Transportation Systems with Autonomous Vehicles: Models and algorithms for equilibrium assignment

Abstract Technologies for connected, automated or autonomous vehicles (AVs) are fast developing, so that they seem ready for substituting in the near future privately owned non-autonomous traditional vehicles (TVs) and further supporting the spread of shared vehicles both for person and good transportation. On the other hand, it may easily be anticipated that the time needed to turn the existing stock of TVs into AVs will last several years during which mixed traffic is expected. A change so great may be not technology-driven only, but also requires a carefully analysis of its several impact through well designed enhancements of tools already available to the transportation systems modelers and planners. Such enhanced tools may be casted in the general framework of multi-user class assignment to transportation networks, concerning: (i) transportation network analysis, through level-of-service models distinguishing between non-autonomous vs. autonomous vehicles, presumably sharing same infrastructure; (ii) travel demand analysis, through behavioral choice modeling paradigms, including choice between AVs vs. TVs, owned vs. shared, as well as route choice behavior; (iii) steady-state equilibrium assignment. This paper describes models and algorithms to deal with steady-state equilibrium assignment; they are used to show to which extent existing methods can still be applied as well as which issues remain still open and worth of further research efforts

solving stochastic assignment to transportation networks with tvs and avs

Abstract This paper focuses on solving stochastic assignment with several types of vehicles, for instance advanced and traditional vehicles, competing for the same arcs and jointly participating to congestion. In urban transportation networks paths likely overlap, thus two path choice models, derived from Random Utility Theory, are analyzed: Probit and Gammit, properly modeling path overlap through covariance between path perceived utilities. Since for these two models no closed form is available for choice probabilities, two specifications of Montecarlo algorithms for assignment to uncongested networks are presented: the efficiency of the commonly used Mersenne Twister Pseudo-Random Number Generator is compared with a PRNG based on Sobol (quasi-random) numbers. Then, several MSA-based algorithms for equilibrium assignment ot congested networks are analyzed: some step size strategies are proposed and compared with existing ones aiming at improving practical rate of convergence. Sufficient convergence conditions are presented for equilibrium assignment with arc cost flow functions with symmetric or asymmetric Jacobian matrix. Results of applications are also discussed to support theoretical results

Painting maps with bats: Species distribution modelling in bat research and conservation

Species distribution models (SDMs) offer an effective tool for identifying species conservation requirements and forecasting how global environmental changes will affect species diversity and distribution. This approach is particularly relevant for bats because their nocturnal behaviour hinders detectability and identification in flight. Despite their important contribution to global biodiversity and wide geographical ranges, bats have been under-represented in early SDM studies, and only in the last few years has this approach become more widely used in bat research. We carried out a meta-analysis of the published literature to review the history of the use of SDMs in bat research and their application in conservation, climate change assessments and genetic studies. We focus on the geographical coverage, theme and modelling algorithm of published studies, and compare studies that are uniquely dedicated to bats to multi-taxa studies that include bats. We provide recommendations for good modelling practices through considering spatial scale and spatial biases, selecting ecologically relevant variables, following rigorous modelling protocols, and recognising the limitations of extrapolation across temporal scales. We suggest future developments that will further favour the use of SDMs to study bat ecology and biogeography, as well as inform conservation management. We conclude that despite an increase in bat SDM studies, their scope and application can be further enhanced through incorporating dispersal, landscape connectivity and biotic interactions between bats, their prey and their pathogens

Traffic management system for smart road networks reserved for self-driving cars

A model of a smart road network consisting of unsignalised intersections and smart roads connecting them is considered in this work with the aim of presenting a traffic management system for self-driving cars (or, more generally, autonomous vehicles) which travel the network. The proposed system repeatedly solves a set of mathematical programming problems (each of them relative to a single intersection or to a single road stretch of the network) within a decentralised control scheme in which each local intersection controller and each local road controller communicates with the fully autonomous vehicles in order to receive travel data from vehicles and to provide speed profiles to them once determined the optimal solution of the problem. In order to reduce the computational effort required to provide the optimal solution, a discrete-time approach is adopted so that, in each time interval, a limited number of vehicles are taken into consideration; in this way, solutions can be determined in a very short time thus making the proposed model compatible with a practical application to real traffic systems. The proposed model is general enough, and can be adapted to different scenarios of smart road networks reserved for self-driving cars

On analyzing the vulnerabilities of a railway network with Petri nets

Petri nets are used in this paper to estimate the indirect consequences of accidents in a railway network, which belongs to the class of the so-called transportation Critical Infrastructures (CIs), that is, those assets consisting of systems, resources and/or processes whose total or partial destruction, or even temporarily unavailability, has the effect of significantly weakening the functioning of the system. In the proposed methodology, a timed Petri ne<t represents the railway network and the trains travelling over the rail lines; such a net also includes some places and some stochastically-timed transitions that are used to model the occurrence of unexpected events (accidents, disruptions, and so on) that make some resources of the network (tracks, blocks, crossovers, overhead line, electric power supply, etc.) temporarily unavailable. The overall Petri net is a live and bounded Generalized Stochastic Petri Net (GSPN) that can be analyzed by exploiting the steady-state probabilities of a continuous-time Markov chain (CTMC) that can be derived from the reachability graph of the GSPN. The final target of such an analysis is to determine and rank the levels of criticality of transportation facilities and assess the vulnerability of the whole railway network

Testing for changes in rate of evolution and position of the climatic niche of clades

1. There is solid recognition that phylogenetic effects must be acknowledged to appreciate climatic niche variability among species clades properly. Yet, most currently available methods either work at the intra- specific level (hence they ignore phylogeny) or rely on the Brownian motion model of evolution to estimate phylogenetic effects on climatic niche variation. The Brownian mo-tion model may be inappropriate to describe niche evolution in several cases, and even a significant phylogenetic signal in climatic variables does not in-dicate that the effect of shared ancestry was relevant to niche evolution.2. We introduce a new phylogenetic comparative method which describes sig-nificant changes in the width and position of the climatic niche at the inter-specific (clade) level, while making no a priori assumption about how niche evolution took place.3. We devised the R function phylo.niche.shift to estimate whether the climatic niches of individual clades in the tree are either wider or narrower than expected, and whether the niche occupies unexpected climates. We tested phylo.niche.shift on realistic virtual species’ distribution patterns applied to a phylogeny of 365 extant primate species.4. We demonstrate via simulations that the new method is fast and accurate under widely different climatic niche evolution scenarios. phylo.niche.shift showed that the capuchin monkeys and langurs occupy much wider, and prosimian much narrower, climatic niche space than expected by their phylogenetic positions.5. phylo.niche.shift may help to improve research on niche evolution by allow-ing researchers to test specific hypotheses on the factors affecting clades’ realised niche width and position, and the potential effects of climate change on species’ distribution

From Smart Apes to Human Brain Boxes. A Uniquely Derived Brain Shape in Late Hominins Clade

Modern humans have larger and more globular brains when compared to other primates. Such anatomical features are further reflected in the possession of a moderately asymmetrical brain with the two hemispheres apparently rotated counterclockwise and slid anteroposteriorly on one another, in what is traditionally described as the Yakovlevian torque. Developmental disturbance in human brain asymmetry, or lack thereof, has been linked to several cognitive disorders including schizophrenia and depression. More importantly, the presence of the Yakovlevian torque is often advocated as the exterior manifestation of our unparalleled cognitive abilities. Consequently, studies of brain size and asymmetry in our own lineage indirectly address the question of what, and when, made us humans, trying to trace the emergence of brain asymmetry and expansion of cortical areas back in our Homo antecedents. Here, we tackle this same issue by studying the evolution of human brain size, shape, and asymmetry on a phylogenetic tree including 19 apes and Homo species, inclusive of our fellow ancestors. We found that a significant positive shift in the rate of brain shape evolution pertains to the clade including modern humans, Neanderthals, and Homo heidelbergensis. Although the Yakovlevian torque is well evident in these species and levels of brain asymmetry are correlated to changes in brain shape, further early Homo species possess the torque. Even though a strong allometric component is present in hominoid brain shape variability, this component seems unrelated to asymmetry and to the rate shift we recorded. These results suggest that changes in brain size and asymmetry were not the sole factors behind the fast evolution of brain shape in the most recent Homo species. The emergence of handedness and early manifestations of cultural modernity in the archeological record nicely coincide with the same three species sharing the largest and most rapidly evolving brains among all hominoids

A new, fast method to search for morphological convergence with shape data

Morphological convergence is an intensely studied macroevolutionary phenomenon. It refers to the morphological resemblance between phylogenetically distant taxa. Currently available methods to explore evolutionary convergence either: rely on the analysis of the phenotypic resemblance between sister clades as compared to their ancestor, fit different evolutionary regimes to different parts of the tree to see whether the same regime explains phenotypic evolution in phylogenetically distant clades, or assess deviations from the congruence between phylogenetic and phenotypic distances. We introduce a new test for morphological convergence working directly with non-ultrametric (i.e. paleontological) as well as ultrametric phylogenies and multivariate data. The method (developed as the function search.conv within the R package RRphylo) tests whether unrelated clades are morphologically more similar to each other than expected by their phylogenetic distance. It additionally permits using known phenotypes as the most recent common ancestors of clades, taking full advantage of fossil information. We assessed the power of search.conv and the incidence of false positives by means of simulations, and then applied it to three well-known and long-discussed cases of (purported) morphological convergence: the evolution of grazing adaptation in the mandible of ungulates with high-crowned molars, the evolution of mandibular shape in sabertooth cats, and the evolution of discrete ecomorphs among anoles of Caribbean islands. The search.conv method was found to be powerful, correctly identifying simulated cases of convergent morphological evolution in 95% of the cases. Type I error rate is as low as 4-6%. We found search.conv is some three orders of magnitude faster than a competing method for testing convergence