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Online ISSN 1751-9578 Print ISSN 1751-956X

IET Intelligent Transport Systems

Volume 4, Issue 3, September 2010

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Volume 4, Issue 3

September 2010

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    • Urban traffic signal control using reinforcement learning agents
      • Author(s): P.G. Balaji ; X. German ; D. Srinivasan
      • Source: IET Intelligent Transport Systems, Volume 4, Issue 3, p. 177 –188
      • DOI:  10.1049/iet-its.2009.0096
      • Type: Article
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      • p. 177 –188 (12)
        This study presents a distributed multi-agent-based traffic signal control for optimising green timing in an urban arterial road network to reduce the total travel time and delay experienced by vehicles. The proposed multi-agent architecture uses traffic data collected by sensors at each intersection, stored historical traffic patterns and data communicated from agents in adjacent intersections to compute green time for a phase. The parameters like weights, threshold values used in computing the green time is fine tuned by online reinforcement learning with an objective to reduce overall delay. PARAMICS software was used as a platform to simulate 29 signalised intersection at Central Business District of Singapore and test the performance of proposed multi-agent traffic signal control for different traffic scenarios. The proposed multi-agent reinforcement learning (RLA) signal control showed significant improvement in mean time delay and speed in comparison to other traffic control system like hierarchical multi-agent system (HMS), cooperative ensemble (CE) and actuated control.
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      Development of a real-time bus arrival prediction system for Indian traffic conditions
      • Author(s): R.P.S. Padmanaban ; K. Divakar ; L. Vanajakshi ; S.C. Subramanian
      • Source: IET Intelligent Transport Systems, Volume 4, Issue 3, p. 189 –200
      • DOI:  10.1049/iet-its.2009.0079
      • Type: Article
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      • p. 189 –200 (12)
        The accuracy of Bus Traveler Information Systems (BTIS) depends on several factors such as accuracy of the input data, speed of data transfer, data quality control and performance of the prediction scheme. A majority of the existing BTIS in India does not take into account the real-time data and the quality control of data. Also, there is a scope for improving the performance of the underlying prediction schemes. There are several studies on real-time bus arrival time prediction under homogeneous traffic conditions. However, the traffic condition in India is different and direct implementation of those studies may not yield the best results. One of the main components of bus travel time is the delay time at bus stops, in addition to the other common delays. These delays need to be incorporated in the prediction scheme for better accuracy, which is not the case currently in most studies. Also, there is a need to develop an accurate automated bus arrival time prediction system using real-time data under heterogeneous traffic conditions. This study presents a model-based algorithm that uses real-time data from field and takes delays automatically into account for an accurate prediction of bus arrival time. The results obtained are compared with the currently adopted field method and show a clear improvement in the prediction accuracy.
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      Current paradigms in intelligent transportation systems
      • Author(s): S.L. Toral ; M.R. Martínez Torres ; F.J. Barrero ; M.R. Arahal
      • Source: IET Intelligent Transport Systems, Volume 4, Issue 3, p. 201 –211
      • DOI:  10.1049/iet-its.2009.0102
      • Type: Article
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      • p. 201 –211 (11)
        Intelligent transportation systems (ITS) constitute today a multidisciplinary field of study involving a large number of different research areas. As a consequence, it is difficult to achieve a structured view of ITS, which is necessary to unify efforts and as guidance for future developments. This study aims to identify the main paradigms in the field of ITS by semantically analysing studies related to this general topic. An understanding about which research is considered valuable by the research community to build upon may provide valuable insights in this field. As a result of the statistical treatment of data, up to 13 paradigms are obtained. The scope of these paradigms and the relationships between them have also been detailed, providing a structured vision of ITS synthesised in a map form.
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      Graphical route information panel for the urban freeway network in Shanghai, China
      • Author(s): H. Gan
      • Source: IET Intelligent Transport Systems, Volume 4, Issue 3, p. 212 –220
      • DOI:  10.1049/iet-its.2010.0017
      • Type: Article
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      • p. 212 –220 (9)
        The concept of using graphical route information panel (GRIP) to improve the dynamic traffic management efficiency is becoming increasingly popular recently. Colour-coded level-of-service (LOS) map and route travel time are important information displayed by GRIP. This study addresses the graphical information provision issue and the travel time prediction issue, based on research and development of Shanghai urban freeway GRIPs. It first presents function and location of Shanghai GRIP, philosophy of GRIP panel layout and basic principle of LOS display method. Then it focuses on segmentation of LOS map and proposes three segmentation approaches: the detector-based approach, the ramp-based approach and the hybrid approach. Opinions and lessons learned regarding advantages and disadvantages of different segmentation approaches are given. Next, it proposes a macroscopic traffic flow model-based travel time prediction approach for GRIP. The traffic flow model incorporated in the prediction approach is a validated high-order continuum model. The preliminary performance test of the approach is conducted using real-traffic data of a three-lane urban freeway section of Yan-An elevated road in Shanghai. The results reveal that the travel time prediction approach performs well both under free-flowing conditions and under congested conditions. Last, it gives concluding remarks.
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      Economic evaluation of intelligent transportation systems strategies: the case of the Oslo toll cordon
      • Author(s): J. Odeck  and  M. Welde
      • Source: IET Intelligent Transport Systems, Volume 4, Issue 3, p. 221 –228
      • DOI:  10.1049/iet-its.2010.0027
      • Type: Article
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      • p. 221 –228 (8)
        Intelligent transportation systems (ITS) projects often offer an effective solution for many transportation problems as compared to traditional solutions such as increasing road capacity to solve congestion problems. However, ITS projects are often not evaluated in economic terms either because methodologies are not available, or when they are, data become a limitation. Since economic assessment is the order of the day in the transportation sector, many potential ITS projects are losing terrain relative to alternative solutions. This study develops and demonstrates that economic evaluation of ITS projects in the road sector is possible. The authors use the Oslo toll cordon as a case example, where semi-automatic toll collection was replaced by a full-fledged ITS-based toll collection. The results show that ITS-based toll collection is highly profitable from an economic point of view. The reasons are that the ITS-based toll collection relieves congestion at toll points thereby leading to (i) time savings for road users, (ii) reduced noise and pollution associated with slow movement of vehicles at toll points, (iii) improvement of the city's landscape because toll booths and signposts are removed and (iv) reduced costs associated with operating tolls. The study urges ITS proponents to start using economic evaluation when assessing the merits of their projects.
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