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Full-Text Articles in Automotive Engineering

Intelligent Roadside Unit Deployment In Vehicular Network, Xiangyu Xu Dec 2020

Intelligent Roadside Unit Deployment In Vehicular Network, Xiangyu Xu

Masters Theses

Intelligent Transportation System (ITS) has been an important research area in building the foundational infrastructures of self-driving vehicles and improving traffic efficiency of future transportation systems. Scientists have been hoping to incorporate intelligence into traditional transportation systems to help reduce the risks, accident rates, traffic congestion, and even environmental emissions.

There are many research works that have been focused on the communication part of ITS, such as vehicular networks, which collect data from vehicles and send it to the cloud for analysis. In the vehicular networks, Roadside Unit (RSU) is a key infrastructure as an intermediate layer between the vehicles …


Radio Direction Finding Using Pseudo-Doppler For Uav-Based Animal Tracking, Anup Karki Dec 2019

Radio Direction Finding Using Pseudo-Doppler For Uav-Based Animal Tracking, Anup Karki

Masters Theses

Radio Direction Finding (RDF) is commonly used for low cost tracking and navigation systems. However, for a low cost application and mobility, the design constraints are highly limited. Pseudo Doppler (PD) can improve RDF capabilities without being cost prohibitive. This work entails the analysis of PD RDF and its potential use for Unmanned Aerial Vehicles (UAV) that are currently employed in wildlife research animal tracking. PD is based on the doppler effect or doppler shift. The doppler effect works like a frequency modulator that increases or decreases the observed frequency depending on whether a signal source is approaching or receding …


Object Detection, Classification, And Tracking For Autonomous Vehicle, Milan Aryal Dec 2018

Object Detection, Classification, And Tracking For Autonomous Vehicle, Milan Aryal

Masters Theses

The detection and tracking of objects around an autonomous vehicle is essential to operate safely. This paper presents an algorithm to detect, classify, and track objects. All objects are classified as moving or stationary as well as by type (e.g. vehicle, pedestrian, or other). The proposed approach uses state of the art deep-learning network YOLO (You Only Look Once) combined with data from a laser scanner to detect and classify the objects and estimate the position of objects around the car. The Oriented FAST and Rotated BRIEF (ORB) feature descriptor is used to match the same object from one image …