Abstract

The rapid evolution of autonomous technology in the field of automotive and information technology (IT) has made it possible to implement autonomous vehicles (AVs) for public passenger transport. Although the shuttle bus transport capacities currently in use are low (maximum 15 people), the use of these transport units in large urban agglomerations is beneficial for society. The current paper is written to review the current AV implementation with respect to shuttle buses with its direct implications in their scientific evolution, with direct links to the legal and social aspects of public transportation all over the world. A critical aspect that is presented in the paper is the legal framework of autonomous driving, which is extremely uneven around the globe, with the direct impact of autonomous shuttle bus exploitation. As the legislation on AVs presents some shortcomings in the approval, registration, and public road implementation of these vehicles, many of the world’s major cities have found ways to integrate them into testing programs, establishing the basis for future comprehensive legislative measures in this highly dynamic scientific domain. The current technological solutions adopted by several autonomous shuttle bus producers will be presented with an exhaustive overview of each major component. The aspects of the control algorithm, with its complicated layers of security and perturbance factors, will be explained in detail. Thus, in some countries/cities, autonomous shuttle buses have been implemented on less-traveled routes where they can travel at speeds up to 25 km/h without hindering the public’s circulation, such as university campuses, industrial areas, airports, and sports bases. Some countries/cities use autonomous shuttle buses for pilot programs related to passenger transport, while others use them in postal transport and others for scientific purposes. In all of these situations, the first step in autonomous driving has been taken. The paper also makes an evaluation of the social factors that are a consequence of the mass introduction of autonomous driving as a means of public transportation. Autonomous shuttle buses are becoming a part of everyday life in big cities. Their acceptance as a strategic means of transport depends on their efficiency in daily services; through its efficiency, this means of transport will become a game-changer once its benefits become not only known but experienced by a large number of users.

Highlights

  • Public transport is one of the key issues in designing a large metropolitan area, one of the criteria that defines the quality of life in a city, and strictly related to the social life of each inhabitant

  • autonomous vehicles (AVs) will become a key of the foundations of smart cities

  • Cities without traffic jams related to public rapidly increase their quality of life, decrease their energy consumption

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Summary

Introduction

Public transport is one of the key issues in designing a large metropolitan area, one of the criteria that defines the quality of life in a city, and strictly related to the social life of each inhabitant. There are plenty of direct, indirect, and random factors that influence public transport, but by far the most disturbing one is human interaction in urban traffic. If we eliminate the equation, human factor from this equation, we traffic jams and increase road security. A driver spends min to h in traffic to reach will dramatically reduce traffic jams and increase road security. A driver spends 45 minwork to 1 from home;to if the same person public transport (the conventional he (the or she will spend h in traffic reach work fromuses home; if the same person uses public mode), transport conventional approximately the same amount of time (including lane changing and waiting time). In the case and of a mode), he or she will spend approximately the same amount of time (including lane changing dedicated line for public transportation, theline spent according to several studies willaccording decrease by waiting time).

Conclusions
Automated
General Technical Characteristics
Driveline
Steering
Braking
Charging System
Sensor Systems
Technical data
Camera
Inertial
Autonomous
Autonomous Driving Algorithm
The Electronic Control Unit of the Autonomous Driving Algorithm
19. Software
21. Apollo
Safety and Cybersecurity
Route Specifications
Legal Framework
United States
Europe
Austria
Belgium
France
Germany
The Netherlands
Sweden
Social Implications
Findings
Full Text
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