INTRODUCTION
The following discussions are made on an organization, Waymo LLC, it is one of the
leading international American autonomous driving technology development company based in
US in 2009. It offers the products and services like self-driving taxi services. It mainly uses the
technical concept of artificial intelligence in their systems and productions. Company is relied on
the concept of AI because they want to apply the machine learning using google brain in its self-
driving cars. They have used the concept of deep learning to teach their cars a certain thing such
as nature of the objects on roads and understanding that how they actually react and response to
senses they feel due to the concept of artificial intelligence (Badue, Guidolini, Carneiro and de
Paula Veronese, 2020). Therefore, this report covers the review of four research papers such as
Rage against the machine? Google's self-driving cars versus human drivers, Autonomous Taxi
Service Design and User Experience, Self-Driving Cars: A Survey and Attitudes Toward
Autonomous on Demand Mobility System: The Case of Self-Driving Taxi. All are reviewed in
context of the Waymo LLC company with the questions which are addressed are exploring
datasets, proposal, research Problems solved, methodology used, merits, demerits, aspects
covered in literature review, formulation and justification of the work, claims by the author,
justification of such claims, comparative analysis, findings, contribution, importance of findings,
scope of improvement, ways to improve, future dimensions and review.
MAIN BODY
Research Paper 1 - Rage against the machine? Google's self-driving cars versus human drivers
Proposal Methodology used
It describes the both disadvantages and
advantages in highway safety of self-driving
cars. Google has been inventing self-driving cars
and experimenting them under worker direction
on open roads since 2009. These transports have
been included in various crashes, and it is of
involvement that how this experiment
programme is different from manlike drivers in
Google car crashes were coded by variety
and intensity which is dependent on narration
discharged by Google. Crash taxation per
million vehicle miles travelled - VMT were
calculated for crashes took in an intense
manner adequately to be reportable to police.
These were differentiated with police-
reported crash taxation for manlike drivers.
1

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Review of Self-Driving Taxi Research Papers

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