Cities everywhere are anticipating new mobility technologies to help solve issues with congestion and pollution while providing afforable, accessible, reliable and convenient transportation for growing populations. The adoption of self-driving vehicles is projected to happen soon and help with achieving these goals, especially if part of a shared mobility on demand service. Potential benefits of such a system include a reduction of the number of vehicles and freeing up parking spaces, while challenges still include managing the traffic volume. Previous research focused on estimating fleet size in different scenarios. In this work, we focus on estimating minimum fleet size, parking needs and total travel distance for an autonomous mobility on demand solution serving all trips made in private vehicles in Singapore, generated from a comprehensive simulation of the city’s mobility. We specifically focus on parking demand as currently a significant amount of space has to be designated as parking in cities, which is poised to become obsolate if people switch from private vehicles to shared ones which are utilized much more efficiently. We show that over 85% reduction in the number of vehicles and parking spaces can be achieved while serving all trips made currently in private vehicles. We further show that potential increased traffic volume can be mitigated with the incorporation of ride-sharing, while offering even higher savings, up to 92% in both fleet size and parking needs.

 

Large-scale estimation of parking requirements for autonomous mobility on demand systems
Daniel Kondor, Paolo Santi, Kakali Basak, Xiaohu Zhang, Carlo Ratti

Source: arxiv.org

A common property of many complex systems is resilience, that is, the ability of the system to react to perturbations, internal failures, and environmental events by absorbing the disturbance and/or rebuild to maintain its functions. Nowadays, understanding how complex systems demonstrate resilience is critical in many different fields, because examples of collapses and crises caused by low resilience are more and more spreading all over the world including transportation, financial, energy, communication, and ecological systems.

Therefore, in the last decade, the topic of resilience has grown a lot in popularity. Studies on resilience are popular in multiple disciplines, such as ecology, environmental science, computer science, engineering, management science, economics, and phycology. They investigate resilience of a broad variety of complex systems involving individuals, teams, ecosystems, organizations, communities, supply chains, financial networks, computer networks, and building infrastructures.

Despite this multidisciplinary nature, two main perspectives in the conceptualization of resilience are recognized, that is, the static and dynamic ones [1–4]. The resilience is static when it focuses on the ability of the system to absorb disturbance and bounce back to the original equilibrium state, maintaining its core functions when shocked. In such a case, the resilience is linked to the ability to recover the original shape and features once stretched (robustness) and the capacity of the system to take alternative positions to respond better to change (flexibility). The dynamic perspective focuses on the ability of the system to evolve over time moving towards a new more favorable equilibrium state. According to this perspective, resilience concerns the adaptive capacity of the system, which is able to react to disturbance by changing its structure, processes, and functions in order to increase its ability to persist [5].

This special issue collects nine papers concerning resilience of complex systems, which accords well with the main features summarized above. They concern studies investigating resilience of complex systems in diverse disciplines (engineering, management science, computer science, economics, and organization science) and adopting both the static and dynamic perspectives. Their aim is to identify the main factors and dynamics influencing resilience of diverse systems (water system infrastructures, organizational teams, financial markets, wireless sensor network, and urban system) to a variety of unexpected and negative events

 

Complexity
Volume 2018, Article ID 8756418, 3 pages
https://doi.org/10.1155/2018/8756418
Editorial
Advances on the Resilience of Complex Networks
Ilaria Giannoccaro, Vito Albino, and Anand Nair

Source: www.hindawi.com

Groups of interacting active particles, insects, or humans can form clusters that hinder the goals of the collective; therefore, development of robust strategies for control of such clogs is essential, particularly in confined environments. Our biological and robophysical excavation experiments, supported by computational and theoretical models, reveal that digging performance can be robustly optimized within the constraints of narrow tunnels by individual idleness and retreating. Tools from the study of dense particulate ensembles elucidate how idleness reduces the frequency of flow-stopping clogs and how selective retreating reduces cluster dissolution time for the rare clusters that still occur. Our results point to strategies by which dense active matter and swarms can become task capable without sophisticated sensing, planning, and global control of the collective.

 

Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation
J. Aguilar, D. Monaenkova, V. Linevich, W. Savoie, B. Dutta, H.-S. Kuan, M. D. Betterton, M. A. D. Goodisman, D. I. Goldman
Science  17 Aug 2018:
Vol. 361, Issue 6403, pp. 672-677
DOI: 10.1126/science.aan3891

Source: science.sciencemag.org

Another example of the "slower-is-faster" effect.

This paper reviews the state of the art on the resilience of complex systems by embracing different research areas and using bibliometric tools. The aim is to identify the main intellectual communities and leading scholars and to synthesize key knowledge of each research area. We also carry out a comparison across the research areas, aimed at analyzing how resilience is approached in any field, how the topic evolved starting from the ecological field of study, and the level of cross-fertilization among domains. Our analysis shows that resilience of complex systems is a multidisciplinary concept, which is particularly important in the fields of environmental science, ecology, and engineering. Areas of recent and increasing interest are also operation research, management science, business, and computer science. Except for environmental science and ecology, research is fragmented and carried out by isolated research groups. Integration is not only limited inside each field but also between research areas. In particular, we trace the citation links between different research areas and find a very limited number, revealing a scarce cross-fertilization among domains. We conclude by providing some directions for future research.

 

Complexity
Volume 2018, Article ID 3421529, 44 pages
https://doi.org/10.1155/2018/3421529
Review Article
Resilience of Complex Systems: State of the Art and Directions for Future Research
Luca Fraccascia, Ilaria Giannoccaro, and Vito Albino

Source: www.hindawi.com

Zipf-like distributions characterize a wide set of phenomena in physics, biology, economics, and social sciences. In human activities, Zipf’s law describes, for example, the frequency of appearance of words in a text or the purchase types in shopping patterns. In the latter, the uneven distribution of transaction types is bound with the temporal sequences of purchases of individual choices. In this work, we define a framework using a text compression technique on the sequences of credit card purchases to detect ubiquitous patterns of collective behavior. Clustering the consumers by their similarity in purchase sequences, we detect five consumer groups. Remarkably, post checking, individuals in each group are also similar in their age, total expenditure, gender, and the diversity of their social and mobility networks extracted from their mobile phone records. By properly deconstructing transaction data with Zipf-like distributions, this method uncovers sets of significant sequences that reveal insights on collective human behavior.

 

Sequences of purchases in credit card data reveal lifestyles in urban populations
Riccardo Di Clemente, Miguel Luengo-Oroz, Matias Travizano, Sharon Xu, Bapu Vaitla & Marta C. González
Nature Communicationsvolume 9, Article number: 3330 (2018)

Source: www.nature.com