Context models for pedestrian intention prediction by factored latent-dynamic conditional random fields

Smooth handling of pedestrian interactions is a key requirement for Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS). Such systems call for early and accurate prediction of a pedestrian's crossing/not-crossing behaviour in front of the vehicle. Existing approaches to pedes...

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Bibliographic Details
Main Author: Satyajit Neogi
Other Authors: Justin Dauwels
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/143222
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Institution: Nanyang Technological University
Language: English