4,386 research outputs found
Impact of Traffic Sign Diversity on Autonomous Vehicles: A Literature Review
Traffic sign classification is indispensable for road traffic systems, including automated ones. There is a fundamental difference in the visual appearance of traffic signs from one country to another. Each dataset has its design standards and regulations based on shape, color, and information content, making implementing classification and recognition techniques more difficult. This paper aims to assess the influence of traffic sign diversity on autonomous vehicles (AVs) by reviewing several previous studies, comparing, summarizing their results, and focusing on classifying and detecting traffic sign datasets based on color, shape, and deep learning spaces using various methods and applications. Furthermore, it covers the main challenges facing road designers and planners considering changes to road safety infrastructure. It will be argued that compiling and standardizing a comprehensive global database of traffic signs is very difficult because it is costly and complex in application. However, it is still one of the possible solutions for the coming decades. Recommendations for future developments are also presented in this study
International overview on the legal framework for highly automated vehicles
The evolution of Autonomous and automated technologies during the last decades has been
constant and maintained. All of us can remember an old film, in which they shown us a
driverless car, and we thought it was just an unreal object born of filmmakers imagination.
However, nowadays Highly Automated Vehicles are a reality, even not in our daily lives.
Hardly a day we donât have news about Tesla launching a new model or Google showing the
new features of their autonomous car. But donât have to travel far away from our borders.
Here in Europe we also can find different companies trying, with more or less success
depending on with, not to be lagged behind in this race.
But today their biggest problem is not only the liability of their innovative technology, but also
the legal framework for Highly Automated Vehicles. As a quick summary, in only a few
countries they have testing licenses, which not allow them to freely drive, and to the contrary
most nearly ban their use. The next milestone in autonomous driving is to build and
homogeneous, safe and global legal framework.
With this in mind, this paper presents an international overview on the legal framework for
Highly Automated Vehicles. We also present de different issues that such technologies have
to face to and which they have to overcome in the next years to be a real and daily
technology
Mobility on Demand in the United States
The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportationâs MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment
Implications of automated vehicles for street design and planning: Espoo case
Automated Vehicles (AVs), in their foundational stage, are gradually emerging into Espooâs road network. During the transition phase, AVs are expected to introduce several challenges and requirements for road operators in design and maintenance of physical infrastructure. This has pushed cities to investigate the potential changes needed to the way their road networks are operated and managed, to consistently support and optimize the outcomes from the introduction of AVs.
The thesis uses a combination of qualitative methods, including map-based survey, road test drives, expert discussions and critical testing scenarios to identify and assess several street design elements in Espoo. The study assesses the automation ability of the Tesla Autopilot in the road network by experimenting several driving scenarios and weather conditions i.e. night and rain. The study also briefly tests other steering assist systems as a way to assess and compare capabilities of other steering assist systems within similar road environments.
Today, the design and quality of road markings are the key features influencing the operation of machine vision based automated systems. Therefore, discussions regarding street design implications are mainly related to the design of longitudinal markings. In this study, several design elements had been identified and studied, including edge marking, lane split and merge marking, bus stop and side parking marking. Based on the current technological trends in vehicle automation, road operators are advised to consider several physical infrastructure and maintenance elements, including primarily the machine readability of line markings. The consistency in design, implementation and maintenance of road markings are seen to have the most benefit in facilitating the deployment of AVs today. However, it was observed that some road marking elements were more critical than others, and therefore, it is suggested that they have higher maintenance and design priority.
While the study assesses street design elements that are seen significant for the operation of steering assist systems today, operators are advised to consider planning frameworks to plan for the introduction of AVs, in order to avoid making changes that may hinder their operation in the future. However, it is important to consider other aspects of road operation and management when considering any new innovative changes in street design in the future
Autonomous Vehicles in Road Tunnels : A Risk Safety Perspective
This study examines the challenges associated with deploying autonomous vehicles (AVs) in road tunnels, focusing on both operational aspects and vehicle-human interaction. This work explored that road tunnels present unique constraints, such as limited visibility and confined spaces, which necessitate careful consideration for AV integration. It is observed that factors like varying light conditions and restricted communication capabilities within tunnels impact AVs' performance. Additionally, the study investigates and categorizes challenges related to tunnel geometries, infrastructure modifications, sensor technologies, emergency situations, and human-machine interaction.
Furthermore, this work comprehensively explored academic and non-academic literature, gathering contemporary knowledge on AVs in road tunnels in one place to provide a foundational base for researchers on this topic. In this regard, the adopted methodological framework is also presented for researchers' review. The other notable contribution is to specifically highlight the critical operational issues of human-AV interaction in tunnel environments. In the last section, it also proposes potential solutions to these issues. In doing so, it keeps the directional approach open for other researchers as there are insightful risk-related implications for further research in this significant domain
The Critical Role of Public Charging Infrastructure
Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change
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