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    Achurra-Gonzalez PE, Novati M, Foulser-Piggott R, Graham DJ, Bowman G, Bell MGH, Angeloudis Pet al., 2019,

    Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application.

    , Accid Anal Prev, Vol: 123, Pages: 399-410

    Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity.

    Ainalis D, Achurra-Gonzalez P, Gaudin A, Garcia de la Cruz JM, Angeloudis P, Ochieng WY, Stettler MEJet al.,

    Ultra-Capacitor based kinetic energy recovery system for heavy goods vheicles

    , 15th International Symposium on Heavy Vehicle Transport Technology

    The Climate Change Act 2008 commits the UK to reduce the Greenhouse Gas emissions by 80% by 2050 relative to 1990 levels. While Heavy Goods Vehicles and buses contribute about 4% of the total Greenhouse Gas emissions in the UK, these emissions only decrease by 10% between 1990 and 2015. Urban areas are particularly susceptible to emissions and can have a significant impact upon the health of residents. For Heavy Goods Vehicles, braking losses are one of the most significant losses. A Kinetic Energy Recovery System can help reduce these emissions, and increase fuel efficiency by up to 30 %. This paper describes an InnovateUK funded project aimed at evaluating the technical and economic feasibility of a retrofitted Kinetic Energy Recovery System on Heavy Goods Vehicles through an operational trial, controlled emissions and fuel tests, and numerical modelling. A series of preliminary results using a numerical vehicle model is compared with operational data, along with simulations comparing the fuel efficiency of a Heavy Goods Vehicle with and without the KERS.

    Rivers R, Evans T, Knappett C, 2017,

    Winds and maritime linkages in ancient Greece

    , Advances in Shipping Data Analysis and Modeling: Tracking and Mapping Maritime Flows in the Age of Big Data, Pages: 11-20, ISBN: 9781315271446
    Achurra Gonzalez PE, Angeloudis P, Hu S, Zavitsas K, Graham DJet al.,

    Modelling the impact of infrastructure developments on the resilience of intermodal container transport networks: One-Belt-One-Road Case study

    , 7th International Conference on Logistics and Maritime Systems
    Koudis GS, Hu SJ, Majumdar A, Jones R, Stettler MEJet al., 2017,

    Airport emissions reductions from reduced thrust takeoff operations

    Karamanis R, Niknejad A, Angeloudis P,

    A Fleet Sizing Algorithm for Autonomous Car Sharing

    , Transportation Research Board 96th Annual Meeting
    Achurra Gonzalez PE, Angeloudis P, Zavitsas K, Niknejad SA, Graham DJet al.,

    A Quantitative Framework for Assessment of Network Vulnerability in Liner Shipping Networks

    , Transportation Research Board 96th Annual Meeting
    Goldbeck N, Angeloudis P, 2017,

    Civil Engineering

    , Defining the Urban: Interdisciplinary and Professional Perspectives, Editors: Iossifova, Gasparatos, Doll, Publisher: Routledge, ISBN: 978-1472449498
    Wang K-C, Wang W-C, Wang H-H, Hsu P-Y, Wu W-H, Kung C-Jet al., 2016,

    Applying building information modeling to integrate schedule and cost for establishing construction progress curves

    , Automation in Construction, Vol: 72, Pages: 397-410, ISSN: 0926-5805
    Song J, Hu J, Han K,

    Real-time adaptive traffic signal control: Trade-off between traffic and environmental objectives

    , Transportation Research Board 96th Annual Meeting
    Sun R, Han K, Hu J, Wang Y, Hu M, Ochieng WYet al., 2016,

    Integrated solution for anomalous driving detection based on BeiDou/GPS/IMU measurements

    Goldbeck N, Angeloudis P, Ochieng W, 2016,

    Analysing the resilience of metro systems under consideration of interdependencies: A combined Dynamic Bayesian Network and network flow approach

    , 14th World Conference on Transport Research (WCTR)
    WANG S-H, WANG W-C, HSU P-Y, CHEN C-H, WANG K-Cet al., 2016,


    , JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT, Vol: 22, Pages: 890-902, ISSN: 1392-3730
    Mascia M, Hu J, Han K, North R, Van Poppel M, Theunis J, Beckx C, Litzenberger Met al., 2016,

    Impact of traffic management on black carbon emissions: a microsimulation study

    , Networks & Spatial Economics, Vol: 17, Pages: 269-291, ISSN: 1572-9427

    This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project.

    Achurra Gonzalez PE, Angeloudis P, Zavitsas K, Niknejad SA, Graham DJet al.,

    Attacker-defender modelling of transport vulnerability in maritime logistics corridors

    , 2nd International Workshop on Maritime Flows and Networks
    Mascia M, Hu S, Han K, Sun A, North R, Lees-Miller JDet al., 2016,

    A holistic approach for performance assessment of personal rapid transit

    Goldbeck N, Angeloudis P, Ochieng W, 2016,

    Joint Vulnerability Analysis of Urban Rail Transit and Utility Networks

    , Transportation Research Board 95th Annual Meeting, Publisher: Transportation Research Board

    As climate change is expected to increase the frequency of extreme weather events, cities around the world develop strategies to improve their disaster resilience. A key issue is the protection of critical urban infrastructure systems, such as transport networks. Rail transit networks are particularly exposed to flood risks and additional vulnerabilities arise from interdependencies with other infrastructure systems. This paper aims to improve modelling techniques that help to understand the conditions under which cascading failure can occur in interdependent urban infrastructure systems. Building on existing network flow models, a novel method for the coupling of networks is introduced, using binary connector variables and mixed integer linear programming. The coupling is modelled as additional commodity demand that is induced in one network depending on the commodity flows in another network. An example problem consisting of a rail transit network, a control system, an electric power network and a water supply network illustrates the practicability of the proposed modelling technique.

    Sun R, Han K, Hu J, Bai H, Ochieng WYet al., 2016,

    An Integrated Algorithm Based on BeiDou/GPS/IMU and its Application for Anomalous Driving Detection

    , 29th International Technical Meeting of The-Satellite-Division-of-the-Institute-of-Navigation (ION GNSS+), Publisher: INST NAVIGATION, Pages: 1885-1890, ISSN: 2331-5911
    Mascia M, Hu SJ, Han K, North RJ, Vranckx S, Van Poppel M, Theunis J, Litzenberger Met al., 2015,

    Reducing Environmental Impact By Adaptive Traffic Control And Management For Urban Road Networks

    , The 94th Transportation Research Board Annual Meeting, Publisher: Transportation Research Board

    This paper investigates the effectiveness of traffic signal control and variable message sign (VMS) as environmental traffic management tool. The focus is on black carbon and CO2, which are among the highest contributors to climate change. The modelling tool chain adopted to support this study includes traffic microsimulation, emission modelling and dispersion modelling. A number of scenarios have been simulated with different levels of demand and VMS compliance rates. The results demonstrate the potential of these interventions in reducing black carbon and CO2 emissions and improving air quality, as well as reducing traffic congestion and travel delays.

    Hu J, Mascia M, Han K, Thiyagarajah A, Luan J, North Ret al., 2015,

    Assessment of different urban traffic control strategy impacts on vehicle emissions

    , The 47th Annual UTSG Conference

    This paper investigates the influence of traffic signal control strategy on vehicle emissions, vehicle journey time and total throughput flow within a single isolated four-armed junction. Two pre-timed signal plans are considered, one with two-stages involving permissive-only opposing turns and the other with four-stages which has no conflicting traffic. Additionally, the increase in efficiency by utilising actuated signal timing where green time is re-optimised as flow values vary is investigated. A microscopic traffic simulation model is used to model flows and AIRE (Analysis of Instantaneous Road Emissions) microscopic emissions model is utilised to out- put emission levels from the flow data. A simple junction model shows that the two-stage signal plan is more efficient in both emis- sions and journey time. However, as the level of opposed turning vehicles and conflicting movement increases, the two-stage model moves to being the inferior signal plan choice and the four-stage plan outputs fewer emissions than the two-stage plan. A real-world example of a four-armed junction has been used in this study and from the traffic survey data and existing junction layout; it is rec- ommended that a two-stage plan is used as it produces lower amounts of emissions and shorter journey times compared to a four-stage plan. The results also show that nitrogen oxides (NOx) are the most sensitive to changes in flow followed by carbon dioxide (CO2), Black Carbon and then particulate matter (PM10).

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