Peer Reviewed

Informal and emergent organizations play a vital role in disaster response, and are a central concern to crisis informatics. Prior research in the field has tended to focus on the activities of individual organizations during periods of disaster. Though unsurprising, this focus has led to limited understanding of the origins and long-term trajectories of these organizations or their participation in broader networks of informal response, whose individual membership, ideologies, and practices are often fluid and overlapping. In this paper, we examine the activities of informal organizations that mobilized in response to the 2015 earthquake in Nepal. Drawing on semi-structured interviews with 17 participants, we identify five categories of resources - funding, people, information, skills, and shared values - that these organizations mobilized to sustain themselves and continue their activities long after the immediate disaster abated. We contribute insights into the adaptation decisions of emergent organizations, guidance in understanding these decisions in relation to their social and historical context, and considerations for how long-term, network-oriented studies can help address some of the contemporary challenges in crisis-informatics research.

Open Data has become a prominent ideal in humanitarian information work and is increasingly promoted for crisis situations to increase effectiveness, accountability, and empower citizens. However, like all socio-technical systems, open data platforms for disasters make implicit and explicit assumptions about data, data users, disasters, and the context of use. In this paper, we turn to feminist theory to examine three open data projects rolled out in the aftermath of the 2015 earthquake in Nepal. We used the seven principles of Data Feminism introduced by D'Ignazio and Klein to design an evaluative framework for the three projects. We use this framework to highlight and link the socio-political nature of both disasters and open data platforms. In our results, we highlight significant gaps in how these projects made labor (in)visible, engaged with affective aspects of disaster, addressed context, and challenged power. We argue that these gaps are reflective of dominant practices in open data for disasters and serve as opportunities for designers and crisis informatics researchers to reimagine the potential of such projects. We propose four ways of doing so based on feminist principles and values.

This paper introduces the Buffered Input Cell as a reciprocal collision avoidance method for multiple vehicles with high-order linear dynamics, extending recently proposed methods based on the Buffered Voronoi Cell [1] and generalized Voronoi diagrams [2]. We prove that if each vehicle's control input remains in its Buffered Input Cell at each time step, collisions will be avoided indefinitely. The method is fast, reactive, and only requires that each vehicle measures the relative position of neighboring vehicles. We incorporate this collision avoidance method as one layer of a complete lane change control stack for autonomous cars in a freeway driving scenario. The lane change control stack comprises a decision-making layer, a trajectory planning layer, a trajectory following feedback controller, and the Buffered Input Cell for collision avoidance. We show in simulations that collisions are avoided with multiple vehicles simultaneously changing lanes on a freeway. We also show in simulations that autonomous cars using the BIC method effectively avoid collisions with an aggressive human-driven car.