Combining Analytics and Simulation Methods to Assess the Impact of Shared, Autonomous Electric Vehicles on Sustainable Urban Mobility

Urban mobility is currently undergoing three fundamental transformations with the sharing economy, electrification, and autonomous vehicles changing how people and goods move across cities. In this paper, we demonstrate the valuable contribution of decision support systems that combine data-driven analytics and simulation techniques in understanding complex systems such as urban transportation. Using the city of Berlin as a case study, we show that shared, autonomous electric vehicles can substantially reduce resource investments while keeping service levels stable. Our findings inform stakeholders on the trade-off between economic and sustainability-related considerations when fostering the transition to sustainable urban mobilit

Graph-based Algorithms for Smart Mobility Planning and Large-scale Network Discovery

Graph theory has become a hot topic in the past two decades as evidenced by the increasing number of citations in research. Its applications are found in many fields, e.g. database, clustering, routing, etc. In this thesis, two novel graph-based algorithms are presented. The first algorithm finds itself in the thriving carsharing service, while the second algorithm is about large graph discovery to unearth the unknown graph before any analyses can be performed. In the first scenario, the automatisation of the fleet planning process in carsharing is proposed. The proposed work enhances the accuracy of the planning to the next level by taking an advantage of the open data movement such as street networks, building footprints, and demographic data. By using the street network (based on graph), it solves the questionable aspect in many previous works, feasibility as they tended to use rasterisation to simplify the map, but that comes with the price of accuracy and feasibility. A benchmark suite for further research in this problem is also provided. Along with it, two optimisation models with different sets of objectives and contexts are proposed. Through a series of experiment, a novel hybrid metaheuristic algorithm is proposed. The algorithm is called NGAP, which is based on Reference Point based Non-dominated Sorting genetic Algorithm (NSGA-III) and Pareto Local Search (PLS) and a novel problem specific local search operator designed for the fleet placement problem in carsharing called Extensible Neighbourhood Search (ENS). The designed local search operator exploits the graph structure of the street network and utilises the local knowledge to improve the exploration capability. The results show that the proposed hybrid algorithm outperforms the original NSGA-III in convergence under the same execution time. The work in smart mobility is done on city scale graphs which are considered to be medium size. However, the scale of the graphs in other fields in the real-world can be much larger than that which is why the large graph discovery algorithm is proposed as the second algorithm. To elaborate on the definition of large, some examples are required. The internet graph has over 30 billion nodes. Another one is a human brain network contains around 1011 nodes. Apart of the size, there is another aspect in real-world graph and that is the unknown. With the dynamic nature of the real-world graphs, it is almost impossible to have a complete knowledge of the graph to perform an analysis that is why graph traversal is crucial as the preparation process. I propose a novel memoryless chaos-based graph traversal algorithm called Chaotic Traversal (CHAT). CHAT is the first graph traversal algorithm that utilises the chaotic attractor directly. An experiment with two well-known chaotic attractors, Lozi map and Rössler system is conducted. The proposed algorithm is compared against the memoryless state-of-the-art algorithm, Random Walk. The results demonstrate the superior performance in coverage rate over Random Walk on five tested topologies; ring, small world, random, grid and power-law. In summary, the contribution of this research is twofold. Firstly, it contributes to the research society by introducing new study problems and novel approaches to propel the advance of the current state-of-the-art. And Secondly, it demonstrates a strong case for the conversion of research to the industrial sector to solve a real-world problem

Public Bikesharing in North America During a Period of Rapid Expansion: Understanding Business Models, Industry Trends & User Impacts, MTI Report 12-29

Public bikesharing—the shared use of a bicycle fleet—is an innovative transportation strategy that has recently emerged in major cities around the world, including North America. Information technology (IT)-based bikesharing systems typically position bicycles throughout an urban environment, among a network of docking stations, for immediate access. Trips can be one-way, round-trip, or both, depending on the operator. Bikesharing can serve as a first-and-last mile connector to other modes, as well as for both short and long distance destinations. In 2012, 22 IT-based public bikesharing systems were operating in the United States, with a total of 884,442 users and 7,549 bicycles. Four IT-based programs in Canada had a total of 197,419 users and 6,115 bicycles. Two IT-based programs in Mexico had a total of 71,611 users and 3,680 bicycles. (Membership numbers reflect the total number of short- and long-term users.) This study evaluates public bikesharing in North America, reviewing the change in travel behavior exhibited by members of different programs in the context of their business models and operational environment. This Phase II research builds on data collected during our Phase I research conducted in 2012. During the 2012 research (Phase I), researchers conducted 14 expert interviews with industry experts and public officials in the United States and Canada, as well as 19 interviews with the manager and/or key staff of IT-based bikesharing organizations. For more information on the Phase I research, please see the Shaheen et al., 2012 report Public Bikesharing in North America: Early Operator and User Understanding. For this Phase II study, an additional 23 interviews were conducted with IT-based bikesharing organizations in the United States, Canada, and Mexico in Spring 2013. Notable developments during this period include the ongoing expansion of public bikesharing in North America, including the recent launches of multiple large bikesharing programs in the United States (i.e., Citi Bike in New York City, Divvy in Chicago, and Bay Area Bike Share in the San Francisco Bay Area). In addition to expert interviews, the authors conducted two kinds of surveys with bikesharing users. One was the online member survey. This survey was sent to all people for whom the operator had an email address.The population of this survey was mainly annual members of the bikesharing system, and the members took the survey via a URL link sent to them from the operator. The second survey was an on-street survey. This survey was designed for anyone, including casual users (i.e., those who are not members of the system and use it on a short-term basis), to take “on-street” via a smartphone. The member survey was deployed in five cities: Montreal, Toronto, Salt Lake City, Minneapolis-Saint Paul, and Mexico City. The on-street survey was implemented in three cities: Boston, Salt Lake City, and San Antonio

Contributions to sustainable urban transport : decision support for alternative mobility and logistics concepts

Increasing transport activities in cities are a substantial driver for congestion and pollution, influencing urban populations’ health and quality of life. These effects are consequences of ongoing urbanization in combination with rising individual demand for mobility, goods, and services. With the goal of increased environmental sustainability in urban areas, city authorities and politics aim for reduced traffic and minimized transport emissions. To support more efficient and sustainable urban transport, this cumulative dissertation focuses on alternative transport concepts. For this purpose, scientific methods and models of the interdisciplinary information systems domain combined with elements of operations research, transportation, and logistics are developed and investigated in multiple research contributions. Different transport concepts are examined in terms of optimization and acceptance to provide decision support for relevant stakeholders. In more detail, the overarching topic of urban transport in this dissertation is divided into the complexes urban mobility (part A) in terms of passenger transport and urban logistics (part B) with a focus on the delivery of goods and services. Within part A, approaches to carsharing optimization are presented at various planning levels. Furthermore, the user acceptance of ridepooling is investigated. Part B outlines several optimization models for alternative urban parcel and e-grocery delivery concepts by proposing different network structures and transport vehicles. Conducted surveys on intentional use of urban logistics concepts give valuable hints to providers and decision makers. The introduced approaches with their corresponding results provide target-oriented support to facilitate decision making based on quantitative data. Due to the continuous growth of urban transport, the relevance of decision support in this regard, but also the understanding of the key drivers for people to use certain services will further increase in the future. By providing decision support for urban mobility as well as urban logistics concepts, this dissertation contributes to enhanced economic, social, and environmental sustainability in urban areas

Optimizing energy consumption in smart cities’ mobility: electric vehicles, algorithms, and collaborative economy

Mobility and transportation activities in smart cities require an increasing amount of energy. With the frequent energy crises arising worldwide and the need for a more sustainable and environmental friendly economy, optimizing energy consumption in these growing activities becomes a must. This work reviews the latest works in this matter and discusses several challenges that emerge from the aforementioned social and industrial demands. The paper analyzes how collaborative concepts and the increasing use of electric vehicles can contribute to reduce energy consumption practices, as well as intelligent x-heuristic algorithms that can be employed to achieve this fundamental goal. In addition, the paper analyzes computational results from previous works on mobility and transportation in smart cities applying x-heuristics algorithms. Finally, a novel computational experiment, involving a ridesharing example, is carried out to illustrate the benefits that can be obtained by employing these algorithms.Peer ReviewedPostprint (published version

Transportation planning via location-based social networking data : exploring many-to-many connections

textToday’s metropolitan areas see changes in populations and land development occurring at faster rates than transportation planning can be updated. This dissertation explores the use of a new dataset from the location-based social networking spectrum to analyze origin-destination travel demand within Austin, TX. A detailed exploration of the proposed data source is conducted to determine its overall capabilities with respect to the Austin area demographics. A new methodology is proposed for the creation of origin-destination matrices using a peer-to-peer modeling structure. This methodology is compared against a previously examined and more traditional approach, the doubly-constrained gravity model, to understand the capabilities of both models with various friction functions. Each method is examined within the constructs of the study area’s existing origin-destination matrix by examining the coincidence ratios, mean errors, mean absolute errors, frequency ratios, swap ratios, trip length distributions, zonal trip generation and attraction heat maps, and zonal origin-destination flow patterns. Through multiple measures, this dissertation provides initial interpretations of the robust Foursquare data collected for the Austin area. Based upon the data analytics performed, the Foursquare data source is shown to be capable of providing immensely detailed spatial-temporal data that can be utilized as a supplementary data source to traditional transportation planning data collection methods or in conjunction with other data sources, such as social networking platforms. The examination of the proposed peer-to-peer methodology presented within this dissertation provides a first look at the potential of many-to-many modeling for transportation planning. The peer-to-peer model was found to be superior to the doubly-constrained gravity model with respect to intrazonal trips. Furthermore, the peer-to-peer model was found to better estimate productions, attractions, and zone to zone movements when a linear function was used for long trips, and was computationally more proficient for all models examined.Civil, Architectural, and Environmental Engineerin

Serving travel demand with autonomous vehicles in Barcelona

Estat de l'art del vehicle autònom i potencial de desenvolupament en l'entorn urbà. Aplicació al cas de BarcelonaOutgoin

Public Bikesharing in North America: Early Operator and User Understanding, MTI Report 11-19

This study evaluates public bikesharing in North America, reviewing the advances in technology and major events during its rapid expansion. We conducted 14 interviews with industry experts, public officials, and governmental agencies in the United States and Canada during summer 2011/spring 2012 and interviewed all 19 IT-based bikesharing organizations in the United States and Canada in spring 2012. Several bikesharing insurance experts were also consulted in spring 2012. Notable developments during this period include the emergence of a close partnership between vendor and operator and technological advances, such as mobile bike-docking stations that can be moved to different locations and real-time bike/station tracking to facilitate system rebalancing and provide user information

Analysis of business opportunities for car-related shared mobility services

The confluence of digital technology and connectivity has led, in several sectors, to the rise of application-based shared economy activities. In particular, in the mobility sector, there has been an increase in on-demand shared transport initiatives. These new business models are transforming the urban mobility sector from a limited choice of transport services to a scenario full of new players offering different types of demand responsive mobility services. This change in urban mobility also has an impact on the automotive industry, where manufacturers such as SEAT not only see the opportunity for their cars to be used by these new services, but begin as well to see themselves as potential providers of mobility services. Even so, for the time being, the most popular and widespread shared mobility services remain unprofitable. For this reason, the thesis analyses the business models of the new shared mobility services, with the aim of proposing improvements to increase their profitability. It also identifies the different uses that can be given to them and the factors to be taken into account in the design and implementation process. The methodology used for this research is the study of cases, which have been conducted through surveys and interviews. The research begins with the study of the current and future mobility ecosystem and the behaviour of the automobile industry in this context. Next, the following five case studies are developed. The first analyses the business models of shared mobility services provided by cars –i.e. carsharing, ridesharing, and ride-hailing services– to find out synergies between them for proposing a combined business model. The second aims to study the mobility patterns of citizens and their intention to use shared mobility services. The third and fourth case studies focus on the identification of design factors and use cases of on-demand shared ride-hailing services. This part of the research looks at these services given their potential when cars are autonomous, and the opportunities that the software they use represents for public transport, with buses that could become demand responsive transport services. Finally, the fifth case study analyses the mobility ecosystem from the perspective of local governments and providers of technology and insurance, studies the feasibility of the combination of uses in shared mobility services, and detects the barriers faced by these new business models.La confluència de la tecnologia digital i la connectivitat ha motivat, en diversos sectors, l'auge de les activitats d'economia compartida basades en aplicacions. Concretament, en el sector de la mobilitat s'ha experimentat un creixement de les iniciatives de transport compartit a demanda. Aquests nous models de negoci estan transformant el sector de la mobilitat urbana, que passa de tenir una oferta limitada de serveis de transport a un escenari ple de nous actors que ofereixen diferents serveis de mobilitat a la carta. Aquest canvi en la mobilitat urbana també impacta en la indústria de l'automòbil, on fabricants com SEAT no només veuen l'oportunitat que els seus cotxes siguin utilitzats per aquests nous serveis, sinó que a més a més es comencen a veure com a possibles proveïdors de serveis de mobilitat. Tot i això, de moment, els serveis de mobilitat compartida més populars i estesos continuen sense ser rendibles. Per aquesta raó, la tesi portada a terme analitza els models de negoci dels nous serveis de mobilitat compartida, amb l’objectiu de proposar millores que permetin augmentar la seva rendibilitat. També s'identifiquen els diferents usos que se'ls hi pot donar i els factors que cal tenir en compte a l’hora de dissenyar-los i implementar-los. La metodologia utilitzada per a aquesta investigació és l'estudi de casos, els quals s'han desenvolupat a través d'enquestes i entrevistes. La recerca comença amb l'estudi de l'ecosistema de mobilitat actual i futur, i el comportament de la indústria de l'automòbil en aquest context. Tot seguit es desenvolupen cinc casos d'estudi. En el primer s'analitzen els models de negoci dels serveis de mobilitat compartida que s’ofereixen amb cotxes, es a dir, els serveis de carsharing, ridesharing i ride-hailing, amb la finalitat de trobar sinergies entre ells per a proposar un model de negoci combinat. El segon té com a objectiu estudiar els patrons de mobilitat dels ciutadans i la seva intenció en utilitzar els serveis de mobilitat compartida. El tercer i el quart cas d'estudi se centren a identificar els factors de disseny i els casos d'ús dels serveis d'on- demand shared ride-hailing. Aquesta part de la investigació es fixa en aquests serveis pel potencial que poden tenir quan els cotxes siguin autònoms, i per les oportunitats que el software que utilitzen representen per al transport públic, amb busos que podrien convertir-se en serveis de transport a demanda. Per últim, en el cinquè cas d'estudi s'analitza l’ecosistema de mobilitat des de la perspectiva dels governs locals i dels proveïdors de tecnologia i d'assegurances, s'estudia la viabilitat de la combinació d'usos en els serveis de mobilitat compartida, i es detecten quines són les barreres amb què es troben aquests nous models de negoci.La confluencia de la tecnología digital y la conectividad ha motivado, en varios sectores, el auge de las actividades de economía compartida basadas en aplicaciones. Concretamente, en el sector de la movilidad se ha experimentado un crecimiento de las iniciativas de transporte compartido a la demanda. Estos nuevos modelos de negocio están transformando el sector de la movilidad urbana, que pasa de tener una oferta limitada de servicios de transporte a un escenario lleno de nuevos actores que ofrecen diferentes servicios de movilidad a la carta. Este cambio en la movilidad urbana también impacta en la industria del automóvil, donde fabricantes como SEAT no solo ven la oportunidad que sus coches sean utilizados por estos nuevos servicios, sino que además se empiezan a ver como posibles proveedores de servicios de movilidad. Aun así, por el momento, los servicios de movilidad compartida más populares y extendidos continúan sin ser rentables. Por esta razón, la tesis llevada a cabo analiza los modelos de negocio de los nuevos servicios de movilidad compartida, con el objetivo de proponer mejoras que permitan aumentar su rentabilidad. También se identifican los diferentes usos que se les puede dar y los factores a tener en cuenta en el proceso de diseño e implementación. La metodología utilizada para esta investigación es el estudio de casos, los cuales se han desarrollado por medio de encuestas y entrevistas. La investigación empieza con el estudio del ecosistema de movilidad actual y futuro, y el comportamiento de la industria del automóvil en este contexto. Posteriormente se desarrollan cinco casos de estudio. En el primero se analizan los modelos de negocio de los servicios de movilidad compartida que se ofrecen con coches, es decir, los servicios de carsharing, ridesharing y ride-hailing, con el fin de encontrar sinergias entre ellos para proponer un modelo de negocio combinado. El segundo tiene como objetivo estudiar los patrones de movilidad de los ciudadanos y su intención al utilizar los servicios de movilidad compartida. El tercer y el cuarto caso de estudio se centran en identificar los factores de diseño y los casos de uso de los servicios de on-demand shared ride-hailing. Esta parte de la investigación se centra en estos servicios por su potencial con la llegada del coche autónomo, y por las oportunidades que el software que utilizan representan para el transporte público, con autobuses que podrían convertirse en servicios de transporte a la demanda. Por último, en el quinto caso de estudio se analiza el ecosistema de movilidad desde la perspectiva de los gobiernos locales y de los proveedores de tecnología y seguros, se estudia la viabilidad de la combinación de usos en los servicios de movilidad compartida, y se detectan cuáles son las barreras para estos nuevos modelos de negocio