Contesting neoliberalism in an ‘activist city’: working towards the urban commons in Berlin

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Contesting austerity, de-centring the state : anti-politics and the political horizon of the urban

This article draws novel links between ‘anti-politics’, austerity and a political horizon centred on the urban. Research on anti-politics often invokes a binary understanding of a politics of and within the state and an anti-politics at a distance from or hostile towards the state. This article argues that in the context of austerity, this binary loses traction. Austerity has intensified the transformation towards networked forms of governance within which the state becomes a more hybrid entity of contradictory ideals and practices. Austerity not only calls into question the legitimacy of formal politics because of its devastating social outcomes, it also disaggregates the political authority of the state and opens up a particularly urban terrain of politics. We capture this development by examining the intersections between the local state and the urban field of politics. Looking across the struggles against austerity in Europe, and focusing in more detail on housing politics in Berlin, we assert that the urban is important not only as a setting (as typically argued) but also as the basis for a different rationality of political action in and against austerity. In the context of austerity struggles, state authority becomes ever more contingent and other, more urban, forms of politics advance. In sum, the article contributes to a spatial reading of (anti-)politics against austerity, points to the de-centring of the state in transformative political projects and emphasizes the analytical purchase of a distinctly urban perspective on contemporary politics in Europe

Contesting austerity, de-centring the state: anti-politics and the political horizon of the urban

This article draws novel links between ‘anti-politics’, austerity and a political horizon centred on the urban. Research on anti-politics often invokes a binary understanding of a politics of and within the state and an anti-politics at a distance from or hostile towards the state. This article argues that in the context of austerity, this binary loses traction. Austerity has intensified the transformation towards networked forms of governance within which the state becomes a more hybrid entity of contradictory ideals and practices. Austerity not only calls into question the legitimacy of formal politics because of its devastating social outcomes, it also disaggregates the political authority of the state and opens up a particularly urban terrain of politics. We capture this development by examining the intersections between the local state and the urban field of politics. Looking across the struggles against austerity in Europe, and focusing in more detail on housing politics in Berlin, we assert that the urban is important not only as a setting (as typically argued) but also as the basis for a different rationality of political action in and against austerity. In the context of austerity struggles, state authority becomes ever more contingent and other, more urban, forms of politics advance. In sum, the article contributes to a spatial reading of (anti-)politics against austerity, points to the de-centring of the state in transformative political projects and emphasizes the analytical purchase of a distinctly urban perspective on contemporary politics in Europe

Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction

In this paper, we present an end-to-end future-prediction model that focuses on pedestrian safety. Specifically, our model uses previous video frames, recorded from the perspective of the vehicle, to predict if a pedestrian will cross in front of the vehicle. The long term goal of this work is to design a fully autonomous system that acts and reacts as a defensive human driver would --- predicting future events and reacting to mitigate risk. We focus on pedestrian-vehicle interactions because of the high risk of harm to the pedestrian if their actions are miss-predicted. Our end-to-end model consists of two stages: the first stage is an encoder/decoder network that learns to predict future video frames. The second stage is a deep spatio-temporal network that utilizes the predicted frames of the first stage to predict the pedestrian's future action. Our system achieves state-of-the-art accuracy on pedestrian behavior prediction and future frames prediction on the Joint Attention for Autonomous Driving (JAAD) dataset