Autonomous Vehicles: Open-Source Technologies, Considerations, and Development

Autonomous vehicles are the culmination of advances in many areas such as sensor technologies, artificial intelligence (AI), networking, and more. This paper will introduce the reader to the technologies that build autonomous vehicles. It will focus on open-source tools and libraries for autonomous vehicle development, making it cheaper and easier for developers and researchers to participate in the field. The topics covered are as follows. First, we will discuss the sensors used in autonomous vehicles and summarize their performance in different environments, costs, and unique features. Then we will cover Simultaneous Localization and Mapping (SLAM) and algorithms for each modality. Third, we will review popular open-source driving simulators, a cost-effective way to train machine learning models and test vehicle software performance. We will then highlight embedded operating systems and the security and development considerations when choosing one. After that, we will discuss Vehicle-to-Vehicle (V2V) and Internet-of-Vehicle (IoV) communication, which are areas that fuse networking technologies with autonomous vehicles to extend their functionality. We will then review the five levels of vehicle automation, commercial and open-source Advanced Driving Assistance Systems, and their features. Finally, we will touch on the major manufacturing and software companies involved in the field, their investments, and their partnerships. These topics will give the reader an understanding of the industry, its technologies, active research, and the tools available for developers to build autonomous vehicles.Comment: 13 pages, 7 figure

Mobilité des travailleurs et scénarios de gestion des déplacements faits en automobile

RÉSUMÉ À Montréal comme ailleurs, la congestion routière aux heures de pointe, causée principalement par les déplacements pendulaires des travailleurs auto conducteurs, est une problématique qui préoccupe les spécialistes du transport et de la mobilité. De nombreux auteurs affirment qu’une gestion efficace des déplacements faits en automobiles pourrait contribuer à améliorer la situation. Ce mémoire de maîtrise caractérise la mobilité des travailleurs de la région métropolitaine de Montréal pour mieux comprendre leurs habitudes de déplacement. Dans ce cadre, ce mémoire se compose de trois parties. Tout d’abord, une analyse des comportements de mobilité des travailleurs de la région métropolitaine de Montréal, à partir des données de l’enquête Origine-Destination de 2008 et de l’Enquête Nationale des Ménages de 2011, est réalisée pour tracer le profil typique d’un travailleur montréalais et de sa mobilité. À cet effet, les travailleurs sont classifiés selon différentes caractéristiques ciodémographiques. Les liens domicile-travail de ces derniers sont ensuite étudiés à travers une analyse spatiotemporelle et modale de leurs déplacements. Cette partie révèle, sans surprise, que le mode auto conducteur est le mode favorisé par les travailleurs de Montréal pour leurs déplacements domicile-travail. Cela se conjugue avec un taux de possession automobile assez élevé, dépassant 1,28 auto/logis.----------ABSTRACT In Montreal as elsewhere, traffic congestion during peak hours is mainly caused by commuting drivers. It is an issue that concerns transportation planners and specialists. Many authors argue that a more effective management of car trips could help improve the situation. This thesis characterizes the mobility of workers in the Montreal metropolitan area in order to understand the commuting patterns. In this context, this thesis consists of three sections. First, an analysis of commuting behavior of workers in the Montreal metropolitan area is conducted to profile the typical Montreal worker, using the 2008 Origin-Destination survey and the 2011 National Survey of Households. Workers are classified according to demographics, then, a patiotemporal and modal analysis of their commuting is realized. This part reveals, unsurprisingly, that the auto driver mode is the preferred commuting mode of the Montreal residents. This could be related to the high rate of car ownership, exceeding 1.28 cars/house