Agent-based modelling of air transport demand

Constraints such as opening hours or passenger capacities influence travel options that can be offered by an airport and by the connecting airlines. If infrastructure, policy or technological measures modify transport options, then the benefits do not only depend on the technology, but also on possibly heterogeneous user preferences such as desired arrival times or on the availability of alternative travel modes. This paper proposes an agent-based, iterative assignment procedure to model European air traffic and German passenger demand on a microscopic level, capturing individual passenger preferences. Air transport technology is simulated microscopically, i.e. each aircraft is represented as single unit with attached attributes such as departure time, flight duration or seat availability. Trip-chaining and delay propagation can be added. Microsimulation is used to verify and assess passengers’ choices of travel alternatives, where those choices improve over iterations until an agent-based stochastic user equilibrium is reached. This requires fast simulation models, thus, similar to other approaches in air traffic modelling a queue model is used. In contrast to those approaches, the queue model in this work is solved algorithmically. Overall, the approach is suited to analyze, forecast and evaluate the consequences of mid-distance transport measures

European Air- and Rail-Transport

This chapter discusses simulation of air- and rail-transport technology and passengers using MATSim. There is no great difference in overall travel times between middle-range rail and air transportation. Airports and railway stations are affected by capacity and opening time constraints. For passengers and goods, geospatial location is an important property. Both modes, but especially air transport, are faced with difficult capacity restrictions at certain departure times. This chapter discusses how MATSim can be applied to capture these constraints and how interaction between passenger demand and constraints on technology supply can be modeled

Extensible Software Design of a Multi-Agent Transport Simulation

This paper explains the chosen methodology for software design of the Multi-Agent Transport Simulation, MATSim. The design focusses on standard architectures and design patterns to ease usability and improve extensibility of the software, Potential for extension is discussed using an example implementation of a traffic signal control module. Both, MATSim and the extension are using the same concepts for software architecture

Emergent effects in multi-agent simulations of road pricing

Road pricing is debated as an option of transportation policy. Especially in metropolitan areas congestion pricing is promising to reduce congestion and to protect the environment. In order to reach the promised results the choice and design of a policy is very important, especially in a ”second-best” context. Therefore it is worth to attempt detailed predictions of the effects and implications of the planned pricing scheme. Most if not all state-of-thepractice methodologies forecasting those effects are • aggregate and in consequence do not consider social and economic characteristics of individual travelers. • static in time and in consequence do not consider temporal effects such as toll avoidance In order to bridge this gap, multi-agent microsimulations can be used. Our large-scale multi-agent traffic simulation is capable to simulate a complete day-plan of up to seven million individuals (agents). In contrast to other approaches, our simulation truly traces the synthetic travelers through their day, thus enabling us (at least in principle) to model emergent effects such as complex re-scheduling across the whole day. This paper describes the implementation of a toll-scheme for the bigger Zurich area and presents the results of the simulation. We point out how agents (population) react to changed prices of transportation by modifying their consumption patterns. The analysis of the policy is based on the performance of simulated day-plans of the agents. This performance is directly given by a utility function, which is used to measure gains and losses of different groups of inhabitants in the research area. Based on these measurements we provide an economic interpretation of the policy and highlight emergent phenomena like changes in route choice and time reactions

Agent-based Modelling and Simulation of Air Transport Technology

Declining travel time differences of mid-distance transport modes motivate use of multi-agent simulation models to analyze and forecast behaviour of actors in the transport system. This paper focuses on air-transport technology. A simulation model is proposed, that represents details of air traffic microscopically but is fast enough to enable an iterative simulation-based passenger-trip assignment. Aircraft are modelled in detail in respect to departure time and seat availability. Modelling of airports and routes of aircraft focuses on the available capacity of runways. Several simulation runs illustrate how the model can be calibrated using available parameters. The model can be used for an agent-based traffic assignment. Overall, the approach appears to be suited to analyze and forecast mid-distance transport

The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations

Multi-agent simulation has increasingly been used for transportation simulation in recent years. With current techniques, it is possible to simulate systems consisting of several million agents. Such multi-agent simulations have been applied to whole cities and even large regions. In this paper it is demonstrated how to adapt an existing multi-agent transportation simulation framework to large-scale pedestrian evacuation simulation. The underlying flow model simulates the traffic-based on a simple queue model where only free speed, bottleneck capacities, and space constraints are taken into account. The queue simulation, albeit simple, captures the most important aspects of evacuations such as the congestion effects of bottlenecks and the time needed to evacuate the endangered area. In the case of an evacuation simulation the network has time-dependent attributes. For instance, large-scale inundations or conflagrations do not cover all the endangered area at once. These time-dependent attributes are modeled as network change events. Network change events are modifying link parameters at predefined points in time. The simulation framework is demonstrated through a case study for the Indonesian city of Padang, which faces a high risk of being inundated by a tsunami.BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIENBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacitie

Simulation of Urban Traffic Control: A Queue Model Approach

This paper aims at an agent-based simulation of the interplay between two types of agents within a transport system: travelers, and traffic signals. For the simulation of this interplay, a computationally efficient traffic model is needed. It is thus shown how queue models can be used to model traffic flow and spill-back at signalized intersections.BMBF, 03MOPAI1, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Optimale Routenführung in Large Scale MikrosimulationenBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in MegacitiesBMBF, 03SKPAI6, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrssteuerung bei Großereignissen und Evakuierun

Multi-agent transport simulations and economic evaluation

Tolls are frequently discussed policies to reduce traffic in cities. However, road pricing measures are seldom implemented due to high investments and unpopularity. Transportation planning tools can support planning authorities by solving those problems if they take into account the following aspects: – Demographic attributes like income and time constraints – Time reactions to the policy – Schedule changes of population’s individuals during the whole day Our approach uses multi-agent simulations to model and simulate full daily plans. Each of our agents has a utility function that appraises the performance of a typical, microscopically simulated day. The sum of all utility changes to a policy change can be interpreted as the change in the system’s welfare thus the economic evaluation of a measure straightforward. The approach is tested with travel behavior of the Zurich metropolitan region in Switzerland. Several tolling schemes are investigated. It is shown that the simulation can be used to model travelers’ reactions to time-dependent tolls in a way most existing transportation planning tools are not able to do. It is demonstrated that route adjustment only, as is done in many traditional transport planning packages, results in no economic gains from the tolls. As time-dependent tolls are a much-debated subject in transportation politics, the ability to fully model such tolls and the reactions of travelers may help to find better toll schemes. In a world where individuals have more and more freedom to schedule their daily plans, agent-based simulations offer an intuitive way to research complex topics with lots of interdependencies

A potent and selective inhibitor for the modulation of MAGL activity in the neurovasculature.

Chronic inflammation and blood-brain barrier dysfunction are key pathological hallmarks of neurological disorders such as multiple sclerosis, Alzheimer's disease and Parkinson's disease. Major drivers of these pathologies include pro-inflammatory stimuli such as prostaglandins, which are produced in the central nervous system by the oxidation of arachidonic acid in a reaction catalyzed by the cyclooxygenases COX1 and COX2. Monoacylglycerol lipase hydrolyzes the endocannabinoid signaling lipid 2-arachidonyl glycerol, enhancing local pools of arachidonic acid in the brain and leading to cyclooxygenase-mediated prostaglandin production and neuroinflammation. Monoacylglycerol lipase inhibitors were recently shown to act as effective anti-inflammatory modulators, increasing 2-arachidonyl glycerol levels while reducing levels of arachidonic acid and prostaglandins, including PGE2 and PGD2. In this study, we characterized a novel, highly selective, potent and reversible monoacylglycerol lipase inhibitor (MAGLi 432) in a mouse model of lipopolysaccharide-induced blood-brain barrier permeability and in both human and mouse cells of the neurovascular unit: brain microvascular endothelial cells, pericytes and astrocytes. We confirmed the expression of monoacylglycerol lipase in specific neurovascular unit cells in vitro, with pericytes showing the highest expression level and activity. However, MAGLi 432 did not ameliorate lipopolysaccharide-induced blood-brain barrier permeability in vivo or reduce the production of pro-inflammatory cytokines in the brain. Our data confirm monoacylglycerol lipase expression in mouse and human cells of the neurovascular unit and provide the basis for further cell-specific analysis of MAGLi 432 in the context of blood-brain barrier dysfunction caused by inflammatory insults

OGLE-2013-BLG-0911Lb: A Secondary on the Brown-dwarf Planet Boundary around an M Dwarf

We present the analysis of the binary-lens microlensing event OGLE-2013-BLG-0911. The best-fit solutions indicate the binary mass ratio of q $\simeq$ 0.03, which differs from that reported in Shvartzvald et al. The event suffers from the well-known close/wide degeneracy, resulting in two groups of solutions for the projected separation normalized by the Einstein radius of s ∼ 0.15 or s ∼ 7. The finite source and the parallax observations allow us to measure the lens physical parameters. The lens system is an M dwarf orbited by a massive Jupiter companion at very close (${M}_{\mathrm{host}}={0.30}_{-0.06}^{+0.08}{M}_{\odot }$, ${M}_{\mathrm{comp}}={10.1}_{-2.2}^{+2.9}{M}_{\mathrm{Jup}}$, ${a}_{\exp }={0.40}_{-0.04}^{+0.05}\,\mathrm{au}$) or wide (${M}_{\mathrm{host}}={0.28}_{-0.08}^{+0.10}{M}_{\odot }$, ${M}_{\mathrm{comp}}={9.9}_{-3.5}^{+3.8}{M}_{\mathrm{Jup}}$, ${a}_{\exp }={18.0}_{-3.2}^{+3.2}\,\mathrm{au}$) separation. Although the mass ratio is slightly above the planet-brown dwarf (BD) mass-ratio boundary of q = 0.03, which is generally used, the median physical mass of the companion is slightly below the planet-BD mass boundary of 13M$_{Jup}$. It is likely that the formation mechanisms for BDs and planets are different and the objects near the boundaries could have been formed by either mechanism. It is important to probe the distribution of such companions with masses of ∼13M$_{Jup}$ in order to statistically constrain the formation theories for both BDs and massive planets. In particular, the microlensing method is able to probe the distribution around low-mass M dwarfs and even BDs, which is challenging for other exoplanet detection methods