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Pedestrian Behavior Prediction Using Deep Learning Methods for Urban Scenarios: A Review

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Support systems for cyclists in automated traffic: A review and future outlook

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Interdisciplinary Industrial Design Strategies for Human-Automation Interaction: Industry Experts’ Perspectives

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Learning the Pedestrian-Vehicle Interaction for Pedestrian Trajectory Prediction

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Unequally Yoked [Skilled]: Transformative Views on Human-Automation Skilfulness.

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Understanding the interaction between cyclists and automated vehicles: Results from a cycling simulator study

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Vulnerable road users and the coming wave of automated vehicles: Expert perspectives

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Perceived safety and predictability of human/AV interactions : Deliverable 1.2 in the EC ITN project SHAPE-IT

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Towards Understanding Pedestrian Behavior Patterns from LiDAR Data

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

An overview of current AV interface strategies (inside/outside)

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Augmented reality interfaces for pedestrian-vehicle interactions: An online study.

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Triangulating the future: Developing scenarios of cyclist-automated vehicle interactions from literature, expert perspec...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Immersive insights: Evaluating augmented reality interfaces for pedestrians in a CAVE-based experiment.

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

From Driver to Supervisor: Comparing Cognitive Load and EEG-Based Attentional Resource Allocation Across Automation Leve...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

User comfort and naturalness of automated driving: The effect of vehicle kinematics and proxemics on subjective response

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Behavioural models explaining and predicting transparent negotiations between AVs and human road users : Deliverable 2.2...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

How do cyclists interact with motorized vehicles at unsignalized intersections? Modeling cyclists’ yielding behavior u...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Human factors in developing automated vehicles: A requirements engineering perspective

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Human-machine interface evaluation using EEG in driving simulator

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Methodological Framework for Modelling and Empirical Approaches (Deliverable D1.1 in the H2020 MSCA ITN project SHAPE-IT...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Drivers' Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural?

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Spatial-Temporal-Spectral LSTM: A Transferable Model for Pedestrian Trajectory Prediction

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Ambient Light Conveying Reliability Improves Drivers’ Takeover Performance without Increasing Mental Workload

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Fatigue and mental underload further pronounced in L3 conditionally automated driving: Results from an EEG experiment on...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Long-term behavioural adaptation and learning curve of humans interacting with AVs : Deliverable 1.3 in the EC ITN proje...

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Phantom braking in automated vehicles: A theoretical outline and cycling simulator demonstration

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Exploring turn signal usage patterns in lane changes: A Bayesian hierarchical modelling analysis of realistic driving da...

Project: Shape-IT

Updated at: 28-04-2024

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A comparison of two methodologies for subjective evaluation of comfort in automated vehicles

Project: Shape-IT

Updated at: 28-04-2024

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Project acronym Shape-IT

Resources

Selected filters:

Pedestrian Behavior Prediction Using Deep Learning Methods for Urban Scenarios: A Review

Support systems for cyclists in automated traffic: A review and future outlook

Interdisciplinary Industrial Design Strategies for Human-Automation Interaction: Industry Experts’ Perspectives

Learning the Pedestrian-Vehicle Interaction for Pedestrian Trajectory Prediction

Unequally Yoked [Skilled]: Transformative Views on Human-Automation Skilfulness.

Understanding the interaction between cyclists and automated vehicles: Results from a cycling simulator study

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles

Vulnerable road users and the coming wave of automated vehicles: Expert perspectives

Perceived safety and predictability of human/AV interactions : Deliverable 1.2 in the EC ITN project SHAPE-IT

Towards Understanding Pedestrian Behavior Patterns from LiDAR Data

An overview of current AV interface strategies (inside/outside)

Augmented reality interfaces for pedestrian-vehicle interactions: An online study.

Triangulating the future: Developing scenarios of cyclist-automated vehicle interactions from literature, expert perspec...

Immersive insights: Evaluating augmented reality interfaces for pedestrians in a CAVE-based experiment.

From Driver to Supervisor: Comparing Cognitive Load and EEG-Based Attentional Resource Allocation Across Automation Leve...

User comfort and naturalness of automated driving: The effect of vehicle kinematics and proxemics on subjective response

Behavioural models explaining and predicting transparent negotiations between AVs and human road users : Deliverable 2.2...

How do cyclists interact with motorized vehicles at unsignalized intersections? Modeling cyclists’ yielding behavior u...

Human factors in developing automated vehicles: A requirements engineering perspective

Human-machine interface evaluation using EEG in driving simulator

Methodological Framework for Modelling and Empirical Approaches (Deliverable D1.1 in the H2020 MSCA ITN project SHAPE-IT...

Drivers' Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural?

Spatial-Temporal-Spectral LSTM: A Transferable Model for Pedestrian Trajectory Prediction

Ambient Light Conveying Reliability Improves Drivers’ Takeover Performance without Increasing Mental Workload

Fatigue and mental underload further pronounced in L3 conditionally automated driving: Results from an EEG experiment on...

Long-term behavioural adaptation and learning curve of humans interacting with AVs : Deliverable 1.3 in the EC ITN proje...

Phantom braking in automated vehicles: A theoretical outline and cycling simulator demonstration

Exploring turn signal usage patterns in lane changes: A Bayesian hierarchical modelling analysis of realistic driving da...

A comparison of two methodologies for subjective evaluation of comfort in automated vehicles