ILU: A technology to help improve Urban Mobility
INESC-ID is developing a project in partnership with National Civil Engineering Laboratory, Câmara Municipal de Lisboa (Lisbon Municipality), and the major public carriers in the Lisbon metropolitan area with the aim of aligning urban mobility plans with the emerging traffic dynamics.
The ILU project (Integrative Learning from Urban Data and Situational Context for City Mobility Optimization) aims to improve mobility in Lisbon by analyzing heterogeneous sources of traffic data produced by ticketing systems, stationary road sensors, and mobile devices; therefore: 1) supporting the transparency of urban mobility plans to the citizen; 2) offering a solid ground for coordination efforts among municipalities and public transport operators; and 3) ensuring the public transport system responds to the ongoing city transformations and changes observed in a pandemic context.
To this end, the ILU APP, a pioneer recommendation system that integrates the main computational contributions of the project, is being developed. ILU APP offers a multimodal, dynamic and context-sensitive analysis of urban traffic, combining five main features:
- automatic consolidation of urban data sources from public transport operators and PGIL (platform for intelligent management in Lisbon) with potential impact on the city traffic analysis, with particular attention to the provision of: efficient cross-modal spatiotemporal queries, Big Data visualization utilities, dynamic updates, mappings into data structures conducive to the subsequent machine learning tasks, and the inference of incomplete traffic flows, including alighting stop estimates in the CARRIS network;
- descriptive analytics for detecting vulnerabilities and ongoing changes to mobility in the city, focusing on:
– statistically significant traffic patterns, including: (a) frequent and periodic patterns indicative of overcrowding or congestion; (b) emerging traffic patterns that may reveal future vulnerabilities; (c) deviant patterns including anomalous variations in demand; (d) multimodal traffic synergies; and (e) correlations present in multiple sources of urban traffic;
– dynamic inference of multimodal origin-destination matrices, allowing the detection of vulnerabilities in the network, including transfer needs and long journey times;
- predictive analytics of traffic flows from various data sources, using innovative associative learning and deep learning principles. The facilities are provided within a solid statistical frame, enabling forecasts of road traffic or demand on the public transport network to be made with guarantees of significance and variability;
- analytics sensitive to different sources of situational context, in particular the extension of the previous description and forecasting facilities for the study of traffic dynamics in the presence of historical and prospective context, including: (a) planned events (such as sport matches and cultural events), (b) weather forecasts, and (c) interdictions on public roads;
- optimization facilities based on the previous data-centric models of traffic for: (a) adjusting the public transportation network by revising vehicle routing and frequency; and (b) designing intelligent traffic light control systems at specific city junctures. In this context, the ILU project is combining control and micro-simulation principles with advances from deep reinforcement learning.
The recommendation system will be delivered in the form of a functional prototype to the project’s public partners – CML, CARRIS and METRO – to support their: (a) strategic decisions related to the city mobility; and (b) real-time operational decisions, including the signaling of the ongoing vulnerabilities in the mobility system.
These contributions are expected to reveal untapped multimodal synergies and promote a sustainable urban mobility, giving priority for public transport options and the integration of active travel modes. Moreover, the modular, dynamic, and online nature of the devised contributions ensures their interoperability and scalability to other cities in the current pandemic era.
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ILU: A tecnologia a contribuir para melhorar a Mobilidade Urbana
O INESC-ID está a desenvolver um projeto em parceria com a Câmara Municipal de Lisboa e o Laboratório Nacional de Engenharia Civil que visa contribuir para melhorar a Mobilidade Urbana.
O projeto iLU (Integrative Learning from Urban Data and Situational Context for City Mobility Optimization) visa melhorar a mobilidade em Lisboa a partir da análise de dados da circulação automóvel e de transportes públicos. Pretende-se descobrir padrões de circulação na cidade, antecipar problemas e fazer recomendações.
O INESC-ID está a desenvolver um projeto em parceria com o Laboratório Nacional de Engenharia Civil, a Câmara Municipal de Lisboa, e transportadoras na área metropolitana de Lisboa com o objetivo de alinhar os planos de Mobilidade Urbana com as emergentes dinâmicas de tráfego.
O projeto ILU (Integrative Learning from Urban Data and Situational Context for City Mobility Optimization) visa melhorar a mobilidade em Lisboa através da análise de dados de tráfego produzidos por sistemas de bilhetagem na rede de transportes públicos, sensores rodoviários estacionários, e dispositivos móveis; visando: 1) apoiar a transparência dos planos de mobilidade urbana para o cidadão; 2) fortalecer a coordenação entre municípios e operadoras de transporte público a partir das vistas centradas nos dados; e 3) garantir que o sistema de transporte público responde às transformações em curso na cidade e às mudanças estruturas observadas em contextos pandémicos.
Para tal, foi desenvolvida a ILU APP, um sistema de recomendação pioneiro que integra as principais contribuições computacionais do projeto. A ILU APP oferece uma análise multimodal, dinâmica e sensível ao contexto do tráfego urbano, combinando cinco características principais:
- consolidação automática de fontes de dados urbanos presentes nos operadores de transportes públicos e disponibilizados na PGIL (plataforma para gestão inteligente em Lisboa), tendo particular atenção à disponibilização de facilidades de visualização, procuras eficientes, atualização dinâmica dos dados, mapeamentos em estruturas de dados conducivas às subsequentes tarefas de aprendizagem, e à inferência de fluxos de tráfego incompletos, incluindo estimativas do desembarque por passageiro na rede CARRIS;
- analítica descritiva para detectar vulnerabilidades e contínuas alterações à mobilidade na cidade, com foco em:
– padrões de tráfego estatisticamente significativos, incluindo: (a) padrões frequentes e periódicos indicativos de congestionamento ou sobrelotação; (b) padrões emergentes capazes de antecipar vulnerabilidades futuras; (c) padrões desviantes incluindo variações anómalas na procura; (d) sinergias multimodais no tráfego; e (e) correlações presentes nas múltiplas fontes de tráfego urbano;
– inferência dinâmica de matrizes de origem-destino multimodais, permitindo a detecção de vulnerabilidades na rede, incluindo necessidades de transbordo e durações elevadas de viagem;
- análise preditiva de fluxos de tráfego a partir de várias fontes de dados, usando princípios inovadores de aprendizagem associativa e aprendizagem profunda. As facilidades disponibilizadas têm um enquadramento estatístico sólido, permitindo realizar previsões do tráfego rodoviário ou de procura na rede pública de transportes com garantias de significância e variabilidade;
- análises sensíveis a diferentes fontes de contexto situacional, em particular estendo as anteriores facilidades de descrição e previsão para o estudo da dinâmicas de tráfego na presença de contexto histórico e prospectivo, incluindo: (a) eventos planeados (desportivos e culturais), (b) registos e previsões meteorológicas, e (c) interdições em vias públicas;
- optimizadores com base nos modelos de tráfego centrados em dados anteriores para: (a) ajustar a rede de transporte público revendo o roteamento e a frequência dos veículos; e (b) desenhar sistemas de controle de semáforos inteligentes em cruzamentos específicos na cidade. Nesse contexto, o projeto ILU combina princípios de controlo e micro-simulação com avanços em aprendizagem profunda com reforço.
O sistema de recomendação será entregue sob a forma de um protótipo funcional aos parceiros públicos do projeto – CML, CARRIS e METRO – por forma a apoiar: (a) decisões estratégicas ligadas ao planeamento da mobilidade na cidade; e (b) decisões operacionais em tempo real, incluindo a sinalização de vulnerabilidades ou necessidades de reforço à oferta.
Esperamos que estas contribuições revelem sinergias multimodais desconhecidas, promovendo uma mobilidade urbana mais sustentável, prioritizando as opções de transporte público e a integração de meios de transporte ativo (mobilidade pedonal, cicloviável, e partilhada). Além disso, a natureza modular e dinâmica das contribuições garante a sua extensão a outras cidades de Portugal e no mundo.
Upcoming Events
OLISSIPO Workshop: “How to design a graphical abstract” with Dr. Rita Félix (CNC-UC)
On April 19, the OLISSIPO project will host an 8-hour workshop titled “How to design a graphical abstract” with Dr. Rita Félix, a science communicator, illustrator and designer from CNC Center for Neuroscience and Cell Biology (Coimbra, Portugal). Registration is free and seating is limited.
Registration Deadline: April 5 | Register here (free but mandatory)
Date & Time: April 19, 09h00-18h00 ( 8-hours)
Where: INESC-ID, R. Alves Redol 9, 1000-029 Lisboa | Room 9 (Auditorium), Ground Floor
Summary: “How to design a graphical abstract” Workshop aims to explain what a graphical abstract is, and give you design tools and tips on how to create a better, clear and engaging graphical abstract. This workshop is tailored to give you tools and improve your graphical abstract, without having to learn how to use a new software program (like Adobe Illustrator). Bring your graphical abstract, share it with the class, work on it and take home a new version.
Short Bio: Rita Félix is a science communicator, illustrator and designer, with life sciences research experience. Currently working as the Institutional Communication Manager and Designer at CNC-UC. She completed her PhD in Neuroscience in 2020, in the Champalimaud Neuroscience Programme. After that, she enrolled in a Digital Illustration Specialization Course to further develop her visualization and design skills. Worked as a Scientific Graphic Designer at Science Crunchers, a science communication company, where she developed multiple graphical abstracts, article figures, infographics, diagrams, illustrations, visual identity, logos and webdesign for companies, scientific institutions and Horizon 2020 consortia. More information at https://ritallfelix.wixsite.com/portfolio .
INESC-ID talk: “Rise of the AI-Empowered End User Software Engineer” by Ed Ayers and Andy Gordon (Cogna)
On April 19, INESC-ID will host a talk by Ed Ayers and Andy Gordon from the startup Cogna. The talk is titled “Rise of the AI-Empowered End User Software Engineer” and is organised by INESC-ID researcher Nuno Lopes.
Date & Time: April 19, 15h00 -16h00
Where: INESC-ID, Rua Alves Redol, 9, 1000-029 Lisboa | Room 9 (Auditorium), Ground Floor
Summary:
“What if natural language really is the new programming language? Inspired by the transformation of professional software engineering by generative AI, let’s take the next step: empowering end users. We can boost their productivity with hyper-customized software generated from natural language. This challenge needs research right across software engineering: requirements, architecture, coding, testing, verification, repair, and maintenance. We will survey current progress and open research questions in this exciting new area of programming language research.”
(Photo: Cogna website)
Técnico Open Day 2024
Técnico Open Day 2024
On April 20, Instituto Superior Técnico will host the Técnico Open Day 2024, at the Alameda Campus. The event will consist of a science fair, guided visits, and interaction with members of the IST community.
Date & Time: April 20, 10h00-17h00
Where: Instituto Superior Técnico – Alameda Campus (Free Entry)
Summary: The 2024 edition of the Técnico Open Day will count with over 60 activities within the science fair, guided visits to the campus, including teaching and research laboratories, and contact with professors, researchers and students from IST. The event will be an opportunity to hold an interactive exhibition, displaying more than 40 research and innovation projects, and allowing all attendees to become more familiar with the School and its initiatives.
EV4EU will be part of the Open Day “Science Fair”, representing the project at the INESC-ID info stand from 10am to 5pm. Project researchers Cindy P. Guzman and Larissa Montefusco will be at the Info booth to share with visitors an overview of the project, its main goals and latest developments. Under the title “Electric Vehicles Management for Carbon Neutrality: Discover how Electrical Vehicles can contribute to the fight against climate change”, the EV4EU team will focus on explaining how can EV4EU plan solutions, and support the massification of electrical vehicles while contributing to the decrease of carbon emissions and global warming.
Full agenda of the event here
Know more about the project here
Educational Workshop on Responsible AI for Peace and Security (UNODA)
On June 6 and 7, The United Nations Office for Disarmament Affairs (UNODA) and the Stockholm International Peace Research Institute (SIPRI) are offering a selected group of technical students the opportunity to join a 2-day educational workshop on Responsible AI for peace and security.
The third workshop in the series will be held in Porto Salvo, Portugal, in collaboration with GAIPS, INESC-ID, and Instituto Superior Técnico. The workshop is open to students affiliated with universities in Europe, Central and South America, the Middle East and Africa, Oceania, and Asia.
Date & Time: June 6 a 7
Where: IST – Tagus Park, Porto Salvo
Registration deadline: April 8
Summary: “As with the impacts of Artificial intelligence (AI) on people’s day-to-day lives, the impacts for international peace and security include wide-ranging and significant opportunities and challenges. AI can help achieve the UN Sustainable Development Goals, but its dual-use nature means that peaceful applications can also be misused for harmful purposes such as political disinformation, cyberattacks, terrorism, or military operations. Meanwhile, those researching and developing AI in the civilian sector remain too often unaware of the risks that the misuse of civilian AI technology may pose to international peace and security and unsure about the role they can play in addressing them. Against this background, UNODA and SIPRI launched, in 2023, a three-year educational initiative on Promoting Responsible Innovation in AI for Peace and Security. The initiative, which is supported by the Council of the European Union, aims to support greater engagement of the civilian AI community in mitigating the unintended consequences of civilian AI research and innovation for peace and security. As part of that initiative, SIPRI and UNODA are organising a series of capacity building workshops for STEM students (at PhD and Master levels). These workshops aim to provide the opportunity for up-and-coming AI practitioners to work together and with experts to learn about a) how peaceful AI research and innovation may generate risks for international peace and security; b) how they could help prevent or mitigate those risks through responsible research and innovation; c) how they could support the promotion of responsible AI for peace and security.”