Eyes in Motion: A New Traffic Sensing Paradigm for Pedestrians and Cyclists

A.A. Vial

doi:10.4233/uuid:e9cc7cc5-227c-464c-8d46-cb1b4073b7a2

Eyes in Motion: A New Traffic Sensing Paradigm for Pedestrians and Cyclists

A.A. Vial

Transport, Mobility and Logistics

Research output: Thesis › Dissertation (TU Delft)

154 Downloads (Pure)

Abstract

The deployment of moving sensor platforms (e.g., self-driving cars, drones, and other instances) with advanced sensing is rapidly increasing the capture of human features at unprecedented temporal and spatial scales, especially in cities. This thesis advances knowledge on extracting information from this novel data source for traffic research and practice, while highlighting implications for privacy and beyond. Findings provide insights for traffic control and management, policy development, and anyone involved in responsible urban innovation.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Delft University of Technology
Supervisors/Advisors	Hoogendoorn, S.P., Promotor van Arem, B., Promotor Daamen, W., Promotor
Award date	1 May 2025
Print ISBNs	978-90-5584-366-4
DOIs	https://doi.org/10.4233/uuid:e9cc7cc5-227c-464c-8d46-cb1b4073b7a2
Publication status	Published - 2025

Keywords

Mobile sensor systems
Pedestrians and cyclists
Active modes
Moving sensor platforms
Connected autonomous vehicles
Intelligent autonomous systems
Data collection
Data fusion
Real-time systems
Trajectory reconstruction
Multiple target tracking
Road networks
Traffic data
Mobility
Traffic monitoring and control
Advanced traffic management systems
Privacy
Surveillance

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.4233/uuid:e9cc7cc5-227c-464c-8d46-cb1b4073b7a2

PhDThesis_AVial_finalv1.2_tudrepositoryFinal published version, 12.2 MB

Cite this

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title = "Eyes in Motion: A New Traffic Sensing Paradigm for Pedestrians and Cyclists",

abstract = "The deployment of moving sensor platforms (e.g., self-driving cars, drones, and other instances) with advanced sensing is rapidly increasing the capture of human features at unprecedented temporal and spatial scales, especially in cities. This thesis advances knowledge on extracting information from this novel data source for traffic research and practice, while highlighting implications for privacy and beyond. Findings provide insights for traffic control and management, policy development, and anyone involved in responsible urban innovation.",

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AB - The deployment of moving sensor platforms (e.g., self-driving cars, drones, and other instances) with advanced sensing is rapidly increasing the capture of human features at unprecedented temporal and spatial scales, especially in cities. This thesis advances knowledge on extracting information from this novel data source for traffic research and practice, while highlighting implications for privacy and beyond. Findings provide insights for traffic control and management, policy development, and anyone involved in responsible urban innovation.

KW - Mobile sensor systems

KW - Pedestrians and cyclists

KW - Active modes

KW - Moving sensor platforms

KW - Connected autonomous vehicles

KW - Intelligent autonomous systems

KW - Data collection

KW - Data fusion

KW - Real-time systems

KW - Trajectory reconstruction

KW - Multiple target tracking

KW - Road networks

KW - Traffic data

KW - Mobility

KW - Traffic monitoring and control

KW - Advanced traffic management systems

KW - Privacy

KW - Surveillance

U2 - 10.4233/uuid:e9cc7cc5-227c-464c-8d46-cb1b4073b7a2

DO - 10.4233/uuid:e9cc7cc5-227c-464c-8d46-cb1b4073b7a2

M3 - Dissertation (TU Delft)

SN - 978-90-5584-366-4

T3 - TRAIL Thesis Series, The Netherlands Research School TRAIL

ER -

Eyes in Motion: A New Traffic Sensing Paradigm for Pedestrians and Cyclists

Abstract

Keywords

UN SDGs

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