AIMC Topic: Built Environment

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JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments.

IEEE transactions on pattern analysis and machine intelligence May 8, 2023
We present JRDB, a novel egocentric dataset collected from our social mobile manipulator JackRabbot. The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360 RGB video at 15 fps, 3D point clouds from two 1...
Humans Algorithms Built Environment Visual Perception Robotics Benchmarking
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Does Deep Learning Enhance the Estimation for Spatially Explicit Built Environment Stocks through Nighttime Light Data Set? Evidence from Japanese Metropolitans.

Environmental science & technology Feb 21, 2023
Built environment stocks have attracted much attention in recent decades because of their role in material and energy flows and environmental impacts. Spatially refined estimation of built environment stocks benefits city management, for example, in ...
Built Environment Deep Learning Cities Japan Industry
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A Design Framework of Exploration, Segmentation, Navigation, and Instruction (ESNI) for the Lifecycle of Intelligent Mobile Agents as a Method for Mapping an Unknown Built Environment.

Sensors (Basel, Switzerland) Sep 1, 2022
Recent work on intelligent agents is a popular topic among the artificial intelligence community and robotic system design. The complexity of designing a framework as a guide for intelligent agents in an unknown built environment suggests a pressing ...
Artificial Intelligence Learning Built Environment Algorithms
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Measuring Perceived Psychological Stress in Urban Built Environments Using Google Street View and Deep Learning.

Frontiers in public health May 11, 2022
An urban built environment is an important part of the daily lives of urban residents. Correspondingly, a poor design can lead to psychological stress, which can be harmful to their psychological and physical well-being. The relationship between the ...
Built Environment Search Engine Republic of Korea Humans Deep Learning Stress, Psychological
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Application of an adapted FMEA framework for robot-inclusivity of built environments.

Scientific reports Mar 1, 2022
Mobile robots are deployed in the built environment at increasing rates. However, lack of considerations for a robot-inclusive planning has led to physical spaces that would potentially pose hazards to robots, and contribute to an overall productivit...
Built Environment Humans Robotics
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Visual Evaluation of Urban Streetscape Design Supported by Multisource Data and Deep Learning.

Computational intelligence and neuroscience Feb 7, 2022
This paper integrates classical design theory, multisource urban data, and deep learning to explore an accurate analytical framework in a new data environment, providing a scientific analysis path for the "where" and "how" of greenways in a high-dens...
Walking Built Environment Environment Design Deep Learning Residence Characteristics
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Prediction of pedestrian-vehicle conflicts at signalized intersections based on long short-term memory neural network.

Accident; analysis and prevention Oct 17, 2020
Pedestrian protection is an important component of road safety. Intersections are dangerous locations for pedestrians with mixed traffic. This paper aims to predict potential traffic conflicts between pedestrians and vehicles at signalized intersecti...
Humans Safety Pattern Recognition, Automated Pedestrians Built Environment Neural Networks, Computer Accidents, Traffic
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The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms.

Accident; analysis and prevention Jul 2, 2020
In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was revised with the C4.5 decision tree (DT) algorithm, were applied to the classification of cyclist injury-severity in bicycle-vehicle accidents. The study aims to...
Injury Severity Score Built Environment Bicycling Accidents, Traffic Sex Factors Fuzzy Logic Humans
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Automated traffic incident detection with a smaller dataset based on generative adversarial networks.

Accident; analysis and prevention Jun 20, 2020
An imbalanced and small training sample can cause an incident detection model to have a low detection rate and a high false alarm rate. To solve the scarcity of incident samples, a novel incident detection framework is proposed based on generative ad...
Research Design Support Vector Machine Humans Built Environment Sample Size Accidents, Traffic
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The importance of flow composition in real-time crash prediction.

Accident; analysis and prevention Jan 31, 2020
Previous real-time crash prediction models have scarcely used data disaggregated by vehicle type such as light, heavy and motorcycles. Thus, little effort has been made to quantify the impact of flow composition variables as crash precursors. We anal...
Chile Logistic Models Accidents, Traffic Built Environment Humans Motorcycles Support Vector Machine
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