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Real-world input (hybrid street map, customer's pickup/delivery locations, and vehicle positions) and corresponding viable transportation network. Diamond symbols A, C, and D represent autonomous, conventional, and dual-mode vehicles, respectively.

Real-world input (hybrid street map, customer's pickup/delivery locations, and vehicle positions) and corresponding viable transportation network. Diamond symbols A, C, and D represent autonomous, conventional, and dual-mode vehicles, respectively.

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Conference Paper
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Autonomous vehicles (AVs) are expected to widely re-define mobility in the future, transforming many solutions into autonomous services. Nonetheless, this development requires an expected transition phase of several decades in which some regions will provide sufficient infrastructure for AV movements, while others will not support AVs yet. In this...

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Citations

... The station-based scheme relies on pre-defined stations for users to pick up and return bikes, while the free-floating offers flexibility, allowing users to drop bikes at various locations within designated operational zones (B. Beirigo, Schulte, & Negenborn, 2018). The latter eliminates the constraints associated with station availability in station-based systems, contributing to the growing popularity of free-floating bike sharing in recent years during the past years (Chen, van Lierop, & Ettema, 2020;Fishman, 2016). ...
... Moreover, several studies investigate the interplay of bike sharing and public transport in cities such as Poznan´ (15), Oslo (16), and Vienna (17). Recent literature has further stressed the importance of reliable service quality in shared mobility (18), possibly implemented in different service zones (19). Nevertheless, hardly any research considers disruptive events comparable to the COVID- 19 pandemic and, to the best of our knowledge, there is no study available that explicitly considers the COVID-19 scenario. ...
... Recent literature has further stressed the importance of reliable service quality in shared mobility (18), possibly implemented in different service zones (19). Nevertheless, hardly any research considers disruptive events comparable to the COVID- 19 pandemic and, to the best of our knowledge, there is no study available that explicitly considers the COVID-19 scenario. In this work, we propose and evaluate an operational integration of PTSs and BSSs to meet the mobility demand of cities in the face of disruptive events such as the recent COVID-19 pandemic. ...
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The COVID-19 pandemic poses an unprecedented challenge for public transport systems. The capacity of transport systems has been significantly reduced because of the social distancing measures. Therefore, new avenues to increase the resilience of public urban mobility need to be explored. In this work, we investigate the integration of bike sharing and public transport systems to compensate for limited public transport capacity under the disruptive impacts of the COVID-19 pandemic. As a first step, we develop a data analysis model to integrate the demand of the two underlying systems. Next, we build an optimization model for the design and operation of hybrid mixed-fleet bike sharing systems. We analyze the case of the subway and public bike sharing systems in Milan to assess this approach. We find that the bike sharing system (in its current state) can only compensate for a minor share of the public transport capacity, as the needs in fleet and station capacity are very high. However, the resilience of public urban mobility further increases when new design concepts for the bike sharing system are considered. An extension to a hybrid free-floating bike and docked e-bike system doubled the covered demand of the system. An extension of the station capacity of about 37% yields an additional increase of the covered demand by 6.5%–7.5%. On the other hand, such a hybrid mixed-fleet bike sharing system requires many stations and a relatively large fleet to provide the required mobility capacity, even at low demand requirements.
... Although most studies on urban mobility assume that a single service provider takes care of all requests, this centralized setting is unlikely to happen in reality since multiple providers can exist in one operation area (Ho et al., 2018). Despite optimal from a fleet operational perspective, centralized operations entail a transition from a diversified mobility market to a monopolistic market, possibly leading to less competition 160 and, consequently, higher prices for passengers (Vazifeh et al., 2018), and different services in different zones (Beirigo et al., 2018). ...
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... Meng et al. designed a control strategy for official vehicles in the traffic road network to improve the K-means algorithm to make the nodes of the official vehicle network adapt to the route, increase the weight of the backpressure strategy according to traffic pressure conditions, and improve the parameters through optimization the adaptability of official vehicles in the traffic road network [24]. Beirigo et al. proposed a dual-mode vehicle routing in hybrid autonomous and nonautonomous regional networks and introduced a new mathematical programming model in the routing to achieve coordinated routing planning for autonomous and conventional vehicles [25]. ...
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... Algorithms for optimal task-handling are being investigated for a wide array of applications, ranging from coordinating autonomous self-driving EVs [15], to cooperative robotics [16], industrial site inspection [17], and the management of modern warehouses [18]. As such, the development of these algorithms for optimal cost-efficiency of task handling, regardless of the type of task, becomes imperative for modern industries. ...
... Finally, vertices are identified as boundary vertices (set B) or interior domain (set D) nodes according to (14) and (15). ...
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... Then, in Section 2.5, we evaluate how operational costs, service levels, and fleet utilization develop across scenarios, concluding with a summary of key insights and outlook on future work in Section 2.6. Parts of this chapter have been published in [7]: ...
Thesis
Current mobility services cannot compete on equal terms with self-owned mobility products concerning service quality. Due to supply and demand imbalances, ridesharing users invariably experience delays, price surges, and rejections. Traditional approaches often fail to respond to demand fluctuations adequately since service levels are, to some extent, bounded by fleet size. With the emergence of autonomous vehicles (AVs), however, the characteristics of mobility services change, and new opportunities to overcome the prevailing limitations arise. This thesis proposes a series of learning- and optimization-based strategies to help autonomous transportation providers meet the service quality expectations of diversified user bases. We show how autonomous mobility-on-demand (AMoD) systems can develop to revolutionize urban transportation, improving reliability, efficiency, and accessibility.
... Studies such as these often investigate the frontier of new transportation and smart cities technologies, including autonomous vehicles, electric vehicles, ride-sharing, and bike-sharing. Beirigo et al. (2018) ...
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... Studies such as these often investigate the frontier of new transportation and smart cities technologies, including autonomous vehicles, electric vehicles, ride-sharing, and bike-sharing. Beirigo et al. (2018) ...
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This paper was presented as the 8th annual Transactions in GIS plenary address at the American Association of Geographers annual meeting in Washington, DC. The spatial sciences have recently seen growing calls for more accessible software and tools that better embody geographic science and theory. Urban spatial network science offers one clear opportunity: from multiple perspectives, tools to model and analyze nonplanar urban spatial networks have traditionally been inaccessible, atheoretical, or otherwise limiting. This paper reflects on this state of the field. Then it discusses the motivation, experience, and outcomes of developing OSMnx, a tool intended to help address this. Next it reviews this tool's use in the recent multidisciplinary spatial network science literature to highlight upstream and downstream benefits of open‐source software development. Tool-building is an essential but poorly incentivized component of academic geography and social science more broadly. To conduct better science, we need to build better tools. The paper concludes with paths forward, emphasizing open-source software and reusable computational data science beyond mere reproducibility and replicability.
... Algorithms for optimal task-handling are being investigated for a wide array of applications, ranging from coordinating autonomous self-driving EVs [15], to cooperative robotics [16], industrial site inspection [17], and the management of modern warehouses [18]. As such, the development of these algorithms for optimal cost-efficiency of task handling, regardless of the type of task, becomes imperative for modern industries. ...
... Studies such as these often investigate the frontier of new transportation and smart cities technologies, including autonomous vehicles, electric vehicles, ride-sharing, and bike-sharing. Beirigo et al. (2018) ...