Multiscale identification of emergent and future conditions along corridors of transportation networks

Thorisson, Heimir; Lambert, James H.

doi:10.1016/j.ress.2017.06.005

Cited by 24 publications

(10 citation statements)

References 22 publications

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“…Identifying all possible sources of risk a system is exposed to is impossible and thus the resulting disruption potentials are not fully comprehensive. To balance this limitation, techniques such as risk identification using hierarchical holographic modeling, and risk filtering and ranking are helpful to prioritize which sources of risk should be included in the analysis. Second, stakeholders might disagree on definition of activities, inputs, and controls.…”

Section: Discussionmentioning

confidence: 99%

Addressing schedule disruptions in business processes of advanced logistics systems

Thorisson

Alsultan

Hendrickson³

et al. 2018

Systems Engineering

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Large-scale logistics systems operate under uncertainties of schedule, cost, environmental impacts, reliability, and others rendering it critical for system operations to consider emergent and future conditions involving markets, technologies, environment, and organizations. Business process modeling is used widely to document the activities of an enterprise. Successful analysis of business processes requires explicit accounting for and evaluation of sources of potential disruptive risk. Previous research in the journal integrated risk identification to business process models. This paper creates a framework that evaluates the schedule disruption potential of identified sources of risk in logistics systems with the modeling of the associated business processes. The framework is demonstrated on a scheduling process at a marine container port. The methods first described in this paper should be integrated to software applications that diagram and analyze business processes of large-scale systems. K E Y W O R D Sbusiness process modeling, enterprise systems, risk assessment, risk communication, scenario analysis, scheduling

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Section: Discussionmentioning

confidence: 99%

Addressing schedule disruptions in business processes of advanced logistics systems

Thorisson

Alsultan

Hendrickson³

et al. 2018

Systems Engineering

Self Cite

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“…The research in this cluster is aiming at enhancing decision-making processes and increasing the efficiency of Innovations in freight transport energy consumption in order to reduce environmental impact. Transport systems, road networks and overall freight transport operations are included in this cluster, along with their effects on efficiency and risk management (Thorisson and Lambert, 2017). As a result of engineering, analysis, impact assessment and continuous monitoring, the level of transport operations can be improved, resources can be well-utilised and efficiency can be enhanced.…”

Section: Innovations In Freight Transportmentioning

confidence: 99%

Innovations in freight transport: a systematic literature evaluation and COVID implications

Mavi

Olaru

et al. 2022

IJLM

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PurposeThis paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.Design/methodology/approachQualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.FindingsThe RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.Research limitations/implicationsGiven the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.Originality/valueThis paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.

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“…Risk is often conceptualized as the convergence of hazard intensity, exposure, and vulnerability. In the context of transportation corridors, hazard intensity can be represented by the volume-to-capacity ratio of the roadway; exposure by the average daily traffic; and vulnerability by the condition of the roadway (Thorisson & Lambert, 2017). It is unlikely that each driver has memorized the probability of crash events or calculated quantifiable risk for each road segment traveled.…”

Section: Measuring Cognitive Loadmentioning

confidence: 99%

Cognitive Load Variability from Road Characteristics Should Influence a Safety Requirement for Vehicle Stopping Sight Distance

Pennetti

Hollenback

Kim

et al. 2019

Proceedings of the Human Factors and Ergonomics Society Annual

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Current U.S. geometric road design standards are based on a prescribed value for a driver’s perception-reaction time (a constant value of 2.5 seconds), which represents the time necessary for a driver to safely stop the vehicle to avoid a crash (referred to as a stopping sight distance); however, these standards fail to consider how road complexity, driver risk perception, and visual stimuli can influence perception-reaction time. With over a million vehicle fatalities a year (WHO, n.d.), it is necessary to investigate methods of improving driver safety. The influence of road characteristics is considered with some road design policies, but not currently applied to stopping sight distance. This paper introduces theoretical considerations for increasing perception-reaction time (and thereby adjusting speed limits or road geometry) based on roadway complexity (volume of vehicles, road geometry, pedestrian crossings, frequency of adverse weather conditions, or other conditions).

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Multiscale identification of emergent and future conditions along corridors of transportation networks

Cited by 24 publications

References 22 publications

Addressing schedule disruptions in business processes of advanced logistics systems

Addressing schedule disruptions in business processes of advanced logistics systems

Innovations in freight transport: a systematic literature evaluation and COVID implications

Cognitive Load Variability from Road Characteristics Should Influence a Safety Requirement for Vehicle Stopping Sight Distance

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