An official website of the United States government
The visual control of locomotion has been modeled for individual pedestrian behavior; however, this approach has not been applied to collective human behavior, where spontaneous pattern formation is often observed. We hypothesize that an empirical visual model of human locomotion will reproduce the emergent pattern of lanes and stripes observed in crossing flows, when two groups of pedestrians walk through each other at crosswalks or intersections. Mullick, et al. (2022) manipulated the crossing angle between two groups and found an invariant property: stripe orientation is perpendicular to the mean walking direction (i.e. 90˚ to the bisectrix of the crossing angle). Here we determine the combination of model components required to simulate human-like stripes: (i) steering to a goal (Fajen & Warren, 2003), (ii) collision avoidance with opponents (Bai, 2022; Veprek & Warren, VSS 2023), and (iii) alignment with neighbors (Dachner, et al., 2022), together called the SCruM (Self-organized Collective Motion) model. We performed multi-agent simulations of the data from Mullick et al. (2022), using fixed parameters and initial conditions from the dataset. There were two sets of participants (N=36, 38) with 18 or 19 per group. Crossing angle varied from 60˚ to 180˚ (30˚ intervals), with ~17 trials per condition. The minimal model necessary to reproduce stripe formation consists of the goal and collision avoidance components. Mean stripe orientation did not differ from 90˚ to the bisectrix (BF10 < 0.01, decisive). However, the SD of heading during crossing was significantly larger than the human data (p<0.001), whereas the SD of speed was significantly smaller (p<0.001). Thus, the ratio of heading/speed adjustments is lower than previously found, implying the need to reparameterize model components for walking in groups. In sum, steering to a goal and collision avoidance are sufficient to explain stripe formation in crossing flows, while alignment is unnecessary.
more »
« less
Singular Foliations for Knit Graph Design
We build upon the stripes-based knit planning framework of [Mitra et al. 2023], and view the resultant stripe pattern through the lens of singular foliations. This perspective views the stripes, and thus the candidate course rows or wale columns, as integral curves of a vector field specified by the spinning form of [Knöppel et al. 2015]. We show how to tightly control the topological structure of this vector field with linear level set constraints, preventing helicing of any integral curve. Practically speaking, this obviates the stripe placement constraints of [Mitra et al. 2023] and allows for shifting and variation of the stripe frequency without introducing additional helices. En route, we make the first explicit algebraic characterization of spinning form level set structure within singular triangles, and replace the standard interpolant with an “effective” one that improves the robustness of knit graph generation. We also extend the model of [Mitra et al. 2023] to surfaces with genus, via a Morse-based cylindrical decomposition, and implement automatic singularity pairing on the resulting components.
more »
« less
- Award ID(s):
- 2327137
- PAR ID:
- 10526097
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400705250
- Page Range / eLocation ID:
- 1 to 11
- Subject(s) / Keyword(s):
- Computer-aided manufacturing computational knitting foliations
- Format(s):
- Medium: X
- Location:
- Denver CO USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Fu, Feng (Ed.)When two streams of pedestrians cross at an angle, striped patterns spontaneously emerge as a result of local pedestrian interactions. This clear case of self-organized pattern formation remains to be elucidated. In counterflows, with a crossing angle of 180°, alternating lanes of traffic are commonly observed moving in opposite directions, whereas in crossing flows at an angle of 90°, diagonal stripes have been reported. Naka (1977) hypothesized that stripe orientation is perpendicular to the bisector of the crossing angle. However, studies of crossing flows at acute and obtuse angles remain underdeveloped. We tested the bisector hypothesis in experiments on small groups (18-19 participants each) crossing at seven angles (30° intervals), and analyzed the geometric properties of stripes. We present two novel computational methods for analyzing striped patterns in pedestrian data: (i) an edge-cutting algorithm, which detects the dynamic formation of stripes and allows us to measure local properties of individual stripes; and (ii) a pattern-matching technique, based on the Gabor function, which allows us to estimate global properties (orientation and wavelength) of the striped pattern at a time T . We find an invariant property: stripes in the two groups are parallel and perpendicular to the bisector at all crossing angles. In contrast, other properties depend on the crossing angle: stripe spacing (wavelength), stripe size (number of pedestrians per stripe), and crossing time all decrease as the crossing angle increases from 30° to 180°, whereas the number of stripes increases with crossing angle. We also observe that the width of individual stripes is dynamically squeezed as the two groups cross each other. The findings thus support the bisector hypothesis at a wide range of crossing angles, although the theoretical reasons for this invariant remain unclear. The present results provide empirical constraints on theoretical studies and computational models of crossing flows.more » « less
-
Abstract Pruning is showing huge potential for compressing and accelerating deep neural networks by eliminating redundant parameters. Along with more terminal chips integrated with AI accelerators for internet of things (IoT) devices, structured pruning is gaining popularity with the edge computing research area. Different from filter pruning and group-wise pruning, stripe-wise pruning (SWP) conducts pruning at the level of stripes in each filter. By introducing filter skeleton (FS) to each stripe, the existing SWP method sets an absolute threshold for the values in FS and removes the stripes whose corresponding values in FS could not meet the threshold. Starting with investigation into the process of stripe wise convolution, we use the statistical properties of the weights located on each stripe to learn the importance between those stripes in a filter and remove stripes with low importance. Our pruned VGG-16 achieves the existing results by a fourfold reduction in parameter with only 0.4% decrease in accuracy. Results from comprehensive experiments on IoT devices are also presented.more » « less
-
Abstract Directed self-assembly of block copolymers (BCPs) enables nanofabrication at sub-10 nm dimensions, beyond the resolution of conventional lithography. However, directing the position, orientation, and long-range lateral order of BCP domains to produce technologically-useful patterns is a challenge. Here, we present a promising approach to direct assembly using spatial boundaries between planar, low-resolution regions on a surface with different composition. Pairs of boundaries are formed at the edges of isolated stripes on a background substrate. Vertical lamellae nucleate at and are pinned by chemical contrast at each stripe/substrate boundary, align parallel to boundaries, selectively propagate from boundaries into stripe interiors (whereas horizontal lamellae form on the background), and register to wide stripes to multiply the feature density. Ordered BCP line arrays with half-pitch of 6.4 nm are demonstrated on stripes >80 nm wide. Boundary-directed epitaxy provides an attractive path towards assembling, creating, and lithographically defining materials on sub-10 nm scales.more » « less
-
Santhanam, Rahul (Ed.)The recent breakthrough of Limaye, Srinivasan and Tavenas [Limaye et al., 2022] (LST) gave the first super-polynomial lower bounds against low-depth algebraic circuits, for any field of zero (or sufficiently large) characteristic. It was an open question to extend this result to small-characteristic ([Limaye et al., 2022; Govindasamy et al., 2022; Fournier et al., 2023]), which in particular is relevant for an approach to prove superpolynomial AC⁰[p]-Frege lower bounds ([Govindasamy et al., 2022]). In this work, we prove super-polynomial algebraic circuit lower bounds against low-depth algebraic circuits over any field, with the same parameters as LST (or even matching the improved parameters of Bhargav, Dutta, and Saxena [Bhargav et al., 2022]). We give two proofs. The first is logical, showing that even though the proof of LST naively fails in small characteristic, the proof is sufficiently algebraic that generic transfer results imply the result over characteristic zero implies the result over all fields. Motivated by this indirect proof, we then proceed to give a second constructive proof, replacing the field-dependent set-multilinearization result of LST with a set-multilinearization that works over any field, by using the Binet-Minc identity [Minc, 1979].more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3641519.3657487
