Publications
339 results found
Zhu B, Hu S, Kaparias I, et al., 2024, Revealing the driving factors and mobility patterns of bike-sharing commuting demands for integrated public transport systems, Sustainable Cities and Society, Vol: 104, ISSN: 2210-6707
Bike-sharing for integrated public transport systems (BIPTS) offers an effective solution to the first- and last-mile problems. However, most existing studies have used overly simplified single-catchment area methods to identify BIPTS demands, and the driving factors and mobility patterns of BIPTS commuting demands have remained unclear. To fill this gap, a comprehensive framework for analyzing BIPTS commuting demands is developed. The proposed framework integrates a multi-catchment area method for precise BIPTS demands identification, the SHapley Additive exPlanations (SHAP) approach for uncovering driving factors, and a combination of dimensionality reduction and clustering techniques for discerning mobility patterns, complemented by a validation mechanism. A case study in Beijing demonstrates the efficacy of our multi-catchment areas method, which reduces misidentification of BIPTS demands by 48.6 %. Notably, for morning peak first-mile demands, the driving factors are the available bike density of cycling catchment area, the bikeability index, and the metro passenger inflow. Strong factors interactions are observed, stemming from an imbalance between BIPTS demands and infrastructure supply. Additionally, three distinct commuting patterns emerge, attributed to variations in feature contributions. These insights are crucial for enhancing the seamless integration of bike-sharing and public transport systems.
Li L, Elhajj M, Feng Y, et al., 2023, Machine learning based GNSS signal classification and weighting scheme design in the built environment: a comparative experiment, SATELLITE NAVIGATION, Vol: 4, ISSN: 2662-9291
Shang W-L, Tao X, Bi H, et al., 2023, Audio Related Quality of Experience Evaluation in Urban Transportation Environments With Brain Inspired Graph Learning, 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, Vol: 4, ISSN: 2666-3899
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 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, Vol: 24, Pages: 7357-7362, ISSN: 1524-9050
Adan F, Feng Y, Angeloudis P, et al., 2023, Constrained Multi-Agent Reinforcement Learning Policies for Cooperative Intersection Navigation and Traffic Compliance, Pages: 4079-4085, ISSN: 2153-0009
End to end learning systems are becoming increasingly common in autonomous driving research, from perception, to planning and control. In particular, distributed reinforcement learning systems have demonstrated their applicability to the intersection navigation scenario. Such systems learn via a scalar reward signal from the environment and its design is crucial to the overall performance at the task. In this paper, we investigate an alternative approach to achieving desirable behavior by instead applying constraints to the action spaces and policies of the agents while maintaining a relatively sparse reward regimen. Initial experiments in a simulation environment have demonstrated the efficacy of this approach with simple restrictions in a discrete action space when compared to traditional traffic signal controllers and other Q-learning MARL algorithms. The performance analysis suggest that a more flexible action restriction may be more appropriate but nonetheless validates the utility of the approach by minimising delay and time loss, which we hope will stimulate additional research in policy constraints for autonomous driving.
Nassif E, Tian H, Candela E, et al., 2023, Safety Standards for Autonomous Vehicles: Challenges and Way Forward, Pages: 3004-3009, ISSN: 2153-0009
This paper examines current autonomous vehicle (AV) safety standards and identifies gaps in their scope and depth. It is the first to present a thorough review and critique of such standards. It suggests that they lack the necessary guidance to ensure the safety of AVs, causing a bottleneck in transitioning from AV development to public adoption. Primary challenges of standards are presented, explicitly covering gaps and weaknesses pertaining to AVs' user-system interactions, operational design domains (ODDs), safety testing methods, safety metrics, acceptance criteria, and machine learning pit- falls across the lifecycle of AVs. A way forward to address these challenges is also proposed, emphasising the need to decomplexify the ecosystem of AV standards and promote stake-holder interdependence. The paper concludes by recognising the criticality of legislative and regulatory frameworks for AVs and advocates for cohering safety standards, certification, and regulation.
Mao Y, Sun R, Wang J, et al., 2022, New time-differenced carrier phase approach to GNSS/INS integration, GPS SOLUTIONS, Vol: 26, ISSN: 1080-5370
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- Citations: 14
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: 3
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: 36
Wang H, Sun Y, Quan W, et al., 2022, Traffic volume measurement based on a single smart road stud, MEASUREMENT, Vol: 187, ISSN: 0263-2241
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- Citations: 3
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: 20
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: 55
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
Cheng Q, Chen P, Sun R, et al., 2021, A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning, REMOTE SENSING, Vol: 13
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- Citations: 8
Sun R, Wang G, Cheng Q, et al., 2021, Improving GPS Code Phase Positioning Accuracy in Urban Environments Using Machine Learning, IEEE INTERNET OF THINGS JOURNAL, Vol: 8, Pages: 7065-7078, ISSN: 2327-4662
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- Citations: 28
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, Fu L, Wang G, et al., 2021, Using dual-polarization GPS antenna with optimized adaptive neuro-fuzzy inference system to improve single point positioning accuracy in urban canyons, NAVIGATION-JOURNAL OF THE INSTITUTE OF NAVIGATION, Vol: 68, Pages: 41-60, ISSN: 0028-1522
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- Citations: 8
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: 13
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: 8
Shang W, Chen Y, Ochieng W, 2020, A benchmark index for robustness analysis of multi-scale urban road networks, The 100th Transportation Research Board Annual Meeting
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, 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.
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.
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