Готові списки джерел за темами / Autonomous Mobility on Demand

Добірка наукової літератури з теми "Autonomous Mobility on Demand"

Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Autonomous Mobility on Demand"

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Salazar, Mauro, Nicolas Lanzetti, Federico Rossi, Maximilian Schiffer, and Marco Pavone. "Intermodal Autonomous Mobility-on-Demand." IEEE Transactions on Intelligent Transportation Systems 21, no. 9 (September 2020): 3946–60. http://dx.doi.org/10.1109/tits.2019.2950720.

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Azevedo, Carlos Lima, Katarzyna Marczuk, Sebastián Raveau, Harold Soh, Muhammad Adnan, Kakali Basak, Harish Loganathan, et al. "Microsimulation of Demand and Supply of Autonomous Mobility On Demand." Transportation Research Record: Journal of the Transportation Research Board 2564, no. 1 (January 2016): 21–30. http://dx.doi.org/10.3141/2564-03.

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Wen, Jian, Neema Nassir, and Jinhua Zhao. "Value of demand information in autonomous mobility-on-demand systems." Transportation Research Part A: Policy and Practice 121 (March 2019): 346–59. http://dx.doi.org/10.1016/j.tra.2019.01.018.

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Javanshour, Farid, Hussein Dia, and Gordon Duncan. "Exploring the performance of autonomous mobility on-demand systems under demand uncertainty." Transportmetrica A: Transport Science 15, no. 2 (October 3, 2018): 698–721. http://dx.doi.org/10.1080/23249935.2018.1528485.

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Dia, Hussein, and Farid Javanshour. "Autonomous Shared Mobility-On-Demand: Melbourne Pilot Simulation Study." Transportation Research Procedia 22 (2017): 285–96. http://dx.doi.org/10.1016/j.trpro.2017.03.035.

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Hao, Mingyang, Yanyan Li, and Toshiyuki Yamamoto. "Public Preferences and Willingness to Pay for Shared Autonomous Vehicles Services in Nagoya, Japan." Smart Cities 2, no. 2 (June 11, 2019): 230–44. http://dx.doi.org/10.3390/smartcities2020015.

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Анотація:
Shared autonomous vehicle systems are anticipated to offer cleaner, safer, and cheaper mobility services when autonomous vehicles are finally implemented on the roads. The evaluation of people’s intentions regarding shared autonomous vehicle services appears to be critical prior to the promotion of this emerging mobility on demand approach. Based on a stated preference survey in Nagoya, Japan, the preference for shared autonomous vehicle services as well as willingness to pay for these services were examined among 1036 respondents in order to understand the relationship between people’s socioeconomic characteristics and their preferred shared autonomous vehicle services. For this purpose, k-modes clustering technique was selected and six clusters were obtained. Six groups with respect to different interests on shared autonomous vehicle services were clustered. The result of correlation analysis and discussion of willingness to pay on services provided insightful results for the future shared autonomous vehicle services. This study not only aids in revealing the demands of customer different clusters, but also states the prospective needs of users for stakeholders from research, policymaker and industry field, who are preparing to work on promoting shared autonomous vehicle systems, and subsequently, develops an optimum transportation mode by considering both demand and services as a whole.
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Hogeveen, Peter, Maarten Steinbuch, Geert Verbong, and Auke Hoekstra. "Quantifying the Fleet Composition at Full Adoption of Shared Autonomous Electric Vehicles: An Agent-based Approach." Open Transportation Journal 15, no. 1 (May 17, 2021): 47–60. http://dx.doi.org/10.2174/1874447802115010047.

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Aims: Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Background: Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. Objective: To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. Methods: An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. Results: The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Conclusion: Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.
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Schnieder, Maren, Chris Hinde, and Andrew West. "Land Efficient Mobility: Evaluation of Autonomous Last Mile Delivery Concepts in London." International Journal of Environmental Research and Public Health 19, no. 16 (August 18, 2022): 10290. http://dx.doi.org/10.3390/ijerph191610290.

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Land efficient last mile delivery concepts are key to reducing the traffic in cities and to minimising its environmental impact. This paper proposes a decision support method that evaluates the autonomous delivery concept and applies it to one year’s worth of real parcel delivery data in London. Deliveries to modular and fixed lockers with autonomous delivery vans and road-based autonomous lockers (RAL) and sidewalk autonomous delivery robots (SADRs) have been simulated. Various types of autonomous delivery van fleets, depot locations, customer modes of transport, parcel demand levels, parcel locker network densities and adjustment frequencies of modular lockers are considered. A routing and scheduling algorithm is used to optimise delivery tours and vehicle choice. The optimisation algorithm finds both the optimal number of collection and delivery points (CDPs) and the delivery concept (e.g., modular lockers, sidewalk autonomous delivery robot) depending on the customer mode chosen. The results show that modular lockers which are adjusted weekly are the best option for the current or higher parcel demand levels and road-autonomous parcel lockers (RAL-R) are the best option at the lowest parcel demand level.
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Noh, Seungwon, Chang-Gyun Roh, Byeongsup Moon, and Jung-Ah Ha. "Defining Evaluation Criteria for Real-time Demand Response Autonomous Mobility." Journal of the Korea Academia-Industrial cooperation Society 23, no. 1 (January 31, 2022): 871–79. http://dx.doi.org/10.5762/kais.2022.23.1.871.

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Marczuk, Katarzyna A., Harold S. H. Soh, Carlos M. L. Azevedo, Der-Horng Lee, and Emilio Frazzoli. "Simulation Framework for Rebalancing of Autonomous Mobility on Demand Systems." MATEC Web of Conferences 81 (2016): 01005. http://dx.doi.org/10.1051/matecconf/20168101005.

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Дисертації з теми "Autonomous Mobility on Demand"

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Miller, Justin (Justin Lee). "Demand estimation and fleet management for autonomous mobility on demand systems." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113541.

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Анотація:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 131-137).
Mobility On Demand (MOD) systems are creating a paradigm shift in transportation, where mobility is provided not through personally owned vehicles but rather through a fleet of shared vehicles. To maintain a high customer quality of service (QoS), MOD systems need to manage the distribution of vehicles under spatial and temporal fluctuations in customer demand. A challenge for MOD systems is developing and informing a customer demand model. A new proactive demand model is presented which correlates real-time traffic data to predict customer demand on short timescales. Traditional traffic data collection approaches use pervasive fixed sensors which are costly for system-wide coverage. To address this, new frameworks are presented for measuring real-time traffic data using MOD vehicles as mobile sensors. The frameworks are evaluated using hardware and simulation implementations of a real-world MOD system developed for MIT campus. First, a mobile sensing framework is introduced that uses camera and Lidar sensors onboard MOD shuttles to observe system-wide traffic. Through a principled approach for decoupling dependencies between observation data and vehicle motion, the framework provides traffic rate estimates comparable to those of costly fixed sensors. Second, an active sensing framework is introduced which quantifies demand uncertainty with a Bayesian model and routes mobile sensors to reduce parameter uncertainty. The active sensing framework reduces error in demand estimates over both short and long timescales when compared to baseline approaches. Given estimates of customer demand, the challenge for MOD systems is maintaining high customer QoS through fleet management. New automated fleet management planners are introduced for improving customer QoS in ride hailing, ride requesting, and ridesharing MOD operating frameworks. The planners are evaluated using data-driven simulation of the MIT MOD system. For ride hailing, to address the challenge of missed customers, a chance-constrained planner is introduced for positioning vehicles at likely customer hailing locations. The chance-constrained planner provides a significant improvement in the number of served hailing customers over a baseline exploration approach. For ride requesting, to address the challenge of high customer wait times, a predictive positioning planner is introduced to position vehicles at key locations in the MOD system based on customer demand. The predictive positioning planner provides a reduction in service times for requesting customers compared to a baseline waiting approach. For ridesharing, incorrect assumptions on customer preference for transit delays can lead to poor realized customer QoS. A ridesharing planner is introduced for assigning customers to vehicles based on a trained ratings-based QoS model. The ridesharing planner provides robust performance over a range of unknown customer preferences compared to approaches with assumed customer preferences.
by Justin Lee Miller.
Ph. D.
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2

Chen, Yu Xin (Yu Xin Leo). "Simulation-based design of integrated public transit and shared autonomous mobility-on-demand systems." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120641.

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Анотація:
Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 89-95).
The autonomous vehicle (AV) is poised to be one of the most disruptive technologies in the transportation industry. The advent of three major trends in transportation: automation, on-demand mobility and ride-sharing, are set to revolutionize the way we travel. The forthcoming adoption and commercialization of AVs are expected to have extensive impacts on our road networks, congestion, safety, land use, public transportation (PT) and more. Rapid advances in AV technology are convincing many that AV services will play a significant role in future transportation systems. The advancement of AVs presents both opportunities and threats to transportation. It has the potential to significantly impact traffic congestion, traffic accidents, parking and VMT (vehicle miles traveled), especially for people that are not able to drive such as children and elderly people. Motivated by the potential of autonomous vehicles, authorities around the world are preparing for this revolution in transport and deems this an important research direction that requires significant investigation. This thesis tackled and contributed to three main research questions related to the impact of autonomous vehicles on transportation systems. First, this thesis proposes a simulation-based approach to the design and evaluation of integrated autonomous vehicle and public transportation systems. We highlight the transit-orientation by respecting the social-purpose considerations of transit agencies (such as maintaining service availability and ensuring equity) and identifying the synergistic opportunities between AV and PT. Specifically, we identified that AV has a strong potential to serve first-mile connections to the PT stations and provide efficient and affordable shared mobility in low-density suburban areas that are typically inefficient to serve by conventional fixed-route PT services. The design decisions reflect the interest of multiple stakeholders in the system. Second, the interaction between travelers (demand) and operators (supply) is modeled using a system of equations that is solved as a fixed-point problem through an iterative procedure. In this, we developed demand and supply as two sub-problems. The demand will be predicted using a nested logit model to estimate the volume for different modes based on modal attributes. The supply will use a simulation platform capable of incorporating critical operational decisions on factors including fleet sizes, vehicle capacities, sharing policies, fare schemes and hailing strategies such as in-advance and on-demand requests. Using feedback between demand and supply, we enable interactions between the decisions of the service operator and those of the travelers, in order to model the choices of both parties. Finally, this thesis systematically optimizes service design variables to determine the best outcome in accordance to AV+PT stakeholder goals. Optimization objective functions can be formulated to reflect the different objectives of different stakeholders. In this paper, we specifically propose and develop a simulation-based service design method where we quantify various benefits and costs to reflect the objectives of key AV+PT stakeholders. We simulate the service with different sets of system settings and identify the highest performing set. We employ a case study of regional service contracting to showcase the ability of this method to inform AV+PT service design. We tested our approach with a case study area in a major European city on an agent-based simulation platform, amod-abm. Agent-based simulation has the advantage of capturing individual (agent) behaviors and the interactions of the various individual agents in a realistic synthetic environment where the intent is to re-create a complex phenomenon of mobility on demand service delivered by AV. Although this thesis will focus on a major European city, the general framework and methodologies proposed here can be widely applicable. The thesis concludes that the demand-supply interaction can be effective for designing and assessing the role of AV technology in our mobility systems. Moreover, simulation-based optimization can be an effective method for transit agencies to make decisions that support their overall AV related transport strategy as well as operational planning.
by Yu Xin Chen.
S.M. in Transportation
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Wen, Jian S. M. Massachusetts Institute of Technology. "Value of information in dispatching shared autonomous mobility-on-demand systems : a simulation framework." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115797.

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Анотація:
Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 87-91).
The concept of shared mobility-on-demand (MoD) systems describes an innovative mode of transportation in which rides are tailored as per the immediate requests in a shared manner. Convenience of hailing, ease of transactions, and economic efficiency of crowd-sourcing the rides have made these services very attractive today. It is anticipated that autonomous vehicle (AV) technology may further improve the economics of such services by reducing the operational costs. The design and operation of such an shared autonomous mobility-on-demand (AMoD) system is therefore an important research direction that requires significant investigation. This thesis mainly addresses three issues revolving around the dispatching strategies of shared AMoD systems. First, it responds to the special dispatching need that is critical for effective AMoD operation. This includes a dynamic request-vehicle assignment heuristic and an optimal rebalancing policy. In addition, the dispatching strategies also reflect transit-oriented designs in two ways: (a) the objective function embodies the considerations of service availability and equity through the support of various hailing policies; and (b), the service facilitates first-mile connections to public transportation. Second, this thesis models the interaction between demand and supply through simulation. Using the level of service as interface, this mechanism enables feedback between operators and travelers to more closely represent the choices of both parties. A fixed-point approach is then applied to reach balance iteratively, estimating both the demand volume and the system performance at equilibrium. The results from the simulation support decision-making with regard to comprehensive system design problems such as fleet sizing, vehicle capacities and hailing policies. Third, the thesis evaluates the value of demand information through simulation experiments. To quantify the system performance gain that can be derived from the demand information, this thesis proposes to study two dimensions, level of information and value of information, and builds up the relationship between them. The numerical results help rationalize the efforts operators should spend on data collection, information inference and advanced dispatching algorithms. This thesis also implements an agent-based modeling platform, amod-abm, for simulating large-scale shared AMoD applications. Specifically, it models individual travelers and vehicles with demand-supply interaction and analyzes system performance through various metrics of indicators. This includes wait time, travel time, detour factor and service rate at the traveler's side, as well as vehicle distance traveled, load and profit at the operator's side. A case study area in London is selected to support the presentation of methodology. Results show that encouraging ride-sharing and allowing in-advance requests are powerful tools to enhance service efficiency and equity. Demand information from in-advance requests also enables the operator to plan service ahead of time, which leads to better performance and higher profit. The thesis concludes that the demand-supply interaction can be effective for defining and assessing the roles of AV technology in our future transportation systems. Combining efficient dispatching strategies and demand information management tools is also important for more affordable and efficient services.
by Jian Wen.
S.M. in Transportation
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Berrada, Jaâfar. "Analyse et optimisation technico-économiques des nouveaux services de mobilité basés sur l'usage des véhicules autonomes." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC1002.

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Les véhicules autonomes deviennent de plus en plus une réalité, qui à la fois promet d’améliorer, de manière plus ou moins brutale, les systèmes de transport urbain. En effet, cette technologie présente le potentiel de réduire la consommation d’énergie, le nombre d’accidents, les coûts de déplacement ainsi que l’occupation de l’espace urbain. Cependant, des obstacles à la mise en œuvre et à la pénétration en masse du marché subsistent. Sur le plan économique, les coûts initiaux seront probablement peu abordables. Au niveau social, les utilisateurs pourraient être réticents à changer leurs habitudes de déplacement quotidiennes. Techniquement, les interactions avec les autres composants du système de transport restent incertaines. Les défis en matière de responsabilité, de sécurité, d'éthique et de confidentialité des données doivent aussi être relevés.Cette thèse contribue à l'étude ex-ante des systèmes de mobilité basés sur les véhicules autonomes à travers l'identification, la conception et l'évaluation de modèles d'affaires articulés autour des véhicules autonomes. En particulier, elle propose une analyse systémique des «nouveaux» services de mobilité (notamment les services d'autopartage, de covoiturage et de taxi) pour identifier finalement les taxis autonomes (aTaxis) et les navettes autonomes (aTransit) en tant que deux des formes de services les plus pertinentes qui pourront bénéficier d'une large diffusion. Ensuite, nous nous concentrons sur un service d'aTaxis et nous proposons un cadre stratégique pour la construction d’un modèle microéconomique qui permet d’analyser les décisions stratégiques d’un opérateur de services de taxis autonomes. Le cadre stratégique se compose de trois niveaux (opérationnel, tactique et stratégique) et intègre trois forces de pression (la réglementation, les coûts unitaires et les préférences de la demande). Une application est ensuite réalisée sur une zone stylisée (Orbicity) et un cas réel urbain (Palaiseau, une ville de la région parisienne).Les résultats de la simulation montrent que l’automatisation peut améliorer à la fois les performances de mobilité et l’efficacité économique du système de transport urbain. De plus, les économies de densité de l'offre et de la demande sont évaluées en contrôlant à la fois la taille de la flotte et le nombre d'utilisateurs pour une zone d'étude fixe. En particulier, l'application sur Palaiseau a prouvé que l’utilisation de dix véhicules supplémentaires impliquerait 1 % de plus d'utilisateurs (+15 passagers) et 50 % de moins de profit. Une enquête des préférences déclarées appuie le modèle stratégique et montre que les aTaxis seront probablement utilisés pour les trajets quotidiens de 2 à 5 km par deux profils d’utilisateur: (1) les jeunes utilisateurs non motorisés (âgés de moins de 30 ans) et (2) la population active motorisée âgée de 30 à 50 ans.La thèse adopte une approche interdisciplinaire combinant (1) une analyse qualitative qui commence par une revue des travaux existants appuyée ensuite d’abord par une analyse marketing de Business Models basés sur les véhicules autonomes puis par une analyse systémique d’un service de aTaxis et (2) une analyse quantitative, située à mi-chemin entre la microéconomie et la simulation spatiale
Autonomous Vehicles (AV) are becoming more of a reality, promising beneficial yet potentially disrupting changes to our urban transportation systems. This technology presents the potential to reduce energy consumption and crash occurrences, cut travel costs and minimize urban space occupancy for parking purposes. Yet barriers to implementation and mass-market penetration remain. Economically, the upfront costs in the initial stage will likely lack affordability. Socially, users could be reluctant to change their daily travel routines. Technically, the interactions with the other components of the transportation system remain uncertain. There are other challenges regarding liability, security, ethics and data privacy, too.This thesis contributes to the ex-ante study of AV-based mobility systems through the identification, design and assessment of upcoming Business Models (BM) articulated around AVs. In particular, it brings about a systemic analysis of “new” mobility services (especially car-sharing, carpooling and ride-sourcing services) in order to identify autonomous taxis (aTaxis) and autonomous shuttles (aTransit) as two of the most relevant forms of services that may enjoy wide spreading. Then, we focus on a service of aTaxis and we put forward a microeconomic model framework to evaluate strategic setups of aTaxis provider. The model framework comprises three levels (operational, tactical and strategic), and integrates three pressure forces (regulation, unit costs and demand preferences). An application is then conducted on a stylized area (Orbicity) and a real urban case (Palaiseau, a city in Paris area).Simulation results show that automation has the potential to improve both the mobility performances and the economic efficiency of the urban transportation system. Additionally, the density economies of supply and demand are evaluated by controlling both the fleet size and the number of users for a fixed study area. In particular, the framework application on Palaiseau proved that increasing by ten the fleet size of aTaxis involves 1% more users (+15 passengers) yet 50% less of profit. A stated-preference survey supports the model framework and suggests that aTaxis will likely be used for short-distance (2 to 5 km) commuting trips by two user profiles: (1) non-motorized young users (less than 30 years old) and (2) motorized active population between 30 and 50 years old.The thesis takes an interdisciplinary approach combining (1) a qualitative analysis that starts from a review of existing works and adds first a marketing analysis of Business Models based on AVs and second a systemic analysis of an aTaxis service, and (2) a quantitative analysis, situated midway between microeconomics and spatial simulation
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Zhou, Fan. "The impacts of car-sharing and shared autonomous vehicles on urban mobility: Towards a sustainable future." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/121497/1/Fan_Zhou_Thesis.pdf.

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This dissertation presents a big-picture view for policymakers and related stakeholders regarding the future development of car-sharing services. Car sharing has the potential to significantly disrupt the personal mobility market, particularly on the dawn of self-driving cars. Thus, understanding car-sharing service's market penetration and implications are urgently needed. Studies in this thesis aim to forecast the penetration of car-sharing, to investigate if car-sharing influence consumers' vehicle ownership decision, and to explore the impacts of car-sharing on households' mode choice decision.
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ARCORACI, ANDREA. "Sistemi Interattivi a supporto dei Veicoli Autonomi. User Experience all'interno del concept di mobilità Pop.Up Next." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2915201.

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ROMERO, LÓPEZ ALBERTO. "Optimal operating strategies for first/last mile feeder services due to the arrival of automated vehicles : Case study: suburban areas around tunnelbana, pendeltåg and lokalbana corridors in Stockholm." Thesis, KTH, Transportplanering, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276769.

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With the improvements of the vehicle technology related with connectivity, sharing, automation and electrification and as a solution to the problems that cities are facing, such as an intense population growth and pollution, there are new forms of mobility that are or will be created within the framework of the future mobility. In this context, the arrival of driverless autonomous vehicles will provoke an irreversible change supporting the implementation of new forms of mobility or improving the existent. One factor that will help to do feasible the improvement of the existent mobility is the reduction of costs due to the arrival of autonomous vehicles, what will make ondemand transportation competitive under certain circumstances when comparing costs between it and fixed route systems. This thesis studies for the case of the metro/rail corridors in the metropolitan area of Stockholm which areas are suitable to implement Demand Responsive Transport (DRT) according to urban configuration and access to transit parameters. Once the identification is done, a model to compare between two different operating strategies for feeder services is applied to obtain which one is optimal under different stages of development of the technology related with the vehicles in the fields of automation and electrification. The model used, with additions to existing ones to adapt it to the use of it to real scenarios, gives numerical results for the four considered stages, showing the importance of the travel demand and the street sinuosity on the results and selection of the optimal. The method and criteria developed contributes to have a clear identification of the areas in which the implementation of the DRT services would be feasible in a future mobility scheme.
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Rimjha, Mihir. "On Demand Mobility Cargo Demand Estimation." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/85590.

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Анотація:
Recent developments in the shipping industry have opened some unprecedented trade opportunities on various levels. Be it individual consumption or business needs, the thought of receiving a package on the same day or within 4-hour from some other business or industry in the urban area is worth appreciating. The congestion on ground transportation modes is higher than ever. Since currently the same-day delivery in urban areas is carried mainly by ground modes, the catchment area of this delivery service is limited. The On-Demand Mobility for cargo can elevate the concept of express shipping in revolutionary ways. It will not only increase the catchment area thereby encompassing more business and consumers but will also expedite the delivery as these vehicles will fly over the ground traffic. The objective of this study was to estimate the total demand for ODM Cargo operations and study its effect on ODM passenger operations. The area of interest for this study was Northern California (17 counties). Annual cargo flows in the study area were rigorously analyzed through databases like Transearch, Freight Analysis Framework-4, and T-100 International for freight. The results of this study are presented through a parametric analysis of market share. The end product also includes the flight trajectories (with flight plan) of daily ODM cargo flights in the study region. The On-Demand Mobility cargo operations are expected to complement passenger On-Demand Mobility operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements. Since the movement of cargo is mostly done by private companies, the detailed records of shipments are often not public knowledge.
Master of Science
The recent advancements in shipping industry has made transfer of goods both domestic and international, swifter and more reliable. Nowadays, some business and consumers in urban areas have the options of few-hours or same day delivery. Currently the same-day delivery in urban areas is carried mainly by ground modes (trucks) and hence the catchment area of this delivery service is limited. Adding to it, the traffic congestion on the urban roads is a major hinderance in growth of such services. The On-Demand Mobility for cargo can reform express shipping in revolutionary ways. The concept vehicle can fly over the ground traffic. Therefore, it will increase the catchment area thereby encompassing more business and consumers, along with faster delivery options in currently serviced areas. For the study, we analyzed different databases for annual cargo flows in the region. Seventeen counties in the Northern California were chosen as the study area (or region). The study was focused on estimating the potential market (demand) for the On-Demand Mobility Cargo operations. Multiple set of results were calculated for different market shares that On-Demand Mobility can potentially capture in cargo operations. Flight trajectories (with flight plan) for daily ODM cargo flights were the final product. The On-Demand Mobility cargo operations are expected to complement passenger ODM operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements.
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9

Deng, Xiao Yan. "Cost-driven autonomous mobility." Thesis, Heriot-Watt University, 2007. http://hdl.handle.net/10399/2071.

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Developments in distributed system technology facilitate the sharing of resources, even at a global level. This thesis explores sharing computational resources using mobile computations, agents, and autonomic techniques. We propose autonomous mobile programs (AMPs) which are aware of their resource needs and sensitive to the environment in which they execute. AMPs periodically use a cost model to decide where to execute in a network. Unusually this form of autonomous mobility affects only where the program executes and not what it does. We present a generic AMP cost modei, together with a validated instantiation and comparative performance results for four AMPs. We demonstrate that AMPs are able to dynamically relocate themselves to minimise execution time in the presence of varying network resources. Collections of AMPs effectively perform decentralised dynamic load balancing. Experiments on small LANs show that collections of AMPs quickly obtain and maintain optimal or near-optimal ball1nce. The advantages of our decentralised approach are that it has the potential to scale to very large and dynamic networks, and to achieve improved balance, and offers guarantees to limit overheads under reasonable assumptions. In an autonomous mobile program, the program must contain explicit control of self-aware mobile coordination. To encapsulate this for common patterns of computation over collections, autonomous mobility skeletons (AMSs) are proposed. These are akin to algorithmic skeletons in being polymorphic higher order functions, but where algorithmic skeletons abstract over parallel coordination, AMSs abstract over autonomous mobile coordination. AMS cost models have been built over collection iterations. The automap, autofold and Autolterator AMSs are presented, together with performance measurements for Jocaml, Java Voyager, and JavaGo implementations on LANs. An AMS considers only the cost of the current collective computation, but it is more useful to know the cost of the entire program. We have extended our AMS cost models to be parameterised on the cost of the remainder of the program. A cost calculus to estimate the costs for the remainder of a computation at arbitrary points has been built. An automatic Jocaml cost analyser based oil the calculus produces cost equations parameterised on program variables in context, and may be used to find both cost in higher-order functions and the cost for the remainder of the program. Costed autonomous mobility skeletons (CAMSs) have been built, which not only encapsulate common patterns of autonomous mobility but take additional cost parameters to provide costs for the remainder of the program. Potential performance improvements are assessed by comparing CAMS to AMS programs. The results show that CAMS programs perform more effectively than AMS programs, because they have more accurate cost information. Hence a CAMS program may move to a faster location when the corresponding AMS program does not.
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10

Syed, Nida Umme-Saleem. "On Demand Mobility Commuter Aircraft Demand Estimation." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78879.

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On-Demand Mobility (ODM) is a concept to address congestion problems. Using electric aircraft and vertical take-off with limited landing (VTOL) capabilities, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A conditional logit model was developed to estimate mode choice behavior and to estimate ODM demand; presenting automobile and public transportation as the two competing modes to ODM. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. Nine scenarios were run varying the input for a base fare, landing fare, cost per-passenger-mile, auto operational costs, and ingress (waiting) times. The results yielded sensitivity of demand to all these parameters and especially showed a great difference in demand when auto costs were decreased from the standard American Automobile Association (AAA) cost per mile to a likely, future auto operating cost. The challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1.
Master of Science
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Книги з теми "Autonomous Mobility on Demand"

1

Crute, Jeremy. Planning for autonomous mobility. Chicago, IL: American Planning Association, 2018.

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2

Rainbow, Roger. Meeting the demand for mobility. London: Shell International Petroleum Company, 1993.

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3

Jansen, W. J. International capital mobility and asset demand: Six empirical studies. [Amsterdam: Thesis Publishers], 1995.

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4

Texas Education Agency. Policy Analysis and Evaluation Division. and Teacher Supply, Demand, and Quality Policy Research Project (Tex.), eds. Texas teacher retention, mobility, and attrition. Austin, Tex: Texas Education Agency, Policy Analysis and Evaluation Division, 1995.

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5

Benabou, Roland. Social mobility and the demand for redistribution: The POUM hypothesis. Cambridge, MA: National Bureau of Economic Research, 1998.

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6

Hiscott, Robert D. Employment mobility in the nursing profession survey research report. Waterloo, Ont: Ontario Nursing Human Resources Data Centre, 1993.

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7

Luekens, Michael T. Teacher attrition and mobility: Results from the teacher follow-up survey, 2000-01. Washington, DC: National Center for Education Statistics, 2004.

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8

The peacetime tempo of air mobility operations: Meeting demand and maintaining readiness. Santa Monica, Calif: Rand, 2002.

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9

Organisation for Economic Co-operation and Development. and Seminar on International Mobility of Highly Skilled Workers: From Statistical Analyses to the Formulation of Policies (2001 : Paris, France), eds. International mobility of the highly skilled. Paris, France: Organisation for Economic Co-operation and Development, 2002.

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10

Sustainable transport, mobility management and travel plans. Farnham: Ashgate, 2011.

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Частини книг з теми "Autonomous Mobility on Demand"

1

Pavone, Marco. "Autonomous Mobility-on-Demand Systems for Future Urban Mobility." In Autonomous Driving, 387–404. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48847-8_19.

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2

Beiker, Sven. "Implementation of an Automated Mobility-on-Demand System." In Autonomous Driving, 277–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48847-8_14.

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3

Pavone, Marco. "Autonomous Mobility-on-Demand Systems for Future Urban Mobility." In Autonomes Fahren, 399–416. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45854-9_19.

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4

Javanshour, Farid, Hussein Dia, and Gordon Duncan. "Exploring System Characteristics of Autonomous Mobility On-Demand Systems Under Varying Travel Demand Patterns." In Intelligent Transport Systems for Everyone’s Mobility, 299–315. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7434-0_17.

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5

Yamin, Nuzhat, Syrine Belakaria, Sameh Sorour, and Mohamed Hefeida. "A Hierarchical Management Framework for Autonomous Electric Mobility-on-Demand Services." In Connected and Autonomous Vehicles in Smart Cities, 19–66. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, LLC, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429329401-2.

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6

Shen, Wen, and Cristina Lopes. "Managing Autonomous Mobility on Demand Systems for Better Passenger Experience." In PRIMA 2015: Principles and Practice of Multi-Agent Systems, 20–35. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25524-8_2.

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7

Kim, Ho-Yeon, Hyeon-Mun Jeong, and Han-Lim Choi. "Consensus-Based Auction Approaches for Autonomous Urban Air Mobility on Demand Systems." In Lecture Notes in Mechanical Engineering, 377–85. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4803-8_37.

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8

Di Maria, Andrea, Andrea Araldo, Giovanni Morana, and Antonella Di Stefano. "AMoDSim: An Efficient and Modular Simulation Framework for Autonomous Mobility on Demand." In Lecture Notes in Computer Science, 165–78. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05081-8_12.

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9

Tussyadiah, Iis P., Florian J. Zach, and Jianxi Wang. "Attitudes Toward Autonomous on Demand Mobility System: The Case of Self-Driving Taxi." In Information and Communication Technologies in Tourism 2017, 755–66. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51168-9_54.

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10

Iglesias, Ramon, Federico Rossi, Rick Zhang, and Marco Pavone. "A BCMP Network Approach to Modeling and Controlling Autonomous Mobility-on-Demand Systems." In Springer Proceedings in Advanced Robotics, 831–47. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43089-4_53.

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Тези доповідей конференцій з теми "Autonomous Mobility on Demand"

1

Ang, Marcelo H. "Achieving mobility on demand using autonomous vehicles." In 2015 6th International Conference on Power Electronics Systems and Applications (PESA) - Advancement in Electric Transportation - Automotive, Vessel & Aircraft. IEEE, 2015. http://dx.doi.org/10.1109/pesa.2015.7398961.

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2

Andersen, Hans, You Hong Eng, Wei Kang Leong, Chen Zhang, Hai Xun Kong, Scott Pendleton, Marcelo H. Ang, and Daniela Rus. "Autonomous personal mobility scooter for multi-class mobility-on-demand service." In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2016. http://dx.doi.org/10.1109/itsc.2016.7795795.

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3

Dandl, Florian, Klaus Bogenberger, and Hani S. Mahmassani. "Autonomous Mobility-on-Demand Real-Time Gaming Framework." In 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). IEEE, 2019. http://dx.doi.org/10.1109/mtits.2019.8883286.

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4

Distler, Verena, Carine Lallemand, and Thierry Bellet. "Acceptability and Acceptance of Autonomous Mobility on Demand." In CHI '18: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3173574.3174186.

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5

Zhang, Rick, Federico Rossi, and Marco Pavone. "Model predictive control of autonomous mobility-on-demand systems." In 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016. http://dx.doi.org/10.1109/icra.2016.7487272.

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6

Tsao, Matthew, Ramon Iglesias, and Marco Pavone. "Stochastic Model Predictive Control for Autonomous Mobility on Demand." In 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2018. http://dx.doi.org/10.1109/itsc.2018.8569459.

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7

Peled, Inon, Kelvin Lee, Yu Jiang, Justin Dauwels, and Francisco C. Pereira. "Preserving Uncertainty in Demand Prediction for Autonomous Mobility Services." In 2019 IEEE Intelligent Transportation Systems Conference - ITSC. IEEE, 2019. http://dx.doi.org/10.1109/itsc.2019.8916878.

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8

Turan, Berkay, Nathaniel Tucker, and Mahnoosh Alizadeh. "Smart Charging Benefits in Autonomous Mobility on Demand Systems." In 2019 IEEE Intelligent Transportation Systems Conference - ITSC. IEEE, 2019. http://dx.doi.org/10.1109/itsc.2019.8917278.

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9

Sun, Yimeng, Yuan Huang, and Zhaohao Ding. "Revenue Uncertainty Analysis for Autonomous Mobility-on-Demand System." In 2022 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). IEEE, 2022. http://dx.doi.org/10.1109/icpsasia55496.2022.9949865.

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10

Pendleton, Scott Drew, Hans Andersen, Xiaotong Shen, You Hong Eng, Chen Zhang, Hai Xun Kong, Wei Kang Leong, Marcelo H. Ang, and Daniela Rus. "Multi-class autonomous vehicles for mobility-on-demand service." In 2016 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2016. http://dx.doi.org/10.1109/sii.2016.7843999.

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Звіти організацій з теми "Autonomous Mobility on Demand"

1

Alexander, Serena, Asha Weinstein Agrawal, and Benjamin Y. Clark. Local Climate Action Planning as a Tool to Harness the Greenhouse Gas Emissions Mitigation and Equity Potential of Autonomous Vehicles and On-Demand Mobility. Mineta Transportation Institute, January 2021. http://dx.doi.org/10.31979/mti.2020.1818.

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This report focuses on how cities can use climate action plans (CAPs) to ensure that on-demand mobility and autonomous vehicles (AVs) help reduce, rather than increase, green-house gas (GHG) emissions and inequitable impacts from the transportation system. We employed a three-pronged research strategy involving: (1) an analysis of the current literature on on-demand mobility and AVs; (2) a systematic content analysis of 23 CAPs and general plans developed by municipalities in California; and (3) a comparison of findings from the literature and content analysis of plans to identify opportunities for GHG emissions reduction and mobility equity. Findings indicate that maximizing the environmental and social benefits of AVs and on-demand mobility requires proactive and progressive planning; yet, most cities are lagging behind in this area. Although municipal CAPs and general plans in California have adopted a few strategies and programs relevant to AVs and on-demand mobility, many untapped opportunities exist to harness the GHG emissions reduction and social benefits potential of AVs and on-demand mobility. Policy and planning discussions should consider the synergies between AVs and on-demand mobility as two emerging mobility trends, as well as the key factors (e.g., vehicle electrification, fuel efficiency, use and ownership, access and distribution, etc.) that determine whether deployment of AVs would help reduce GHG emissions from transportation. Additionally, AVs and on-demand mobility can potentially contribute to a more equitable transportation system by improving independence and quality of life for individuals with disabilities and the elderly, enhancing access to transit, and helping alleviate the geographic gap in public transportation services.
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2

Alexander, Serena, Asha Weinstein Agrawal, and Benjamin Y. Clark. Local Climate Action Planning as a Tool to Harness the Greenhouse Gas Emissions Mitigation and Equity Potential of Autonomous Vehicles and On-Demand Mobility. Mineta Transportation Institute, January 2021. http://dx.doi.org/10.31979/mti.2020.1818.

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This report focuses on how cities can use climate action plans (CAPs) to ensure that on-demand mobility and autonomous vehicles (AVs) help reduce, rather than increase, green-house gas (GHG) emissions and inequitable impacts from the transportation system. We employed a three-pronged research strategy involving: (1) an analysis of the current literature on on-demand mobility and AVs; (2) a systematic content analysis of 23 CAPs and general plans developed by municipalities in California; and (3) a comparison of findings from the literature and content analysis of plans to identify opportunities for GHG emissions reduction and mobility equity. Findings indicate that maximizing the environmental and social benefits of AVs and on-demand mobility requires proactive and progressive planning; yet, most cities are lagging behind in this area. Although municipal CAPs and general plans in California have adopted a few strategies and programs relevant to AVs and on-demand mobility, many untapped opportunities exist to harness the GHG emissions reduction and social benefits potential of AVs and on-demand mobility. Policy and planning discussions should consider the synergies between AVs and on-demand mobility as two emerging mobility trends, as well as the key factors (e.g., vehicle electrification, fuel efficiency, use and ownership, access and distribution, etc.) that determine whether deployment of AVs would help reduce GHG emissions from transportation. Additionally, AVs and on-demand mobility can potentially contribute to a more equitable transportation system by improving independence and quality of life for individuals with disabilities and the elderly, enhancing access to transit, and helping alleviate the geographic gap in public transportation services.
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3

Doo, Johnny. Unsettled Issues Concerning eVTOL for Rapid-response, On-demand Firefighting. SAE International, August 2021. http://dx.doi.org/10.4271/epr2021017.

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Recent advancements of electric vertical take-off and landing (eVTOL) aircraft have generated significant interest within and beyond the traditional aviation industry, and many novel applications have been identified and are in development. One promising application for these innovative systems is in firefighting, with eVTOL aircraft complementing current firefighting capabilities to help save lives and reduce fire-induced damages. With increased global occurrences and scales of wildfires—not to mention the issues firefighters face during urban and rural firefighting operations daily—eVTOL technology could offer timely, on-demand, and potentially cost-effective aerial mobility capabilities to counter these challenges. Early detection and suppression of wildfires could prevent many fires from becoming large-scale disasters. eVTOL aircraft may not have the capacity of larger aerial assets for firefighting, but targeted suppression, potentially in swarm operations, could be valuable. Most importantly, on-demand aerial extraction of firefighters can be a crucial benefit during wildfire control operations. Aerial firefighter dispatch from local fire stations or vertiports can result in more effective operations, and targeted aerial fire suppression and civilian extraction from high-rise buildings could enhance capabilities significantly. There are some challenges that need to be addressed before the identified capabilities and benefits are realized at scale, including the development of firefighting-specific eVTOL vehicles; sense and avoid capabilities in complex, smoke-inhibited environments; autonomous and remote operating capabilities; charging system compatibility and availability; operator and controller training; dynamic airspace management; and vehicle/fleet logistics and support. Acceptance from both the first-responder community and the general public is also critical for the successful implementation of these new capabilities. The purpose of this report is to identify the benefits and challenges of implementation, as well as some of the potential solutions. Based on the rapid development progress of eVTOL aircraft and infrastructures with proactive community engagement, it is envisioned that these challenges can be addressed soon. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.
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4

Yegin, A., D. Moses, and S. Jeon. On-Demand Mobility Management. RFC Editor, October 2019. http://dx.doi.org/10.17487/rfc8653.

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5

Seybold, Patricia. Smart Transportation: Mobility-on-Demand. Boston, MA: Patricia Seybold Group, March 2009. http://dx.doi.org/10.1571/tt03-12-09cc.

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6

Donnelly, Matt, Daniel J. Trudnowski, S. Mattix, and Jeffery E. Dagle. Autonomous Demand Response for Primary Frequency Regulation. Office of Scientific and Technical Information (OSTI), January 2012. http://dx.doi.org/10.2172/1118120.

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7

Olivier, Jason, and Sally Shoop. Imagery classification for autonomous ground vehicle mobility in cold weather environments. Engineer Research and Development Center (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42425.

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Autonomous ground vehicle (AGV) research for military applications is important for developing ways to remove soldiers from harm’s way. Current AGV research tends toward operations in warm climates and this leaves the vehicle at risk of failing in cold climates. To ensure AGVs can fulfill a military vehicle’s role of being able to operate on- or off-road in all conditions, consideration needs to be given to terrain of all types to inform the on-board machine learning algorithms. This research aims to correlate real-time vehicle performance data with snow and ice surfaces derived from multispectral imagery with the goal of aiding in the development of a truly all-terrain AGV. Using the image data that correlated most closely to vehicle performance the images were classified into terrain units of most interest to mobility. The best image classification results were obtained when using Short Wave InfraRed (SWIR) band values and a supervised classification scheme, resulting in over 95% accuracy.
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8

Benabou, Roland, and Efe Ok. Social Mobility and the Demand for Redistribution: The POUM Hypothesis. Cambridge, MA: National Bureau of Economic Research, November 1998. http://dx.doi.org/10.3386/w6795.

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9

Lynott, Jana. Modernizing Demand-Responsive Transportation for the Age of New Mobility. Washington, DC: AARP Public Policy Institute, December 2020. http://dx.doi.org/10.26419/ppi.00121.001.

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10

Hodgdon, Taylor, Anthony Fuentes, Brian Quinn, Bruce Elder, and Sally Shoop. Characterizing snow surface properties using airborne hyperspectral imagery for autonomous winter mobility. Engineer Research and Development Center (U.S.), October 2021. http://dx.doi.org/10.21079/11681/42189.

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With changing conditions in northern climates it is crucial for the United States to have assured mobility in these high-latitude regions. Winter terrain conditions adversely affect vehicle mobility and, as such, they must be accurately characterized to ensure mission success. Previous studies have attempted to remotely characterize snow properties using varied sensors. However, these studies have primarily used satellite-based products that provide coarse spatial and temporal resolution, which is unsuitable for autonomous mobility. Our work employs the use of an Unmanned Aeriel Vehicle (UAV) mounted hyperspectral camera in tandem with machine learning frameworks to predict snow surface properties at finer scales. Several machine learning models were trained using hyperspectral imagery in tandem with in-situ snow measurements. The results indicate that random forest and k-nearest neighbors models had the lowest Mean Absolute Error for all surface snow properties. A pearson correlation matrix showed that density, grain size, and moisture content all had a significant positive correlation to one another. Mechanically, density and grain size had a slightly positive correlation to compressive strength, while moisture had a much weaker negative correlation. This work provides preliminary insight into the efficacy of using hyperspectral imagery for characterizing snow properties for autonomous vehicle mobility.
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