Preliminary Results of a Multiagent Traffic Simulation for Berlin

This paper provides an introduction to multi-agent traffic simulation. Metropolitan regions can consist of several million inhabitants, implying the simulation of several million travelers, which represents a considerable computational challenge. We reports on our recent case study of a real-world Berlin scenario. The paper explains computational techniques necessary to achieve results. It turns out that the difficulties there, because of data availability and because of the special situation of Berlin after the re-unification, are considerably larger than in previous scenarios that we have treated

(Dis)contentment with the International System: The Relationship between Territorial Dispute Settlement Attempts and UNGA Voting

To what degree do the methods of management for territorial and maritime disputes relate to voting patterns in the United Nations General Assembly? In particular, do actions taken by the disputants in managing their disputes exert influence on their fellow disputant’s foreign policy preferences in the United Nations General Assembly (UNGA) reflective of the nature of these attempts? As territory has been found to be one of the most important driving factors in the conflict between states, understanding the impacts of different settlement methods in the active conveyance of information to other state actors in attempts to settle can provide insight into the general contentment of states with their place in the international system. This potential impact in understanding the degree settlement attempts are reflected in UNGA voting is important, not only to the disputants but also to the wellbeing of the international system as a whole. In this dissertation, I seek to assess the relationship between settlement attempts on territorial and maritime disputes with resulting voting patterns in the UNGA. To do this, I conduct a large-N quantitative analysis to assess general supports for my theory’s hypotheses, followed by the examination of five case studies involving China to determine additional support. I conclude with an overall discussion of my findings and conclude with the next steps in research

Structural Characterization of the Loop at the Alpha-Subunit C-Terminus of the Mixed Lineage Leukemia Protein Activating Protease Taspase1.

Acknowledgments We acknowledge the Fonds of Chemical Industry for funding JvdB by their Chemiefonds grant and the DFG for funding PB and CB (CRC 1093). Additional gratitude goes to Shirley Knauer for providing Taspase1 expression clones. Funding: The authors acknowledge the Fonds of Chemical Industry for funding JvdB by their Chemiefonds grant and the DFG for funding PB and CB (CRC 1093).Peer reviewedPublisher PD

Decision Strategies for Incremental POS Tagging

Proceedings of the 18th Nordic Conference of Computational Linguistics NODALIDA 2011. Editors: Bolette Sandford Pedersen, Gunta Nešpore and Inguna Skadiņa. NEALT Proceedings Series, Vol. 11 (2011), 26-33. © 2011 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/16955

Agent-Oriented Coupling of Activity-Based Demand Generation with Multiagent Traffic Simulation

The typical method to couple activity-based demand generation (ABDG) and dynamic traffic assignment (DTA) is time-dependent origin-destination (O-D) matrices. With that coupling method, the individual traveler's information gets lost. Delays at one trip do not affect later trips. However, it is possible to retain the full agent information from the ABDG by writing out all agents' plans, instead of the O-D matrix. A plan is a sequence of activities, connected by trips. Because that information typically is already available inside the ABDG, this is fairly easy to achieve. Multiagent simulation (MATSim) takes such plans as input. It iterates between the traffic flow simulation (sometimes called network loading) and the behavioral modules. The currently implemented behavioral modules are route finding and time adjustment. Activity resequencing or activity dropping are conceptually clear but not yet implemented. Such a system will react to a time-dependent toll by possibly rearranging the complete day; in consequence, it goes far beyond DTA (which just does route adaptation). This paper reports on the status of the current Berlin implementation. The initial plans are taken from an ABDG, originally developed by Kutter; to the authors' knowledge, this is the first time traveler-based information (and not just O-D matrices) is taken from an ABDG and used in a MATSim. The simulation results are compared with real-world traffic counts from about 100 measurement stations

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

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

The Mauritanian Slope (NE Atlantic) Has No Desert: <em>Swiftia phaeton</em> (Holaxonia: Plexauridae) Shaping Coral Gardens

Swiftia Duchassaing & Michelotti, 1864, is often found sparse in the NE Atlantic Ocean and Mediterranean Sea. When the cruise MSM 16/3 “PHAETON” filmed the upper bathyal off Mauritania in 2010, the first dense populations dominated by Swiftia were discovered in the NE Atlantic Ocean, co-occurring with the framework-forming scleractinians Desmophyllum pertusum (Linnaeus, 1758) and Madrepora oculata Linnaeus, 1758. Remotely operated vehicle (ROV) video annotation from two canyons and two coral mounds considered Swiftia phaeton Sampaio, Beuck & Freiwald, 2022 presence, size class and abundance as well as substrate and geomorphology of the seafloor. Coral gardens definition included abundance and size of the species. Dense and very dense mono- and multispecific coral gardens dominated by S. phaeton were mapped between 20°24′N and 17°54′N in 470–640 m depth. The resilience of these coral gardens off Mauritania is mainly linked to the presence of hard substrate available to settle and to the exposition of currents rich in food. Still, these ecosystems are located inside a hydrocarbon exploration area off Mauritania and where fisheries occur since the 1960s. Sedimentation plumes caused by both activities can travel and impact on settlement, development, and survival of these populations. Hence, these vulnerable “oases” should be protected