282 results found
Goldbeck N, Angeloudis P, Ochieng WY, 2019, Resilience assessment for interdependent urban infrastructure systems using dynamic network flow models, Reliability Engineering and System Safety, Vol: 188, Pages: 62-79, ISSN: 0951-8320
© 2019 Elsevier Ltd Critical infrastructure systems are becoming increasingly interdependent, which can exacerbate the impacts of disruptive events through cascading failures, hindered asset repairs and network congestion. Current resilience assessment methods fall short of fully capturing such interdependency effects as they tend to model asset reliability and network flows separately and often rely on static flow assignment methods. In this paper, we develop an integrated, dynamic modelling and simulation framework that combines network and asset representations of infrastructure systems and models the optimal response to disruptions using a rolling planning horizon. The framework considers dependencies pertaining to failure propagation, system-of-systems architecture and resources required for operating and repairing assets. Stochastic asset failure is captured by a scenario tree generation algorithm whereas the redistribution of network flows and the optimal deployment of repair resources are modelled using a minimum cost flow approach. A case study on London's metro and electric power networks shows how the proposed methodology can be used to assess the resilience of city-scale infrastructure systems to a local flooding incident and estimate the value of the resilience loss triangle for different levels of hazard exposure and repair capabilities.
Koudis GS, Hu SJ, Majumdar A, et al., 2018, The impact of single engine taxiing on aircraft fuel consumption and pollutant emissions, AERONAUTICAL JOURNAL, Vol: 122, Pages: 1967-1984, ISSN: 0001-9240
Ainalis D, Achurra-Gonzalez P, Gaudin A, et 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.
Han K, Graham D, Ochieng W, 2018, M20/A20 Congestion Prediction with Post-Brexit Border Delays, M20/A20 Congestion Prediction with Post-Brexit Border Delays
This research was commissioned by the BBC Inside Out South East program. It aims to quantify the congestion impact on M20/A20 of potential check time increase at Port of Dover and Eurotunnel (in Folkestone) in a post-Brexit scenario. We focus on a 40-mile segment of the M20/A20 motorway between Maidstone and Dover, with local access to Ashford and Folkestone. We consider outbound lorries and passenger vehicles that use the ferry and tunnel to cross the Straight of Dover, as well as traffic with local origins and destinations. Traffic simulations were conducted with assumptions regarding the check times at Dover and Eurotunnel for both current and post-Brexit scenarios. The impact of vehicle queuing at these locations was assessed in terms of queue length, travel time, and disruption to local traffic. The findings show that even one or two minutes of extra check times at the borders are accompanied by a dramatic increase of congestion on the motorways as well as local streets, with queues extending up to 30 miles from Dover/Eurotunnel towards Maidstone and travel time approaching 5 hours in peak times.
Escribano Macias J, Angeloudis P, Ochieng W, AIAA Integrated Trajectory-Location-Routing for Rapid Humanitarian Deliveries using Unmanned Aerial Vehicles, 2018 Aviation Technology, Integration, and Operations Conference
Yin J, Ma Y, Hu Y, et al., 2018, Dynamic Runway Configurations and Flexible Arrival/Departure Tradeoffs in Metroplex Airports, IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), Publisher: IEEE, Pages: 1176-1183, ISSN: 2155-7195
Sun R, Cheng Q, Xue D, et al., 2017, GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application, SENSORS, Vol: 17, ISSN: 1424-8220
Ali BS, Ochieng WY, Zainudin R, 2017, An analysis and model for Automatic Dependent Surveillance Broadcast (ADS-B) continuity, GPS SOLUTIONS, Vol: 21, Pages: 1841-1854, ISSN: 1080-5370
Sun R, Cheng Q, Wang G, et al., 2017, A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults, SENSORS, Vol: 17, ISSN: 1424-8220
Qin F, Sun R, Ochieng WY, et al., 2017, Integrated GNSS/DR/road segment information system for variable road user charging, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 82, Pages: 261-272, ISSN: 0968-090X
Ochieng W, 2017, Integrated method for the UAV navigation sensor anomaly detection, IET Radar, Sonar and Navigation, Vol: 11, Pages: 847-853, ISSN: 1751-8784
© 2016, The Institution of Engineering and Technology. The rapid development of unmanned aerial vehicles (UAVs) has made great progress for its widespread uses in military and civilian applications in recent years. On-board integrated navigation sensors are essential for UAV flight control systems in that they must operate with robustness and reliability. To achieve this, timely and effectively anomaly detection capabilities for the estimated UAV status from the integrated navigation sensors are required to ensure the UAV flight safety. Extraction of the anomaly information from the real-time navigation sensors and designing a robust and reliable anomaly detection algorithm are major issues for the UAV navigation sensor anomaly detection. This study introduces a novel integrated algorithm for detecting UAV on-board navigation sensor anomaly, by combining particle filter (PF) estimated state residuals with fuzzy inference system (FIS) decision system. The residual information is obtained based on the difference between the collected Global Positioning System measurements and high accuracy PF estimates. The indicators derived from the PF residuals are further made as inputs for the FIS system to output the different anomaly levels. The simulation and filed test results have demonstrated the effectiveness and efficiency of the proposed anomaly detection method in terms of timeliness, recall and precision.
Zhang X, Zhan X, Feng S, et al., 2017, An Analytical Model for BDS B1 Spreading Code Self-Interference Evaluation Considering NH Code Effects, SENSORS, Vol: 17, ISSN: 1424-8220
Sidiropoulos S, Han K, Majumdar A, et al., 2017, Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 75, Pages: 212-227, ISSN: 0968-090X
Ali BS, Schuster W, Ochieng WY, 2017, Evaluation of the Capability of Automatic Dependent Surveillance Broadcast to Meet the Requirements of Future Airborne Surveillance Applications, Journal of Navigation, Vol: 70, Pages: 49-66, ISSN: 0373-4633
© 2016 The Royal Institute of Navigation. Automatic Dependent Surveillance Broadcast (ADS-B) Out supports various ground applications including Air Traffic Control (ATC) surveillance in radar airspace, non-radar airspace and on the airport surface. In addition, the capability of aircraft to receive ADS-B Out messages from other aircraft within their coverage (ADS-B In) enables enhanced airborne surveillance applications. The requirements of the application vary depending on its safety-criticality. More stringent applications will require higher levels of performance. It is therefore critical that the ADS-B system performance is measured against the most stringent application it is designed for. This paper reviews the various enhanced airborne surveillance applications and the required ADS-B information to support them. It identifies the ADS-B based applications required for Air Traffic Management (ATM) modernisation under the SESAR/NextGen programs. It discusses existing ADS-B Out versions and their capabilities. A mapping exercise is undertaken to assess the credibility of the ADS-B system performance to support the functionalities and requirements of the various enhanced airborne surveillance applications and establish those that require further research and development, highlighting some of the key challenges.
Shang W, Han K, Ochieng W, et al., 2017, Agent-based day-to-day traffic network model with information percolation, TRANSPORTMETRICA A-TRANSPORT SCIENCE, Vol: 13, Pages: 38-66, ISSN: 2324-9935
Sun R, Xie F, Xue D, et al., 2017, A Novel Rear-End Collision Detection Algorithm Based on GNSS Fusion and ANFIS, JOURNAL OF ADVANCED TRANSPORTATION, ISSN: 0197-6729
Goldbeck N, Angeloudis P, Ochieng WY, 2017, A Dynamic Network Flow Model for Interdependent Infrastructure and Supply Chain Networks with Uncertain Asset Operability, Publisher: Springer International Publishing, Pages: 513-528, ISSN: 0302-9743
Anvari B, Angeloudis P, Ochieng WY, 2016, A multi-objective GA-based optimisation for holistic Manufacturing, transportation and Assembly of precast construction, Automation in Construction, Vol: 71, Pages: 226-241, ISSN: 0926-5805
Sun R, Han K, Hu J, et al., 2016, Integrated solution for anomalous driving detection based on BeiDou/GPS/IMU measurements, TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, Vol: 69, Pages: 193-207, ISSN: 0968-090X
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)
Anvari B, Majumdar A, Ochieng W, Mixed traffic modelling involving pedestrian dynamics for integrated street designs: A review, PED2016: 8th International Conference on Pedestrian and Evacuation Dynamics
Nascimento FAC, Majumdar A, Ochieng WY, et al., 2016, Fundamentals of safety management: The Offshore Helicopter Transportation System Model, SAFETY SCIENCE, Vol: 85, Pages: 194-204, ISSN: 0925-7535
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, et 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
Damy S, Majumdar A, Ochieng WY, 2016, GNSS-based High Accuracy Positioning for Railway Applications, 47th Annual Precise Time and Time Interval Systems and Applications Meeting (PTTI) / International Technical Meeting of the-Institute-of-Navigation, Publisher: INST NAVIGATION, Pages: 1003-1014, ISSN: 2330-3646
Anvari B, Bell MGH, Angeloudis P, et al., 2016, Calibration and Validation of a Shared Space Model Case Study, TRANSPORTATION RESEARCH RECORD, Pages: 43-52, ISSN: 0361-1981
Zhang X, Zhang Z, Ochieng W, et al., 2016, A Reverse Approach to Antenna Specifications for London Buses Next-generation Positioning System, 29th International Technical Meeting of The-Satellite-Division-of-the-Institute-of-Navigation (ION GNSS+), Publisher: INST NAVIGATION, Pages: 1927-1936, ISSN: 2331-5911
Xue Y, Feng S, Ochieng WY, et al., 2016, The Improvement of the Positioning Accuracy in Search and Rescue with Two Satellites, 7th China Satellite Navigation Conference (CSNC), Publisher: SPRINGER, Pages: 255-261, ISSN: 1876-1100
Sidiropoulos S, Han K, Majumdar A, et al., 2016, Identifying significant traffic flow patterns in Multi-Airport systems terminal manoeuvring areas under uncertainty
© 2016 American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. Multi-Airport Systems (MAS), or Metroplex, serve air traffic demand in large metropolitan aeras such as New York, London and Tokyo. Due to the spatial proximity of the airports, Metroplex airspaces are characterized by high complexity and heavy traffic; and current system structures fail to make optimal use of the available spatio-temporal airspace resources. To increase the operational efficiency in such systems, an accurate depiction of the dominant demand patterns over the operational horizon is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems. The framework is in alignmemt with the Dynamic Route service policy for the effective management of Metroplex operations. A deterministic demand modeling approach is presented first, which takes into account the spatio-temporal changes in demand over the planning horizon of operations for the identification of significant traffic flow patterns. To handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is then proposed, which takes into account historical information regarding both prediction and realization of the traffic demand. Prediction errors are taken into account in a tractable and robust way to ensure the reliability of the optimized control. The DRO approach is applied to decision making in a tactical context (i.e. one-day planning) and on a rolling horizon basis (i.e. every 2 hours). The framework is applied to Time Based Flow Management (TBFM) data for the New York Metroplex (N90). The framework and results are validated by Subject Matter Experts (SMEs) from the Port Authority of New York and New Jersey (PANYNJ).
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