, but they make the same uniform power and omnidirectionality of jamming assumptions we made in our model, resulting in the same cylindrical jamming zones [28]. While the notion of multiple jamming zones introduces coverage areas of different shapes due to overlapping cylinders, the performance improvements from using the FLJM assemblage will remain due to the reactive jammer closely aligning with our constant jamming model. In addition, other attacker models have focused on more dynamic jamming scenarios, such as the jammer being embedded in one of the convoy's follower vehicles [7]. In this attacker model, a follower vehicle in a convoy would switch from a standard network node into a uniform power mobile jammer that prevented messages from arriving at their destination. Assuming the mobile jammer continues following its leader to disguise its adversarial nature, the FLJM assemblage would once again allow for continued convoy operations.