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Autonomous Mobility-on-Demand Systems for Future Urban Mobility400 19.1 Introduction 19.1.1 Overview This chapter discusses the operational and economic aspects of autonomous mobility-on- demand (AMoD) systems, a transformative and rapidly developing mode of transportation wherein robotic, self-driving vehicles transport passengers in a given environment. Specif- ically, AMoD systems are addressed along three dimensions: (1) modeling, that is analyti- cal models capturing salient dynamic and stochastic features of customer demand, (2) control, that is coordination algorithms for the vehicles aimed at throughput maximization, and (3) economic, that is fleet sizing and financial analyses for case studies of New York City and Singapore. Collectively, the models and methods presented in this chapter enable a rigorous assessment of the value of AMoD systems. In particular, the case study of New York City shows that the current taxi demand in Manhattan can be met with about 8,000 robotic vehicles (roughly 70 percent of the size of the current taxi fleet), while the case study of Singapore suggests that an AMoD system can meet the personal mobility needs of the entire population of Singapore with a number of robotic vehicles roughly equal to 1/3 of the current number of passenger vehicles. Directions for future research on AMoD sys- tems are presented and discussed. 19.1.2 Personal urban mobility in the 21st century In the past century, private automobiles have dramatically changed the paradigm of personal urban mobility by enabling fast and anytime point-to-point travel within cities. However, this paradigm is currently challenged due to a combination of factors such as dependency on oil, tailpipe production of greenhouse gases, reduced throughput caused by congestion, and ever-increasing demands on urban land for parking spaces . In the US, urban vehi- cles consume more than half of the oil consumed by all sectors , and produce 20 percent of the total carbon dioxide emissions [3, 4]. Congestion has soared dramatically in the recent past, due to the fact that construction of new roads has not kept up with increasing transportation demand . In 2011, congestion in metropolitan areas increased urban Americans’ travel times by 5.5 billion hours (causing a 1 percent loss of US GDP ), and this figure is projected to increase by 50 percent by 2020 . Parking compounds the con- gestion problem, by causing additional congestion and by competing for urban land for other uses. The problem is even worse on a global scale, due to the combined impact of rapid increases in urban population (to reach 5 billion, more than 60 percent of the world population, by 2030 ), worldwide urban population density, and car ownership in devel- oping countries . As a result, private automobiles are widely recognized as an unsustain- able solution for the future of personal urban mobility .
Autonomes Fahren Technische, rechtliche und gesellschaftliche Aspekte
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