A Modular, Adaptive, and Autonomous Transit System (MAATS): A In-motion Transfer Strategy and Performance Evaluation in Urban Grid Transit Networks

Dynamic traffic demand has been a longstanding challenge for the conventional transit system design and operation. The recent development of autonomous vehicles (AVs) makes it increasingly realistic to develop the next generation of transportation systems with the potential to improve operational performance and flexibility. In this study, we propose an innovative transit system with autonomous modular buses (AMBs) that is adaptive to dynamic traffic demands and not restricted to fixed routes and timetables. A unique transfer operation, termed as “in-motion transfer”, is introduced in this paper to transfer passengers between coupled modular buses in motion. A two-stage model is developed to facilitate in-motion transfer operations in optimally designing passenger transfer plans and AMB trajectories at intersections. In the proposed AMB system, all passengers can travel in the shortest path smoothly without having to actually alight and transfer between different bus lines. Numerical experiments demonstrate that the proposed transit system results in shorter travel time and a significantly reduced average number of transfers. While enjoying the above-mentioned benefits, the modular, adaptive, and autonomous transit system (MAATS) does not impose substantially higher energy consumption in comparison to the conventional bus syste

Key performance and value indicators for enhancing sustainable and intelligent Mobility as a Service solutions

openLa Mobility as a Service (MaaS) rappresenta l'integrazione di diversi servizi di trasporto in un quadro unificato mirato a rivoluzionare la mobilità urbana offrendo soluzioni di viaggio integrate, centrate sull'utente e sostenibili. Questa tesi si concentra sull'esaminare e analizzare gli indicatori chiave di performance (KPI) e gli indicatori chiave di valore (KVI) cruciali per lo sviluppo e l'ottimizzazione di sistemi MaaS sostenibili e intelligenti. Attraverso la valutazione di metriche come l'efficienza del servizio, la soddisfazione dell'utente, l'impatto ambientale, la riduzione della congestione, la minimizzazione dei tempi di arrivo e la convenienza economica, questa ricerca mira a identificare gli indicatori che rafforzano l'implementazione e il funzionamento efficace delle piattaforme MaaS. Attraverso un'analisi approfondita di questi indicatori, questo studio propone funzioni obiettivo che prioritizzano il raggiungimento di un ecosistema MaaS equo e ottimizzato.Mobility as a Service (MaaS) represents the integration of different transportation services into a unified framework aimed at revolutionizing urban mobility by offering integrated, user-centered, and sustainable travel solutions. This thesis focuses on examining and analyzing key performance indicators (KPIs) and key value indicators (KVIs) crucial for developing and optimizing sustainable and intelligent MaaS systems. By assessing metrics such as service efficiency, user satisfaction, environmental impact, congestion reduction, minimization of arrival times, and cost-effectiveness, this research aims to identify the indicators that reinforce the successful and effective implementation and operation of MaaS platforms. Through an in-depth examination of these indicators, this study proposes objective functions that prioritize achieving an equitable and optimized MaaS ecosystem

Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events

This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event

Aerospace Applications of Microprocessors

An assessment of the state of microprocessor applications is presented. Current and future requirements and associated technological advances which allow effective exploitation in aerospace applications are discussed

Simulation verification techniques study: Simulation performance validation techniques document

Techniques and support software for the efficient performance of simulation validation are discussed. Overall validation software structure, the performance of validation at various levels of simulation integration, guidelines for check case formulation, methods for real time acquisition and formatting of data from an all up operational simulator, and methods and criteria for comparison and evaluation of simulation data are included. Vehicle subsystems modules, module integration, special test requirements, and reference data formats are also described

Vehicle Dispatching and Routing of On-Demand Intercity Ride-Pooling Services: A Multi-Agent Hierarchical Reinforcement Learning Approach

The integrated development of city clusters has given rise to an increasing demand for intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading traditional intercity bus services by implementing demand-responsive enhancements. Nevertheless, its online operations suffer the inherent complexities due to the coupling of vehicle resource allocation among cities and pooled-ride vehicle routing. To tackle these challenges, this study proposes a two-level framework designed to facilitate online fleet management. Specifically, a novel multi-agent feudal reinforcement learning model is proposed at the upper level of the framework to cooperatively assign idle vehicles to different intercity lines, while the lower level updates the routes of vehicles using an adaptive large neighborhood search heuristic. Numerical studies based on the realistic dataset of Xiamen and its surrounding cities in China show that the proposed framework effectively mitigates the supply and demand imbalances, and achieves significant improvement in both the average daily system profit and order fulfillment ratio

TOOLS TO SUPPORT TRANSPORTATION EMISSIONS REDUCTION EFFORTS: A MULTIFACETED APPROACH

The transportation sector is a significant contributor to current global climatic problems, one of the most prominent problems that today's society faces. In this dissertation, three complementary problems are addressed to support emissions reduction efforts by providing tools to help reduce demand for fossil fuels. The first problem addresses alternative fuel vehicle (AFV) fleet operations considering limited infrastructure availability and vehicle characteristics that contribute to emission reduction efforts by: supporting alternative fuel use and reducing carbon-intensive freight activity. A Green Vehicle Routing Problem (G-VRP) is formulated and techniques are proposed for its solution. These techniques will aid organizations with AFV fleets in overcoming difficulties that exist as a result of limited refueling infrastructure and will allow companies considering conversion to a fleet of AFVs to understand the potential impact of their decision on daily operations and costs. The second problem is aimed at supporting SOV commute trip reduction efforts through alternative transportation options. This problem contributes to emission reduction efforts by supporting reduction of carbon-intensive travel activity. Following a descriptive analysis of commuter survey data obtained from the University of Maryland, College Park campus, ordered-response models were developed to investigate the market for vanpooling. The model results show that demand for vanpooling in the role of passenger and driver have differences and the factors affecting these demands are not necessarily the same. Factors considered include: status, willingness-to-pay, distance, residential location, commuting habits, demographics and service characteristics. The third problem focuses on providing essential input data, origin-destination (OD) demand, for analysis of various strategies, to address emission reduction by helping to improve system efficiency and reducing carbon-intensive travel activity. A two-stage subarea OD demand estimation procedure is proposed to construct and update important time-dependent OD demand input for subarea analysis in an effort to overcome the computational limits of Dynamic Traffic Assignment (DTA) methodologies. The proposed method in conjunction with path-based simulation-assignment systems can provide an evolving platform for integrating operational considerations in planning models for effective decision support for agencies that are considering strategies for transportation emissions reduction