1,719 research outputs found

    Human Motion Trajectory Prediction: A Survey

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    With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

    Mobility Design

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    Climate change and the scarcity of resources, but also the steadily increasing amount of traffic, make it indispensable to develop new solutions for environmentally friendly and people-friendly mobility. With the expansion of digital information systems, we will in future be able to easily combine different modes of transport according to our needs. These developments are a great challenge for the design of different mobility spaces. While the focus in Volume 1 was on practice, Volume 2 now brings together research from the fields of design, architecture, urban planning, geography, social science, transport planning, psychology and communication technology. The current discussion about the traffic turnaround is expanded to include the perspective of user-centred mobility design

    Crowdsensing-driven route optimisation algorithms for smart urban mobility

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    Urban rörlighet anses ofta vara en av de frĂ€msta möjliggörarna för en hĂ„llbar statsutveckling. Idag skulle det dock krĂ€va ett betydande skifte mot renare och effektivare stadstransporter vilket skulle stödja ökad social och ekonomisk koncentration av resurser i stĂ€derna. En viktig prioritet för stĂ€der runt om i vĂ€rlden Ă€r att stödja medborgarnas rörlighet inom stadsmiljöer medan samtidigt minska trafikstockningar, olyckor och föroreningar. Att utveckla en effektivare och grönare (eller med ett ord; smartare) stadsrörlighet Ă€r en av de svĂ„raste problemen att bemöta för stora metropoler. I denna avhandling nĂ€rmar vi oss problemet frĂ„n det snabba utvecklingsperspektivet av ITlandskapet i stĂ€der vilket möjliggör byggandet av rörlighetslösningar utan stora stora investeringar eller sofistikerad sensortenkik. I synnerhet föreslĂ„r vi utnyttjandet av den mobila rörlighetsavkĂ€nnings, eng. Mobile Crowdsensing (MCS), paradigmen i vilken befolkningen exploaterar sin mobilkommunikation och/eller mobilasensorer med syftet att frivilligt samla, distribuera, lokalt processera och analysera geospecifik information. RörlighetavkĂ€nningssdata (t.ex. hĂ€ndelser, trafikintensitet, buller och luftföroreningar etc.) inhĂ€mtad frĂ„n frivilliga i befolkningen kan ge vĂ€rdefull information om aktuella rörelsesförhĂ„llanden i stad vilka, med adekvata databehandlingsalgoriter, kan anvĂ€ndas för att planera mĂ€nniskors rörelseflöden inom stadsmiljön. SĂ„tillvida kombineras i denna avhandling tvĂ„ mycket lovande smarta rörlighetsmöjliggörare, eng. Smart Mobility Enablers, nĂ€mligen MCS och rese/ruttplanering. Vi kan dĂ€rmed till viss utstrĂ€ckning sammanföra forskningsutmaningar frĂ„n dessa tvĂ„ delar. Vi vĂ€ljer att separera vĂ„ra forskningsmĂ„l i tvĂ„ delar, dvs forskningssteg: (1) arkitektoniska utmaningar vid design av MCS-system och (2) algoritmiska utmaningar för tillĂ€mpningar av MCS-driven ruttplanering. Vi Ă€mnar att visa en logisk forskningsprogression över tiden, med avstamp i mĂ€nskligt dirigerade rörelseavkĂ€nningssystem som MCS och ett avslut i automatiserade ruttoptimeringsalgoritmer skrĂ€ddarsydda för specifika MCS-applikationer. Även om vi förlitar oss pĂ„ heuristiska lösningar och algoritmer för NP-svĂ„ra ruttproblem förlitar vi oss pĂ„ Ă€kta applikationer med syftet att visa pĂ„ fördelarna med algoritm- och infrastrukturförslagen.La movilidad urbana es considerada una de las principales desencadenantes de un desarrollo urbano sostenible. Sin embargo, hoy en dĂ­a se requiere una transiciĂłn hacia un transporte urbano mĂĄs limpio y mĂĄs eficiente que soporte una concentraciĂłn de recursos sociales y econĂłmicos cada vez mayor en las ciudades. Una de las principales prioridades para las ciudades de todo el mundo es facilitar la movilidad de los ciudadanos dentro de los entornos urbanos, al mismo tiempo que se reduce la congestiĂłn, los accidentes y la contaminaciĂłn. Sin embargo, desarrollar una movilidad urbana mĂĄs eficiente y mĂĄs verde (o en una palabra, mĂĄs inteligente) es uno de los temas mĂĄs difĂ­ciles de afrontar para las grandes ĂĄreas metropolitanas. En esta tesis, abordamos este problema desde la perspectiva de un panorama TIC en rĂĄpida evoluciĂłn que nos permite construir movilidad sin la necesidad de grandes inversiones ni sofisticadas tecnologĂ­as de sensores. En particular, proponemos aprovechar el paradigma Mobile Crowdsensing (MCS) en el que los ciudadanos utilizan sus telĂ©fonos mĂłviles y dispositivos, para nosotros recopilar, procesar y analizar localmente informaciĂłn georreferenciada, distribuida voluntariamente. Los datos de movilidad recopilados de ciudadanos que voluntariamente quieren compartirlos (por ejemplo, eventos, intensidad del trĂĄfico, ruido y contaminaciĂłn del aire, etc.) pueden proporcionar informaciĂłn valiosa sobre las condiciones de movilidad actuales en la ciudad, que con el algoritmo de procesamiento de datos adecuado, pueden utilizarse para enrutar y gestionar el flujo de gente en entornos urbanos. Por lo tanto, en esta tesis combinamos dos prometedoras fuentes de movilidad inteligente: MCS y la planificaciĂłn de viajes/rutas, uniendo en cierta medida los distintos desafĂ­os de investigaciĂłn. Hemos dividido nuestros objetivos de investigaciĂłn en dos etapas: (1) DesafĂ­os arquitectĂłnicos en el diseño de sistemas MCS y (2) DesafĂ­os algorĂ­tmicos en la planificaciĂłn de rutas aprovechando la informaciĂłn del MCS. Nuestro objetivo es demostrar una progresiĂłn lĂłgica de la investigaciĂłn a lo largo del tiempo, comenzando desde los fundamentos de los sistemas de detecciĂłn centrados en personas, como el MCS, hasta los algoritmos de optimizaciĂłn de rutas diseñados especĂ­ficamente para la aplicaciĂłn de estos. Si bien nos centramos en algoritmos y heurĂ­sticas para resolver problemas de enrutamiento de clase NP-hard, utilizamos ejemplos de aplicaciones en el mundo real para mostrar las ventajas de los algoritmos e infraestructuras propuestas

    Listening to bike lanes : Moving beyond the feud

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    The White Bicycle: Performance, Installation Art, and Activism in Ghost Bike Memorials

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    In this project I examine the performative nature of the ghost bike memorial. Ghost bikes, flat-white painted immobile bicycles created by cycling communities and loved ones of victims, are installed roadside to mark the locations of cycling related deaths. Using critical performance ethnography and critical-cultural analysis as methods, I analyze how the ghost bike performs as an artifact of mourning and inspires co-incident performances of grief, activism, and community building and maintenance. As a memorial object used worldwide to represent cycling culture, the ghost bike acts as a social network link that connects a multitude of diverse cycling communities. I present five case studies of ghost bikes in New York City, Durham, North Carolina, Baton Rouge, New Orleans, and Lafayette, Louisiana in order to dissect what the polysemic ghost bike communicates to public audiences. My analysis led to the discovery that ghost bikes are not only used as memorials. They also perform as metonyms for the absent, ruined bodies of cyclists; as markers of racial identity for victims; and as tools to reframe the narratives told about cycling-related deaths. I describe how the differing interpretations of the memorial are adapted to create and alter performances of identity, and I argue for the potential for these performances to influence perceptions about cycling safety, cycling-based legislation, and road infrastructure

    Urban Street Networks and Sustainable Transportation

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    Urban street space is challenged with a variety of emerging usages and users, such as various vehicles with different speeds, passenger pick-up and drop-off by mobility services, increasing parking demand for a variety of private and shared vehicles, new powertrains (e.g., charging units), and new vehicles and services fueled by digitalization and vehicle automation. These new usages compete with established functions of streets such as providing space for mobility, social interactions, and cultural and recreational activities. The combination of these functions makes streets focal points of communities that do not only fulfill a functional role but also provide identity to cities. Streets are prominent parts of cities and are essential to sustainable transport plans. The main aim of the Street Networks and Sustainable Transportation collection is to focus on urban street networks and their effects on sustainable transportation. Accordingly, various street elements related to mobility, public transport, parking, design, and movement of people and goods at the street level can be included

    Proceedings of the EAA Spatial Audio Signal Processing symposium: SASP 2019

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