1,795 research outputs found
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
Dynamic fuzzy logic elevator group control system for energy optimization
High-rise buildings with a considerable number of elevators represent a major logistic problem
concerning saving space and time due to economic reasons. For this reason, complex Elevator Group
Control Systems are developed in order to manage the elevators properly. Furthermore, the subject
of energy is acquiring more and more industrial relevance every day as far as sustainable
development is concerned.
In this paper, the first entirely dynamic Fuzzy Logic Elevator Group Control System to dispatch
landing calls so as to minimize energy consumption, especially during interfloor traffic, is proposed.
The fuzzy logic design described here constitutes not only an innovative solution that outperforms
usual dispatchers but also an easy, cheap, feasible and reliable solution, which is possible to be
implemented in real industry controllers
Quantifying the benefits of vehicle pooling with shareability networks
Taxi services are a vital part of urban transportation, and a considerable
contributor to traffic congestion and air pollution causing substantial adverse
effects on human health. Sharing taxi trips is a possible way of reducing the
negative impact of taxi services on cities, but this comes at the expense of
passenger discomfort quantifiable in terms of a longer travel time. Due to
computational challenges, taxi sharing has traditionally been approached on
small scales, such as within airport perimeters, or with dynamical ad-hoc
heuristics. However, a mathematical framework for the systematic understanding
of the tradeoff between collective benefits of sharing and individual passenger
discomfort is lacking. Here we introduce the notion of shareability network
which allows us to model the collective benefits of sharing as a function of
passenger inconvenience, and to efficiently compute optimal sharing strategies
on massive datasets. We apply this framework to a dataset of millions of taxi
trips taken in New York City, showing that with increasing but still relatively
low passenger discomfort, cumulative trip length can be cut by 40% or more.
This benefit comes with reductions in service cost, emissions, and with split
fares, hinting towards a wide passenger acceptance of such a shared service.
Simulation of a realistic online system demonstrates the feasibility of a
shareable taxi service in New York City. Shareability as a function of trip
density saturates fast, suggesting effectiveness of the taxi sharing system
also in cities with much sparser taxi fleets or when willingness to share is
low.Comment: Main text: 6 pages, 3 figures, SI: 24 page
Taxi dispatching strategies with compensations
[EN] Urban mobility efficiency is of utmost importance in big cities. Taxi vehicles are key elements in daily traffic activity. The advance of ICT and geo-positioning systems has given rise to new opportunities for improving the efficiency of taxi fleets in terms of waiting times of passengers, cost and time for drivers, traffic density, CO2 emissions, etc., by using more informed, intelligent dispatching. Still, the explicit spatial and temporal components, as well as the scale and, in particular, the dynamicity of the problem of pairing passengers and taxis in big towns, render traditional approaches for solving standard assignment problem useless for this purpose, and call for intelligent approximation strategies based on domain-specific heuristics. Furthermore, taxi drivers are often autonomous actors and may not agree to participate in assignments that, though globally efficient, may not be sufficently beneficial for them individually. This paper presents a new heuristic algorithm for taxi assignment to customers that considers taxi reassignments if this may lead to globally better solutions. In addition, as such new assignments may reduce the expected revenues of individual drivers, we propose an economic compensation scheme to make individually rational drivers agree to proposed modifications in their assigned clients. We carried out a set of experiments, where several commonly used assignment strategies are compared to three different instantiations of our heuristic algorithm. The results indicate that our proposal has the potential to reduce customer waiting times in fleets of autonomous taxis, while being also beneficial from an economic point of view.This work was supported by the Autonomous Region of Madrid (grant "MOSI-AGIL-CM" (S2013/ICE-3019) co-funded by EU Structural Funds FSE and FEDER), project "SURF" (TIN2015-65515-C4-X-R (MINECO/FEDER)) funded by the Spanish Ministry of Economy and Competitiveness, and through the Excellence Research Group GES2ME (Ref. 30VCPIGI05) co-funded by URJC and Santander Bank.Billhardt, H.; Fernandez Gil, A.; Ossowski, S.; Palanca Cámara, J.; Bajo, J. (2019). Taxi dispatching strategies with compensations. Expert Systems with Applications. 122:173-182. https://doi.org/10.1016/j.eswa.2019.01.001S17318212
Towards a Multimodal Charging Network: Joint Planning of Charging Stations and Battery Swapping Stations for Electrified Ride-Hailing Fleets
This paper considers a multimodal charging network in which charging stations
and battery swapping stations are built in tandem to support the electrified
ride-hailing fleet in a synergistic manner. Our central thesis is predicated on
the observation that charging stations are cost-effective, making them ideal
for scaling up electric vehicles in ride-hailing fleets in the beginning, while
battery swapping stations offer quick turnaround and can be deployed in tandem
with charging stations to improve fleet utilization and reduce operational
costs for the ride-hailing platform. To fulfill this vision, we consider a
ride-hailing platform that expands the multimodal charging network with a
multi-stage investment budget and operates a ride-hailing fleet to maximize its
profit. A multi-stage network expansion model is proposed to characterize the
coupled planning and operational decisions, which captures demand elasticity,
passenger waiting time, charging and swapping waiting times, as well as their
dependence on fleet status and charging infrastructure. The overall problem is
formulated as a nonconvex program. Instead of pursuing the globally optimal
solution, we establish a theoretical upper bound through relaxation,
reformulation, and decomposition so that the global optimality of the derived
solution to the nonconvex problem is verifiable. In the case study for
Manhattan, we find that the two facilities complement each other and play
different roles during the expansion of charging infrastructure: at the early
stage, the platform always prioritizes building charging stations to electrify
the fleet, after which it initiates the deployment of swapping stations to
enhance fleet utilization. Compared to the charging-only case, ..
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Grid flexibility by electrifying energy systems for sustainable aviation
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDecarbonisation of aviation goals set by Flightpath 2050 Europe’s Vision for Aviation
requires that the airports become emission-free by 2050. This thesis original contribution to
knowledge is to explore the incorporation of aviation electrification technologies, including
electric aircraft (EA), electrified ground support equipment (GSE), and airport parking electric
vehicles (EVs), into power systems, evaluating their influence on grid infrastructure and
operations, as well as their potential to support the grid operation.
A comprehensive review of aviation electrification technologies revealed a research gap in the
integration of these technologies into the power systems. The thesis contributes to electricity
network infrastructure planning for electrification of aviation and airport-based distributed
energy resources (DER) that provide ancillary services to the power grid.
A multi-objective airport microgrid planning framework is developed, comparing EA charging
strategies and revealing that battery swap performs better. Vehicle-to-grid (V2G) strategy with
parking EVs improves the microgrid's performance. A techno-economic assessment of wireless charging
systems for electric airport shuttle buses shows better economic performance than conventional
buses and other charging options.
A novel Aviation-to-Grid (A2G) flexibility concept provides frequency response services to the GB
power system using EA battery charging systems, with typical A2G service capacity showing
significant variation across eight UK airports. A deep reinforcement learning (DRL)-based A2G
dispatch approach evaluates the impact of EA charger capacity on energy dispatch results, with
higher capacities leading to higher revenue and lower operation costs.
To summarise, this thesis addresses the research gaps in integrating aviation
electrification technologies into power systems, offering valuable insights for airport operators
aiming to decarbonise air transport activities through the adoption of these technologies. The
study also provides an understanding of the impacts on grid operators in terms of infrastructure
planning and operations. This comprehensive approach ensures a cohesive understanding of the
challenges and opportunities presented by aviation
electrification and its integration into power systems
Kabul city transportation system analysis and the short-term and long-term transportation planning & policy
Thesis(Master) --KDI School:Master of Development Policy,2020The world has witnessed a great increase in motorization, urbanization, population growth and changes in population density over the past few decades. These changes have resulted in heavily congested roads. Congestion reduces efficiency of transportation systems and increases travel time, air pollution and fuel consumption. Kabul, the capital and business center of Afghanistan, is the most populated and congested city in Afghanistan. The increase in population and population density of the city has resulted in increased motorization, hence traffic congestions and air pollution. In this paper the main causes for congestions in Kabul City are studied and the solutions for congestion problems in Kabul City are suggested through case studies of Brazil and India.
From the regression of delay time as dependent and the number of vehicles as independent variable, it has been found that delay time has a positive relationship with number of vehicles (increase in the number of vehicles results in increase in congestion), which suggests that effort should be made to reduce the number of vehicles (specifically private cars) in the city.
From this study it has been found that one of the vital problems related to transportation in Kabul City is the absence of an independent organizing body to manage overall transportation network in Kabul city. As a solution for this problem a new organizing body is suggested that will be in charge of arranging, directing and overseeing the public transport system and will in future steps facilitate the integration of the public transportation system beside central dispatching, a common ticketing and other offices.Chapter 1 Afghanistan
Chapter 2 literature Review
Chapter 3 Analysis of Current Situation of Kabul City
Chapter 4 What is the main reason of congestion in Kabul CitymasterpublishedMohammad Wali AHADI
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