In this paper we present queueing-theoretical methods for the modeling, analysis, and
control of autonomous mobility-on-demand (MOD) systems wherein robotic, self-driving
vehicles transport customers ...within an urban environment and rebalance themselves to
ensure acceptable quality of service throughout the network. We first cast an autonomous
MOD system within a closed Jackson network model with passenger loss. It is shown that an
optimal rebalancing algorithm minimizing the number of (autonomously) rebalancing vehicles
while keeping vehicle availabilities balanced throughout the network can be found by
solving a linear program. The theoretical insights are used to design a robust, real-time
rebalancing algorithm, which is applied to a case study of New York City and implemented
on an eight-vehicle mobile robot testbed. The case study of New York shows that the
current taxi demand in Manhattan can be met with about 8,000 robotic vehicles (roughly 70%
of the size of the current taxi fleet operating in Manhattan). Finally, we extend our
queueing-theoretical setup to include congestion effects, and study the impact of
autonomously rebalancing vehicles on overall congestion. Using a simple heuristic
algorithm, we show that additional congestion due to autonomous rebalancing can be
effectively avoided on a road network. Collectively, this paper provides a rigorous
approach to the problem of system-wide coordination of autonomously driving vehicles, and
provides one of the first characterizations of the sustainability benefits of robotic
transportation networks.
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Self-driving cars, a quintessentially ‘smart’ technology, are not born smart. The algorithms that control their movements are learning as the technology emerges. Self-driving cars represent a ...high-stakes test of the powers of machine learning, as well as a test case for social learning in technology governance. Society is learning about the technology while the technology learns about society. Understanding and governing the politics of this technology means asking ‘Who is learning, what are they learning and how are they learning?’ Focusing on the successes and failures of social learning around the much-publicized crash of a Tesla Model S in 2016, I argue that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge. ‘Self-driving’ or ‘autonomous’ cars are misnamed. As with other technologies, they are shaped by assumptions about social needs, solvable problems, and economic opportunities. Governing these technologies in the public interest means improving social learning by constructively engaging with the contingencies of machine learning.
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Offers a step-by-step guide to building autonomous vehicles and robots, with source code and accompanying videos The first book of its kind on the detailed steps for creating an autonomous vehicle or ...robot, this book provides an overview of the technology and introduction of the key elements involved in developing autonomous vehicles, and offers an excellent introduction to the basics for someone new to the topic of autonomous vehicles and the innovative, modular-based engineering approach called DragonFly. Engineering Autonomous Vehicles and Robots: The DragonFly Modular-based Approach covers everything that technical professionals need to know about: CAN bus, chassis, sonars, radars, GNSS, computer vision, localization, perception, motion planning, and more. Particularly, it covers Computer Vision for active perception and localization, as well as mapping and motion planning. The book offers several case studies on the building of an autonomous passenger pod, bus, and vending robot. It features a large amount of supplementary material, including the standard protocol and sample codes for chassis, sonar, and radar. GPSD protocol/NMEA protocol and GPS deployment methods are also provided. Most importantly, readers will learn the philosophy behind the DragonFly modular-based design approach, which empowers readers to design and build their own autonomous vehicles and robots with flexibility and affordability. Offers progressive guidance on building autonomous vehicles and robots Provides detailed steps and codes to create an autonomous machine, at affordable cost, and with a modular approach Written by one of the pioneers in the field building autonomous vehicles Includes case studies, source code, and state-of-the art research results Accompanied by a website with supplementary material, including sample code for chassis/sonar/radar; GPS deployment methods; Vision Calibration methods Engineering Autonomous Vehicles and Robots is an excellent book for students, researchers, and practitioners in the field of autonomous vehicles and robots.
Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In ...this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.
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Driverless cars are seen as one of the key disruptors in the next technology revolution. However, the main barrier to adoption is the lack of public trust. The purpose of this study is to investigate ...the key factors influencing the adoption of driverless cars. Drawing on quantitative evidence, the study found that the ability of the driverless car to meet performance expectations and its reliability were important adoption determinants. Significant concerns included privacy (autonomy, location tracking and surveillance) and security (from hackers). The paper provides implications for firms developing the next generation of car features and early implementation sites.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We present the results of a stated preference study undertaken in Italy in 2017 on individuals’ preferences between an electric car (EC) and a petrol car, with the purpose of assessing the impact of ...the latent variable EC knowledge on purchasing decisions. We estimate a multinomial, a mixed and two hybrid mixed logit models, with the interaction between EC knowledge, car attributes and additional exogenous covariates. We use three measurement equations to estimate the self-assessed car knowledge, assessed EC knowledge and EC driving experience. We report three main findings. First, the inclusion of EC knowledge improves our capability to explain car choice. Second, the degree of EC knowledge does not change the negative perception respondents have, ceteris paribus, on ECs. Third, the level of EC knowledge influences the importance placed on the attributes of the choice model. Specifically, a higher level of EC knowledge is associated with a lower concern with fast charging station density. Our results are useful for car manufacturers who wish to improve their marketing strategies through tailored advertising efforts, and for policy makers who wish to implement educational campaigns as a means to foster EC uptake.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This is the first book to bring together the increasingly complex radar automotive technologies and tools being explored and utilized in the development of fully autonomous vehicles - technologies ...and tools now understood to be an essential need for the field to fully mature.The book presents state-of-the-art knowledge as shared by the best and brightest experts working in the automotive radar industry today -- leaders who have "been there and done that." Each chapter is written as a standalone "master class" with the authors, seeing the topic through their eyes and experiences. Where beneficial, the chapters reference one another but can otherwise be read in any order desired, making the book an excellent go-to reference for a particular topic or review you need to understand.You'll get a big-picture tour of the key radar needs for fully autonomous vehicles, and how achieving these needs is complicated by the automotive environment's dense scenes, number of possible targets of interest, and mix of very large and very small returns. You'll then be shown the challenges from - and mitigations to - radio frequency interference (RFI), an ever-increasing challenge as the number of vehicles with radars - and radars per vehicle grow.The book also dives into the impacts of weather on radar performance, providing you with insights gained from extensive real-world testing. You are then taken through the integration and systems considerations, especially regarding safety, computing needs, and testing. Each of these areas is influenced heavily by the needs of fully autonomous vehicles and are open areas of research and development.With this authoritative volume you will understand:How to engage with radar designers (from a system integrator / OEM standpoint); How to structure and set requirements for automotive radars; How to address system safety needs for radars in fully autonomous vehicles; How to assess weather impact on the radar and its ability to support autonomy; How to include weather effects into specifications for radars.This is an essential reference for engineers currently in the autonomous vehicle arena and/or working in automotive radar development, as well as engineers and leaders in adjacent radar fields needing to stay abreast of the rapid developments in this exciting and dynamic field of research and development.
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