# Situationally Sensitive Path Planning
## 6 Results
### Dynamic Situations and Path Variation  
Out of these preferences, the DIRT condition appears to have the most consistent effect of causing pedestrians to alternatively choose other paths, rather than follow a single alternative corridor as seen in S-RISK. In this situation, a small minority of pedestrians opt to \"throw away\" trash behind them as they walk. The subsequent build-up of trash articles in the scene appears to have caused agents to prefer alternative corridors without any trash. Though trash articles are scripted to disappear 40 s after they spawn, a space-time wave/lagging effect on path choice is nonetheless observed. In other words, subsequent pedestrians end up reacting to the perception of the situation that was encountered by pedestrians that came before them, much like in traffic jams. To explain the cause of divergent path preferences, we look towards S-RISK and D-RISK, both of which feature agents only choosing the right-hand side corridor in Figure 4A. We consider this to be an artifact of our choice of Dijkstra as the base for the model, rather than an indicator of emergent behavior among agents. Specifically, under an assumed  
Figure 5: Velocity streams and Kernel density estimations (KDEs) that demonstrate crowd movement across time. Subplot columns represent the agents’ preference being tested, while subplot rows represent six frames equally spaced across a 3 min timespan. Each individual subplot geographically represents the 10 m \(\times\) 40 m virtual space. Agents are directed to start in the south and move northward. tie-break situation where the cost of traveling to either right-hand-side or left-hand-side corridor is equal (agents are in between and have no collisions or local situational sensitivity factors that are relevant to their choice), agents will pick the right-hand-side path as a default. (Colloquially, this mimics decades of literature showing that the peculiarity of pedestrians' tendencies to move to the right when all else is equal, regardless of whether they are right-handed or whether people drive on the right-hand side of the road.) In the case of S-RISK, the dog remains stationary in the center of the map. Thus, with no other recourse and personality factors affecting path choice, agents will divert to the right-hand side. D-RISK sees similar behavior where agents will pick either the central or right corridors depending on the location of the dog. When trash is dynamically added to the scene, the pedestrians that divert to the right may begin to throw trash in the right corridor: this creates geographical inertia for that sensitivity factor. As the global environment manifold detects these instances, subsequent agents will begin to prefer the left corridor. In cyclical fashion, the end of the simulation sees agents beginning to prefer the right path once more after all agents begin to move to the left, leaving behind trash. This sequence of events, sourced in behavior, illustrates how macro-scale phenomena such as path dependence and lock-in can form from small and very local (a banana peel) sensitivities as agents' reactions accumulate around them. Because the trash in our simulations has a temporary physical manifestation on the ground, it acts in ways that approach stigmergy in insect behavior, e.g., akin to pheromone trails. We also note the prevalence of pedestrians still choosing to follow the central corridor in D-RISK and DENSITY situations. Alternatively, S-RISK and DIRT demonstrate sizeable populations of pedestrians opting for the side corridors. In fact, DIRT appears to have the most varied pedestrian distribution across all individual factors. While some variation is visibly noticeable in DENSITY, most agents prefer the central corridor. Again, this has basis in the theoretical literature, especially in urban design and the concept of space syntax, which advocates the primacy of preserving viewsheds in pedestrian movement along sidewalks in cities.