Publications
324 results found
Sun Y, Wang H, Quan W, et al., 2023, Smart Road Stud-Empowered Vehicle Magnetic Field Distribution and Vehicle Detection, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, ISSN: 1524-9050
Xia Y, Geng M, Chen Y, et al., 2023, Understanding common human driving semantics for autonomous vehicles, Patterns
Autonomous vehicles will share roads with human-driven vehicles until the transition to fully autonomous transport systems is complete. The critical challenge of improving mutual understanding between both vehicle types cannot be addressed only by feeding extensive driving data into data-driven models but by enabling autonomous vehicles to understand and apply common driving behaviors analogous to human drivers. Therefore, we designed and conducted two electroencephalography experiments for comparing the cerebral activities of human linguistics and driving understanding. The results showed that driving activates hierarchical neural functions in the auditory cortex, which is analogous to abstraction in linguistic understanding. Subsequently, we proposed a neural-informed, semantics-driven framework to understand common human driving behavior in a brain-inspired manner. This study highlights the pathway of fusing neuroscience into complex human behavior understanding tasks and provides a computational neural model to understand human driving behaviors, which will enable autonomous vehicles to perceive and think like human drivers.
Sun R, Qiu M, Liu F, et al., 2022, A Dual w-Test Based Quality Control Algorithm for Integrated IMU/GNSS Navigation in Urban Areas, REMOTE SENSING, Vol: 14
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- Citations: 2
Shang W-L, Gao Z, Daina N, et al., 2022, Benchmark Analysis for Robustness of Multi-Scale Urban Road Networks Under Global Disruptions, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, ISSN: 1524-9050
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- Citations: 31
Sun R, Zhang Z, Cheng Q, et al., 2022, Pseudorange error prediction for adaptive tightly coupled GNSS/IMU navigation in urban areas, GPS SOLUTIONS, Vol: 26, ISSN: 1080-5370
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- Citations: 15
Cheong H-I, Wu Z, Majumdar A, et al., 2021, One-way coupling of fire and egress modeling for realistic evaluation of evacuation process, Transportation Research Record, Vol: 2675, Pages: 1244-1259, ISSN: 0361-1981
In the discipline of fire engineering, computational simulation tools are used to evaluate the available safe egress time (ASET) and required safe egress time (RSET) of a building fire. ASET and RSET are often analyzed separately, using computational fluid dynamics (CFD) and crowd dynamics, respectively. Although there are advantages to coupling the ASET and RSET analysis to quantify tenability conditions and reevaluate evacuation time within a building, the coupling process is computationally complex, requiring multiple steps. The coupling setup can be time-consuming, particularly when the results are limited to the modeled scenario. In addition, the procedure is not uniform throughout the industry. This paper presents the successful one-way coupling of CFD and crowd dynamics modeling through a new simplified methodology that captures the impact of fractional effective dose (FED) and reduced visibility from smoke on the individual evacuee’s movement and the human interaction. The simulation tools used were Fire Dynamics Simulator (FDS) and Oasys MassMotion for crowd dynamics. The coupling was carried out with the help of the software development kit of Oasys MassMotion in two different example geometries: an open-plan room and a floor with six rooms and a corridor. The results presented in this paper show that, when comparing an uncoupled and a coupled simulation, the effects of the smoke lead to different crowd density profiles, particularly closer to the exit, which elongates the overall evacuation time. This coupling method can be applied to any geometry because of its flexible and modular framework.
Mijic A, Whyte J, Myers R, et al., 2021, Reply to a discussion of 'a research agenda on systems approaches to infrastructure' by david elms, Civil Engineering and Environmental Systems: decision making and problem solving, Vol: 38, Pages: 295-297, ISSN: 0263-0257
Sun R, Wang J, Cheng Q, et al., 2021, A new IMU-aided multiple GNSS fault detection and exclusion algorithm for integrated navigation in urban environments, GPS SOLUTIONS, Vol: 25, ISSN: 1080-5370
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- Citations: 29
Chen C, Hu S, Ochieng WY, et al., 2021, Understanding City-Wide Ride-Sourcing Travel Flow: A Geographically Weighted Regression Approach, JOURNAL OF ADVANCED TRANSPORTATION, Vol: 2021, ISSN: 0197-6729
Wang Y, Wang L, Lin S, et al., 2021, Effect of Working Experience on Air Traffic Controller Eye Movement, Engineering, Vol: 7, Pages: 488-494, ISSN: 2095-8099
Eye movement is an important indicator of information-seeking behavior and provides insight into cognitive strategies which are vital for decision-making. Various measures based on eye movements have been proposed to capture humans’ ability to process information in a complex environment. The effectiveness of these measures has not yet been fully explored in the field of air traffic management. This paper presents a comparative study on eye-movement measures in air traffic controllers with different levels of working experience. Two commonly investigated oculomotor behaviors, fixation and saccades, together with gaze entropy, are examined. By comparing the statistical properties of the relevant metrics, it is shown that working experience has a notable effect on eye-movement patterns. Both fixation and saccades differ between qualified and novice controllers, with the former type of controller employing more efficient searching strategies. These findings are useful in enhancing the quality of controller training and contributing to an understanding of the information-seeking mechanisms humans use when executing complex tasks
Mijic A, Whyte J, Fisk D, et al., 2021, The Centre for Systems Engineering and Innovation – 2030 vision and 10-year celebration
The 2030 vision of the Centre is to bring Systems Engineering and Innovation to Civil Infrastructure by changing how cross-sector infrastructure challenges are addressedin an integrated way using principles of systems engineering to maximise resilience, safety and sustainability in an increasingly complex world.We want to better understand the environmental and societal impacts of infrastructure interventions under uncertainty. This requires a change in current approaches to infrastructure systems engineering: starting from the natural environmentand its resources, encompassing societaluse of infrastructure and the supporting infrastructure assets and services.We argue for modelling that brings natural as well as built environments within the system boundaries to better understand infrastructure and to better assess sustainability. We seethe work as relevant to both the academic community and to a wide range of industry and policy applications that are working on infrastructure transition pathways towards fair, safe and sustainable society.This vision was developed through discussions between academics in preparation for the Centre for Systems Engineering and Innovation (CSEI) 10 years celebration. These rich discussions about the future of the Centre were inspired by developing themes for a celebration event, through which we have summarised the first 10 years of the Centre’s work and our vision for the future and identified six emerging research areas.
Sun R, Cheng Q, Xie F, et al., 2021, Combining Machine Learning and Dynamic Time Wrapping for Vehicle Driving Event Detection Using Smartphones, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, Vol: 22, Pages: 194-207, ISSN: 1524-9050
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- Citations: 11
Whyte J, Mijic A, Myers RJ, et al., 2020, A research agenda on systems approaches to infrastructure, Journal of Civil Engineering and Environmental Systems, Vol: 37, Pages: 214-233, ISSN: 1029-0249
At a time of system shocks, significant underlying challenges are revealed in current approaches to delivering infrastructure, including that infrastructure users in many societies feel distant from nature. We set out a research agenda on systems approaches to infrastructure, drawing on ten years of interdisciplinary work on operating infrastructure, infrastructure interventions and lifecycles. Research insights and directions on complexity, systems integration, data-driven systems engineering, infrastructure life-cycles, and the transition towards zero pollution are summarised. This work identifies a need to better understand the natural and societal impacts of infrastructure interventions under uncertainty. We argue for a change in current approaches to infrastructure: starting from the natural environment and its resources, encompassing societal use of infrastructure and the supporting infrastructure assets and services. To support such proposed new systems approaches to infrastructure, researchers need to develop novel modelling methods, forms of model integration, and multi-criteria indicators.
Shang W-L, Chen Y, Bi H, et al., 2020, Statistical Characteristics and Community Analysis of Urban Road Networks, Complexity, Vol: 2020, Pages: 1-21, ISSN: 1076-2787
<jats:p>Urban road networks are typical complex systems, which are crucial to our society and economy. In this study, topological characteristics of a number of urban road networks purely based on physical roads rather than routes of vehicles or buses are investigated in order to discover underlying unique structural features, particularly compared to other types of transport networks. Based on these topological indices, correlations between topological indices and small-worldness of urban road networks are also explored. The finding shows that there is no significant small-worldness for urban road networks, which is apparently different from other transport networks. Following this, community detection of urban road networks is conducted. The results reveal that communities and hierarchy of urban road networks tend to follow a general nature rule.</jats:p>
Wang H, Quan W, Ochieng WY, 2020, Smart road stud based two-lane traffic surveillance, JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, Vol: 24, Pages: 480-493, ISSN: 1547-2450
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- Citations: 6
Escribano Macias J, Goldbeck N, Hsu P-Y, et al., 2020, Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles, OR SPECTRUM, Vol: 42, Pages: 1089-1125, ISSN: 0171-6468
Unmanned aerial vehicles (UAVs) have been increasingly viewed as useful tools to assist humanitarian response in recent years. While organisations already employ UAVs for damage assessment during relief delivery, there is a lack of research into formalising a problem that considers both aspects simultaneously. This paper presents a novel endogenous stochastic vehicle routing problem that coordinates UAV and relief vehicle deployments to minimise overall mission cost. The algorithm considers stochastic damage levels in a transport network, with UAVs surveying the network to determine the actual network damages. Ground vehicles are simultaneously routed based on the information gathered by the UAVs. A case study based on the Haiti road network is solved using a greedy solution approach and an adapted genetic algorithm. Both methods provide a significant improvement in vehicle travel time compared to a deterministic approach and a non-assisted relief delivery operation, demonstrating the benefits of UAV-assisted response.
Shang W-L, Chen Y, Song C, et al., 2020, Robustness Analysis of Urban Road Networks from Topological and Operational Perspectives, Mathematical Problems in Engineering, Vol: 2020, Pages: 1-12, ISSN: 1024-123X
<jats:p>This study comprehensively analyses the robustness of urban road networks through topological indices based on the complex network theory and operational indices based on traffic assignment theory: User Equilibrium (UE), System Optimum (SO), and Price of Anarchy (POA). Analysing topological indices may pin down the most important nodes for URNs from the perspective of connectivity, while more sophisticated operational indices are helpful to examine the importance of nodes for URNs by taking into account link capacity, travel demand, and drivers’ behaviour. The previous way is calculated in a static way, which reduces the computation times and increases the efficiency for quick assessment of the robustness of URNs, while the latter is in a dynamic way, namely, calculating is based on removal of individual nodes, although this way is more likely to capture realistic meanings but consumes huge amount of time. The efforts made in this study try to find the relationship between topological and operational indices so as to assist the assessment of robustness of URNs to local disruptions. Seven realistic urban road networks such as Sioux Falls and Anaheim are used as network examples, and results show that different indices reflect robustness characteristics of urban road networks from different ways, and rank correlations between any two indices are poor although small network such as Sioux Falls have better correlations than others.</jats:p>
Ochieng W, Nascimento F, Majumdar A, 2020, Predictive Safety Through Survey Interviewing - Developing a Task-Based Hazard Identification Survey Process in Offshore Helicopter Operations, Advances in Human Aspects of Transportation Proceedings of the AHFE 2020 Virtual Conference on Human Aspects of Transportation, July 16-20, 2020, USA, Editors: Stenton, Publisher: Springer Nature, ISBN: 9783030509439
Offshore helicopters play a vital role in energy production worldwide and must be operated safely. Safety is underpinned by hazard identification, which aspires to be predictive and remain operationally relevant. A process to elicit pilots’ operational hazard knowledge in a predictive manner is currently absent. This paper redresses this by developing a Task-Based Hazard Identification Survey Process which, through Talk-Through interviewing, collects data from a statistically representative sample of pilots based in specified regions. A factual and exhaustive hazards’ template is formed, to which various statistical methods are applied. Subjected to multiple validation and reliability checks, the process delivers on the aspiration to be predictive on safety.
Ochieng W, Nascimento F, Majumdar A, 2020, redictive Safety Through Survey Interviewing - Developing a Task-Based Hazard Identification Survey Process in Offshore Helicopter Operations, Advances in Human Aspects of Transportation Proceedings of the AHFE 2020 Virtual Conference on Human Aspects of Transportation, July 16-20, 2020, USA, Editors: Stanton, Publisher: Springer Nature, ISBN: 9783030509439
This book discusses the latest advances in the research and development, design, operation, and analysis of transportation systems and their corresponding infrastructures.
Sun R, Wang G, Fan Z, et al., 2020, An Integrated Urban Positioning Algorithm Using Matching, Particle Swam Optimized Adaptive Neuro Fuzzy Inference System and a Spatial City Model, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, Vol: 69, Pages: 4842-4854, ISSN: 0018-9545
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- Citations: 7
Yu Y, Han K, Ochieng W, 2020, Day-to-day dynamic traffic assignment with imperfect information, bounded rationality and information sharing, Transportation Research Part C: Emerging Technologies, Vol: 114, Pages: 59-83, ISSN: 0968-090X
This paper presents a doubly dynamic day-to-day (DTD) traffic assignment model with simultaneous route-and-departure-time (SRDT) choices while incorporating incomplete and imperfect information as well as bounded rationality. Two SRDT choice models are proposed to incorporate imperfect travel information: One based on multinomial Logit (MNL) model and the other on sequential, mixed multinomial/nested Logit model. These two variants, serving as base models, are further extended with two features: bounded rationality (BR) and information sharing. BR is considered by incorporating the indifference band into the random utility component of the MNL model, forming a BR-based DTD stochastic model. A macroscopic model of travel information sharing is integrated into the DTD dynamics to account for the impact of incomplete information on travelers’ SRDT choices. These DTD choice models are combined with within-day dynamics following the Lighthill-Whitham-Richards (LWR) fluid dynamic network loading model. Simulations on large-scale networks (Anaheim) illustrate the interactions between users’ adaptive decision making and network conditions (including local disruption) with different levels of information availability and user behavior. Our findings highlight the need for modeling network transient and disequilibriated states, which are often overlooked in equilibrium-constrained network design and optimization. The MATLAB package and computational examples are available at https://github.com/DrKeHan/DTD.
Elhajj M, Ochieng WY, 2020, Urban bus positioning: Location based services and high level system architecture, Case Studies on Transport Policy, Vol: 8, Pages: 12-21, ISSN: 2213-624X
Today’s urban transport systems are dominated by private vehicles, which are significant contributors to traffic congestion and pollution. This is expected to increase as the urban population grows, predicted to account for about 68% of the world’s population by 2050. In comparison to private cars, transport systems dominated by buses produce lower traffic congestion and emissions. Therefore, improvements in bus operation activities most of which require information on bus location (i.e. location based services) should facilitate urban transport sustainability.However, to date there is no agreement globally on the location based services, their location requirements and technologies to deliver significant improvement in bus operations. Therefore, this paper creates for the first time, a comprehensive list of bus operation services and specifies the performance requirements. These are considered together with challenging spatio-temporal characteristics of the urban environment to specify a high-level location determination system architecture for urban bus operations. The services, their requirements, standards and positioning system architecture are essential for the formulation of appropriate policies, regulation, service provision, and development and procurement of urban bus positioning systems.
Sun R, Zhang W, Zheng J, et al., 2020, GNSS/INS Integration with Integrity Monitoring for UAV No-fly Zone Management, REMOTE SENSING, Vol: 12
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- Citations: 14
Sun R, Wang G, Zhang W, et al., 2020, A gradient boosting decision tree based GPS signal reception classification algorithm, APPLIED SOFT COMPUTING, Vol: 86, ISSN: 1568-4946
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- Citations: 59
Goldbeck N, Angeloudis P, Ochieng W, 2020, Optimal supply chain resilience with consideration of failure propagation and repair logistics, Transportation Research Part E: Logistics and Transportation Review, Vol: 133, Pages: 1-20, ISSN: 1366-5545
The joint optimisation of investments in capacity and repair capability of production and logistics systems at risk of being damaged is an important aspect of supply chain resilience that is not sufficiently addressed by state-of-the-art modelling approaches. Furthermore, logistical issues of procuring repair resources impact speed of recovery but are not considered in most existing models. This paper presents a novel multi-stage stochastic programming model that optimizes pre-disruption investment decisions, as well as post-disruption dynamic adjustment of supply chain operations and allocation of repair resources. A case study demonstrates how the method can quantify the effects of pooling repair resources.
Escribano Macias J, Angeloudis P, Ochieng W, 2020, Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles, Transportation Research Part C: Emerging Technologies, Vol: 110, Pages: 56-80, ISSN: 0968-090X
Unmanned Aerial Vehicles (UAVs) are being increasingly deployed in humanitarian response operations. Beyond regulations, vehicle range and integration with the humanitarian supply chain inhibit their deployment. To address these issues, we present a novel bi-stage operational planning approach that consists of a trajectory optimisation algorithm (that considers multiple flight stages), and a hub selection-routing algorithm that incorporates a new battery management heuristic. We apply the algorithm to a hypothetical response mission in Taiwan after the Chi-Chi earthquake of 1999 considering mission duration and distribution fairness. Our analysis indicates that UAV fleets can be used to provide rapid relief to populations of 20,000 individuals in under 24 h. Additionally, the proposed methodology achieves significant reductions in mission duration and battery stock requirements with respect to conservative energy estimations and other heuristics.
Yin J, Ma Y, Tian W, et al., 2020, Impact Analysis of Demand Management on Runway Configuration in Metroplex Airports, IEEE Access, Vol: 8, Pages: 66189-66212
Shang W-L, Chen Y, Ochieng WY, 2020, Resilience Analysis of Transport Networks by Combining Variable Message Signs With Agent-Based Day-to-Day Dynamic Learning, IEEE Access, Vol: 8, Pages: 104458-104468
Yang L, van Dam KH, Majumdar A, et al., 2019, Integrated design of transport infrastructure and public spaces considering human behavior: A review of state-of-the-art methods and tools, FRONTIERS OF ARCHITECTURAL RESEARCH, Vol: 8, Pages: 429-453, ISSN: 2095-2635
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- Citations: 20
Huang M, Ochieng WY, Nie H, et al., 2019, Main Wheel Prerotation and Ground Taxi Driven by Electric Taxi System, Journal of Aerospace Engineering, Vol: 32, ISSN: 0893-1321
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