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Pedestrians

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A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

Sensors (Basel, Switzerland)
This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a ...

On-Board Detection of Pedestrian Intentions.

Sensors (Basel, Switzerland)
Avoiding vehicle-to-pedestrian crashes is a critical requirement for nowadays advanced driver assistant systems (ADAS) and future self-driving vehicles. Accordingly, detecting pedestrians from raw sensor data has a history of more than 15 years of re...

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

Accident; analysis and prevention
Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual int...

The Moral Machine experiment.

Nature
With the rapid development of artificial intelligence have come concerns about how machines will make moral decisions, and the major challenge of quantifying societal expectations about the ethical principles that should guide machine behaviour. To a...

Robot-Assisted Pedestrian Regulation Based on Deep Reinforcement Learning.

IEEE transactions on cybernetics
Pedestrian regulation can prevent crowd accidents and improve crowd safety in densely populated areas. Recent studies use mobile robots to regulate pedestrian flows for desired collective motion through the effect of passive human-robot interaction (...

Forecasting Pedestrian Movements Using Recurrent Neural Networks: An Application of Crowd Monitoring Data.

Sensors (Basel, Switzerland)
Currently, effective crowd management based on the information provided by crowd monitoring systems is difficult as this information comes in at the moment adverse crowd movements are already occurring. Up to this moment, very little forecasting tech...

Pedestrian's risk-based negotiation model for self-driving vehicles to get the right of way.

Accident; analysis and prevention
Negotiations among drivers and pedestrians are common on roads, but it is still challenging for a self-driving vehicle to negotiate for its right of way with other human road users, especially pedestrians. Currently, the self-driving vehicles are pro...

A Dynamic Part-Attention Model for Person Re-Identification.

Sensors (Basel, Switzerland)
Person re-identification (ReID) is gaining more attention due to its important applications in pedestrian tracking and security prevention. Recently developed part-based methods have proven beneficial for stronger and explicit feature descriptions, b...

Development of pedestrian crash prediction model for a developing country using artificial neural network.

International journal of injury control and safety promotion
Urban intersections in India constitute a significant share of pedestrian fatalities. However, model-based prediction of pedestrian fatalities is still in a nascent stage in India. This study proposes an artificial neural network (ANN) technique to d...

Person Reidentification via Unsupervised Cross-View Metric Learning.

IEEE transactions on cybernetics
Person reidentification (Re-ID) aims to match observations of individuals across multiple nonoverlapping camera views. Recently, metric learning-based methods have played important roles in addressing this task. However, metrics are mostly learned in...