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- Alirezaie, Marjan, 1980-, et al.
(author)
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An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring
- 2017
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In: Sensors. - : M D P I AG. - 1424-8220. ; 17:11
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Journal article (peer-reviewed)abstract
- This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.
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2. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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Exploiting Context and Semantics for UAV Path-finding in an Urban Setting
- 2017
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In: Proceedings of the 1st International Workshop on Application of Semantic Web technologies in Robotics (AnSWeR 2017), Portoroz, Slovenia, May 29th, 2017. - : Technical University Aachen. ; , s. 11-20
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Conference paper (peer-reviewed)abstract
- In this paper we propose an ontology pattern that represents paths in a geo-representation model to be used in an aerial path planning processes. This pattern provides semantics related to constraints (i.e., ight forbidden zones) in a path planning problem in order to generate collision free paths. Our proposed approach has been applied on an ontology containing geo-regions extracted from satellite imagery data from a large urban city as an illustrative example.
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3. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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Knowing without telling : integrating sensing and mapping for creating an artificial companion
- 2016
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In: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450345897 ; , s. 11:1-11:4
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Conference paper (peer-reviewed)abstract
- This paper depicts a sensor-based map navigation approach which targets users, who due to disabilities or lack of technical knowledge are currently not in the focus of map system developments for personalized information. What differentiates our approach from the state-of-art mostly integrating localized social media data, is that our vision is to integrate real time sensor generated data that indicates the situation of dfferent phenomena (such as the physiological functions of the body) related to the user. The challenge hereby is mainly related to knowledge representation and integration. The tentative impact of our vision for future navigation systems is re ected within a scenario.
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6. |
- Bazzan, Ana L. C., et al.
(author)
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A review on agent-based technology for traffic and transportation
- 2014
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In: Knowledge engineering review (Print). - New York : Cambridge University Press. - 0269-8889 .- 1469-8005. ; 29:3, s. 375-403
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Research review (peer-reviewed)abstract
- In the last few years, the number of papers devoted to applications of agent-based technologies to traffic and transportation engineering has grown enormously. Thus, it seems to be the appropriate time to shed light over the achievements of the last decade, on the questions that have been successfully addressed, as well as on remaining challenging issues. In the present paper, we review the literature related to the areas of agent-based traffic modelling and simulation, and agent-based traffic control and management. Later we discuss and summarize the main achievements and the challenges.
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7. |
- Bazzan, Ana L. C., et al.
(author)
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Experience Sharing in a Traffic Scenario
- 2020
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In: ATT2020 Agents in Traffic and Transportation. - : Technical University of Aachen. ; , s. 71-78
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Conference paper (peer-reviewed)abstract
- Travel apps become more and more popular giving in-formation about the current traffic state to drivers who then adapt their route choice. In commuting scenarios, where people repeatedly travel between a particular origin and destination, learning effects add to this information. In this paper, we analyse the effects on the overall network, if adaptive driver agents share their aggregated experience about route choice in a reinforcement learning (Q-learning) setup. Drivers share what they have learnt about the system, not just information about their current travel times. We can show in a standard scenario that experience sharing can improve convergence times for adaptive driver agents
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8. |
- Bazzan, Ana L. C., et al.
(author)
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Re-routing agents in an abstract traffic scenario
- 2008
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In: Advances in artificial intelligence. - Berlin : Springer. - 9783540881896 ; , s. 63-72
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Conference paper (peer-reviewed)abstract
- Human drivers may perform replanning when facing traffic jams or when informed that there are expected delays on their planned routes. In this paper, we address the effects of drivers re-routing, an issue that has been ignored so far. We tackle re-routing scenarios, also considering traffic lights that are adaptive, in order to test whether such a form of co-adaptation may result in interferences or positive cumulative effects. An abstract route choice scenario is used which resembles many features of real world networks. Results of our experiments show that re-routing indeed pays off from a global perspective as the overall load of the network is balanced. Besides, re-routing is useful to compensate an eventual lack of adaptivity regarding traffic management.
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9. |
- Bazzan, Ana L. C., et al.
(author)
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To adapt or not to adapt : consequences of adapting driver and traffic light agents
- 2008
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In: Adaptive agents and multi-agent systems III. - New York : Springer. - 9783540779476 ; , s. 1-14
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Conference paper (peer-reviewed)abstract
- One way to cope with the increasing traffic demand is to integrate standard solutions with more intelligent control measures. However, the result of possible interferences between intelligent control or information provision tools and other components of the overall traffic system is not easily predictable. This paper discusses the effects of integrating co-adaptive decision-making regarding route choices (by drivers) and control measures (by traffic lights). The motivation behind this is that optimization of traffic light control is starting to be integrated with navigation support for drivers. We use microscopic, agent-based modelling and simulation, in opposition to the classical network analysis, as this work focuses on the effect of local adaptation. In a scenario that exhibits features comparable to real-world networks, we evaluate different types of adaptation by drivers and by traffic lights, based on local perceptions. In order to compare the performance, we have also used a global level optimization method based on genetic algorithms.
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10. |
- Bazzan, Ana Lucia, et al.
(author)
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Introduction to Intelligent Systems in Traffic and Transportation
- 2013
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Book (peer-reviewed)abstract
- Urban mobility is not only one of the pillars of modern economic systems, but also a key issue in the quest for equality of opportunity, once it can improve access to other services. Currently, however, there are a number of negative issues related to traffic, especially in mega-cities, such as economical issues (cost of opportunity caused by delays), environmental (externalities related to emissions of pollutants), and social (traffic accidents). Solutions to these issues are more and more closely tied to information and communication technology. Indeed, a search in the technical literature (using the keyword ``urban traffic" to filter out articles on data network traffic) retrieved the following number of articles (as of December 3, 2013): 9,443 (ACM Digital Library), 26,054 (Scopus), and 1,730,000 (Google Scholar). Moreover, articles listed in the ACM query relate to conferences as diverse as MobiCom, CHI, PADS, and AAMAS. This means that there is a big and diverse community of computer scientists and computer engineers who tackle research that is connected to the development of intelligent traffic and transportation systems. It is also possible to see that this community is growing, and that research projects are getting more and more interdisciplinary. To foster the cooperation among the involved communities, this book aims at giving a broad introduction into the basic but relevant concepts related to transportation systems, targeting researchers and practitioners from computer science and information technology. In addition, the second part of the book gives a panorama of some of the most exciting and newest technologies, originating in computer science and computer engineering, that are now being employed in projects related to car-to-car communication, interconnected vehicles, car navigation, platooning, crowd sensing and sensor networks, among others. This material will also be of interest to engineers and researchers from the traffic and transportation community.
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