Decentralized Ride-Sharing and Vehicle-Pooling Based on Fair Cost-Sharing Mechanisms

Ride-sharing or vehicle-pooling allows commuters to team up spontaneously for transportation cost sharing. This has become a popular trend in the emerging paradigm of sharing economy. One crucial component to support effective ride-sharing is the matching mechanism that pairs up suitable commuters. Traditionally, matching has been performed in a centralized manner, whereby an operator arranges ride-sharing according to a global objective (e.g., total cost of all commuters). However, ride-sharing is a decentralized decision-making paradigm, where commuters are self-interested and only motivated to team up based on individual payments. Particularly, it is not clear how transportation cost should be shared fairly between commuters, and what ramifications of cost-sharing are on decentralized ride-sharing. This paper sheds light on the principles of decentralized ride-sharing and vehicle-pooling mechanisms based on stable matching, such that no one would be better off to deviate from a stable matching outcome. We study various fair cost-sharing mechanisms and the induced stable matching outcomes. We compare the stable matching outcomes with a social optimal outcome (that minimizes total cost) by theoretical bounds of social optimality ratios, and show that several fair cost-sharing mechanisms can achieve high social optimality. We also corroborate our results with an empirical study of taxi sharing under fair cost-sharing mechanisms by a data analysis on New York City taxi trip dataset, and provide useful insights on effective decentralized mechanisms for practical ride-sharing and vehicle-pooling.Comment: To appear in IEEE Trans. on Intelligent Transportation System

A simulation of the Neolithic transition in Western Eurasia

Farming and herding were introduced to Europe from the Near East and Anatolia; there are, however, considerable arguments about the mechanisms of this transition. Were it people who moved and outplaced the indigenous hunter- gatherer groups or admixed with them? Or was it just material and information that moved-the Neolithic Package-consisting of domesticated plants and animals and the knowledge of its use? The latter process is commonly referred to as cultural diffusion and the former as demic diffusion. Despite continuous and partly combined efforts by archaeologists, anthropologists, linguists, paleontologists and geneticists a final resolution of the debate has not yet been reached. In the present contribution we interpret results from the Global Land Use and technological Evolution Simulator (GLUES), a mathematical model for regional sociocultural development embedded in the western Eurasian geoenvironmental context during the Holocene. We demonstrate that the model is able to realistically hindcast the expansion speed and the inhomogeneous space-time evolution of the transition to agropastoralism in Europe. GLUES, in contrast to models that do not resolve endogenous sociocultural dynamics, also describes and explains how and why the Neolithic advanced in stages. In the model analysis, we uncouple the mechanisms of migration and information exchange. We find that (1) an indigenous form of agropastoralism could well have arisen in certain Mediterranean landscapes, but not in Northern and Central Europe, where it depended on imported technology and material, (2) both demic diffusion by migration or cultural diffusion by trade may explain the western European transition equally well, (3) [...]Comment: Accepted Author Manuscript version accepted for publication in Journal of Archaeological Science. A definitive version will be subsequently published in the Journal of Archaological Scienc

Thru-Hiking the Appalachian Trail: Examining Opportunities for Learning on a Continuous 2,185-Mile Self-Supported Hike

This study explored transformational adult learning and thru-hiker culture on the Appalachian Trail, employing autoethnography as research methodology within the qualitative research tradition (Creswell, 2007). The researcher explored thru-hiker culture by hiking the complete Appalachian Trail for five months, involving a 2,185 mile journey experienced as a continuous “flip-flop” hike. The researcher began hiking northbound from Mount Greylock, Massachusetts on June 25, 2014. Mount Katahdin, Maine, the A.T. northern terminus was summited August 15, 2014. The southbound journey commenced August 20, 2014 from Mount Greylock and ended at the summit of Springer, Mountain, Georgia, the southern terminus November 22, 2014. Personal observations through daily blog posts and weekly newspaper articles were collected, and used to critically reflect on the experience, a process integral to transformational adult learning, and achieving an understanding of thru-hiker culture. Themes associated with the transformational learning included compassion, community, and simplicity. Theories used to analyze learning included Flow theory (Csikszentmihalyi, 1990), Hierarchy of Needs theory (Maslow, 1970), Ulysses Factor (Anderson, 1970), and Transformational Adult Learning theory (Brookfield, 1987, Mezirow, 1991). A description of thru-hiker culture revealed a unique hierarchy among participants, distinctive norms regarding social interaction, language, and concepts of self and others. The study illustrated the intimate relationship between the self as an independent actor and also member of a culture (Bruner, 1990). The study reveals A.T. thru-hiker culture through a description of the experience, knowledge gained from critical reflection on the experience, and the role of physical and psychological challenge on the emerging self

Tracing the dispersal route of the invasive Japanese beetle Popillia japonica

The Japanese beetle, Popillia japonica, is a highly polyphagous Scarabaeidae native to Japan that colonized North America and Azores in the last century and has recently invaded Italy and Switzerland. Considering its economic impact on the horticulture and turfgrass industries, this species was ranked within the EU priority pests list in 2019. According to the EU Convention on Biological Diversity, the identification of invasion routes is a pivotal aspect in an effective management program aimed at controlling invasive alien species. To reconstruct the source of introductions of this pest, we investigated the genetic variability of P. japonica in its native and invaded areas worldwide by analyzing 9 microsatellite loci and two mitochondrial genes, COX I and CytB. In its native area, P. japonica is structured into two populations: one in the southern and another in the northern-central region of Japan. A limited area within central Japan was identified as the putative source of the North American outbreak. Moreover, the ABC inference and phylogeographic reconstruction suggest that two European populations originated from two independent introductions. The Azores Islands outbreak occurred approximately 50 years ago and originated from the southeastern region of North America (For simplicity, in this paper North America refers to Canada and the USA), while the second introduction, more recently, occurred in Italy and Switzerland and originated from northeastern region of North America

Analysis of Search Incidents and Lost Person Behavior in Yosemite National Park

Every year thousands of people are reported lost or missing in wilderness areas and in response, a search and rescue (SAR) operation is launched to locate, stabilize, and extract those missing. Actually locating the subject is often the most difficult of these processes. This study attempts to improve upon search operations by analyzing lost person behavior at the "local" level. If a search manager knew what a lost subject was most likely to do when lost, then they could plan the search accordingly and return them to safety much quicker. Additionally, if National Park officials knew who was becoming lost, and when and where this occurred, steps could be taken to prevent these people from becoming lost in the first place. Eleven years (2000-2010) of Search and Rescue case incident reports from Yosemite National Park (2,308 in total) were examined and 213 searches were retained for analysis. It was determined that approximately 62% of incidents involve missing hikers. Nearly two thirds of the searches were for one subject and about two-thirds of these involved males. The mean age of missing persons was 36 years old. Most people were reported missing in July, on Saturday, and between the hours of 2 and 3 p.m. Almost half of people reported as missing were actually lost while others were merely separated from their party, or overdue. Contributing factors include losing the trail accidentally, failure to communicate the intended plan, and miscalculating the time or distance of the planned route, among others. Within a Geographic Information System (GIS) the Initial Planning Point (IPP), the point at which the person was last seen or known to be, and the found location was georeferenced for each incident using the point radius method. This allowed for a Getis-Ord Gi* analysis to be conducted of both the IPPs and found locations and "hot spots" were identified for each. The GIS also provided an environment for analyzing lost person behavior. Within Yosemite National Park lost hikers most often utilized route traveling in order to reorient themselves. Additionally, descriptive lost person behavior statistics for hikers were calculated, including: horizontal distance from the IPP to the found location, vertical elevation change from the IPP to the found location, dispersion angle from intended destination to the found location, and the track offset of the found location. These "local" results were then compared to "international" statistics presented by the International Search and Rescue Incident Database (ISRID) using a chi-square goodness of fit test. It was found that the ISRID data provided for horizontal distance from the IPP and track offset were not suitable for use in Yosemite while the data pertaining to vertical elevation change from the IPP and the dispersion angle could potentially be utilized for search planning

An Evolutionary Multi-Objective Optimization Framework for Bi-level Problems

Genetic algorithms (GA) are stochastic optimization methods inspired by the evolutionist theory on the origin of species and natural selection. They are able to achieve good exploration of the solution space and accurate convergence toward the global optimal solution. GAs are highly modular and easily adaptable to specific real-world problems which makes them one of the most efficient available numerical optimization methods. This work presents an optimization framework based on the Multi-Objective Genetic Algorithm for Structured Inputs (MOGASI) which combines modules and operators with specialized routines aimed at achieving enhanced performance on specific types of problems. MOGASI has dedicated methods for handling various types of data structures present in an optimization problem as well as a pre-processing phase aimed at restricting the problem domain and reducing problem complexity. It has been extensively tested against a set of benchmarks well-known in literature and compared to a selection of state-of-the-art GAs. Furthermore, the algorithm framework was extended and adapted to be applied to Bi-level Programming Problems (BPP). These are hierarchical optimization problems where the optimal solution of the bottom-level constitutes part of the top-level constraints. One of the most promising methods for handling BPPs with metaheuristics is the so-called "nested" approach. A framework extension is performed to support this kind of approach. This strategy and its effectiveness are shown on two real-world BPPs, both falling in the category of pricing problems. The first application is the Network Pricing Problem (NPP) that concerns the setting of road network tolls by an authority that tries to maximize its profit whereas users traveling on the network try to minimize their costs. A set of instances is generated to compare the optimization results of an exact solver with the MOGASI bi-level nested approach and identify the problem sizes where the latter performs best. The second application is the Peak-load Pricing (PLP) Problem. The PLP problem is aimed at investigating the possibilities for mitigating European air traffic congestion. The PLP problem is reformulated as a multi-objective BPP and solved with the MOGASI nested approach. The target is to modulate charges imposed on airspace users so as to redistribute air traffic at the European level. A large scale instance based on real air traffic data on the entire European airspace is solved. Results show that significant improvements in traffic distribution in terms of both schedule displacement and air space sector load can be achieved through this simple, en-route charge modulation scheme

Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (1/4)

Technical report about sustainable urban freight solutions, part 1 of

In search of sustainable and inclusive mobility solutions for rural areas

Background Despite emerging research on novel mobility solutions in urban areas, there have been few attempts to explore the relevance and sustainability of these solutions in rural contexts. Furthermore, existing research addressing rural mobility solutions typically focuses on a specific user group, such as local residents, second-home owners, or tourists. In this paper, we study the social inclusivity, economic viability, and environmental impacts of novel mobility solutions in rural contexts based on published scholarly literature. When doing so, we bring both permanent and temporary residents of rural areas under one research framework. Methods We used grey literature to identify and categorise novel mobility solutions, which have been applied in European rural areas and are suitable for travelling longer distances. By using six service flexibility variables, we reached four categories of novel mobility solutions: semi-flexible demand-responsive transport, flexible door-to-door demand-responsive transport, car-sharing, and ride-sharing. We analysed the social inclusivity, economic viability, and environmental impacts of those categories based on criteria and evidence identified from scholarly literature by including the perspectives of both permanent and temporary residents of rural areas. Conclusion: Integration of the needs of various user groups is essential when aiming to achieve the provision of environmentally, socially, and economically sustainable mobility solutions in rural areas. Results Our findings revealed that while single novel mobility solutions are seldom applicable for all rural travellers, strong spatial and temporal synergies exist when combining different solutions. The need for a connected and flexible set of mobility solutions sensitive to the temporal and spatial patterns of mobility needs is inevitable. Accessible and easily understandable information on routing, booking, and ticketing systems, as well as cooperation, shared values, and trust between various parties, are key success factors for sustainable rural mobility. Conclusion Integration of the needs of various user groups is essential when aiming to achieve the provision of environmentally, socially, and economically sustainable mobility solutions in rural areas.Peer reviewe