A framework for agent based simulation of demand responsive transport systems

Demand responsive transport (DRT), such as shared mini busses, have become a viable form of public transport mainly in rural areas in recent years. In contrast to ordinary schedule-based services, DRT systems come in many different shapes and forms and are usually customised to the environment they operate in. E.g., they might be restricted to certain user groups or only operate in specific areas or with a specific fixed terminus. With advances in information and communications technology (ICT) and the possibility of driverless operations in the future, DRT systems may become an attractive additional mode also in urban and inter-urban transport. This brings the necessity to assess and evaluate DRT services and possible business models, with transport simulations being one possible way. This study introduces a framework for an extensible, open source shared minibus service simulation. Based on the agent based transport simulation MATSim and its existing DVRP extension, the extension provides DRT services as an additional mode to the synthetic population of a MATSim scenario. The module allows assigning vehicles to groups according to different dispatch algorithms shaped to the actual use case. In a first case study, a DRT system complements ordinary public transport and car infrastructure on the heavily used commuter relation between Braunschweig and Wolfsburg. During peak times, average travel times per traveler over all modes between the two cities can be reduced by 5 minutes using a fleet of 50 8-seat-vehicles. In a second case study, a DRT system is used to shuttle passengers in an area with non-optimal public transport access to the train station in Braunschweig. With given capacity constraints, the optimizer has to decide which customers to serve in order to achieve an on-time arrival for passenger

Adaptive State Space Partitioning for Dynamic Decision Processes

With the rise of newbusiness processes that require real-time decision making, anticipatory decision making becomes necessary to use the available resources wisely. Dynamic real-time problems occur in many business fields, for example in vehicle routing applications with stochastic customer service requests expecting a fast response. For anticipatory decision making, offline simulation-based optimization methods like value function approximation are promising solution approaches. However, these methods require a suitable approximation architecture to store the value information for the problem states. In this paper, an approach is proposed that finds and adapts this architecture iteratively during the approximation process. A computational proof of concept is presented for a dynamic vehicle routing problem. In comparison to conventional architectures, the proposed method is able to improve the solution quality and reduces the required architecture size significantly

Resource Allocation for a Wireless Coexistence Management System Based on Reinforcement Learning

In industrial environments, an increasing amount of wireless devices are used, which utilize license-free bands. As a consequence of these mutual interferences of wireless systems might decrease the state of coexistence. Therefore, a central coexistence management system is needed, which allocates conflict-free resources to wireless systems. To ensure a conflict-free resource utilization, it is useful to predict the prospective medium utilization before resources are allocated. This paper presents a self-learning concept, which is based on reinforcement learning. A simulative evaluation of reinforcement learning agents based on neural networks, called deep Q-networks and double deep Q-networks, was realized for exemplary and practically relevant coexistence scenarios. The evaluation of the double deep Q-network showed that a prediction accuracy of at least 98 % can be reached in all investigated scenarios.Comment: Submitted to the 23rd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2018

Cetaceans sightings during research cruises in three remote Atlantic British Overseas Territories

Marine mammal sightings were recorded during research cruises to three remote, mid-ocean British Overseas Territories in the South Atlantic and Southern Ocean. In March to April 2018 and 2019, the Exclusive Economic Zones (EEZs) of tropical St Helena and temperate Tristan da Cunha were surveyed. The sub-polar waters of South Georgia and the South Sandwich Islands (SGSSI) were surveyed in February to March 2019. At St Helena in 2018, five species were recorded during 11 sightings, and in 2019, four species, with one additional unidentified species, during seven sightings. Most of these sightings were of dolphin species, which are known to be resident around the Island and seamounts. In Tristan da Cunha in 2018, a total of five identified and one unidentified species were recorded during six sightings, half of which were associated with the Islands or seamounts. In 2019, due to rough weather, no sightings were recorded in the Tristan waters. Around SGSSI, 162 sightings of 236 cetaceans were made in 2019, mostly of baleen whales, with seven species identified with certainty. Sightings around the southern South Sandwich Islands' included beaked whales and large dolphins, whereas baleen whales dominated in the northern South Sandwich Islands. These results provide new data for rarely surveyed regions, helping to build a spatial picture of important areas for marine mammals, which will help inform marine spatial protection strategies

Fish communities associated with cold-water corals vary with depth and substratum type

AbstractUnderstanding the processes that drive the distribution patterns of organisms and the scales over which these processes operate are vital when considering the effective management of species with high commercial or conservation value. In the deep sea, the importance of scleractinian cold-water corals (CWCs) to fish has been the focus of several studies but their role remains unclear. We propose this may be due to the confounding effects of multiple drivers operating over multiple spatial scales. The aims of this study were to investigate the role of CWCs in shaping fish community structure and individual species-habitat associations across four spatial scales in the NE Atlantic ranging from “regions” (separated by >500km) to “substratum types” (contiguous). Demersal fish and substratum types were quantified from three regions: Logachev Mounds, Rockall Bank and Hebrides Terrace Seamount (HTS). PERMANOVA analyses showed significant differences in community composition between all regions which were most likely caused by differences in depths. Within regions, significant variation in community composition was recorded at scales of c. 20–3500m. CWCs supported significantly different fish communities to non-CWC substrata at Rockall Bank, Logachev and the HTS. Single-species analyses using generalised linear mixed models showed that Sebastes sp. was strongly associated with CWCs at Rockall Bank and that Neocyttus helgae was more likely to occur in CWCs at the HTS. Depth had a significant effect on several other fish species. The results of this study suggest that the importance of CWCs to fish is species-specific and depends on the broader spatial context in which the substratum is found. The precautionary approach would be to assume that CWCs are important for associated fish, but must acknowledge that CWCs in different depths will not provide redundancy or replication within spatially-managed conservation networks

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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