Recent advancements in network science showed that the topological credentials of the elements (i... more Recent advancements in network science showed that the topological credentials of the elements (i.e., links) in a network carry important implications. Likewise, roadway segments (i.e., links) in a road network should be assessed based on their network position along with traffic conditions at a given geographic scale. The goal of this study is to present a framework that can identify and select critical links in a road network based on their topological importance such as centrality, and the effects of systematic interventions conducted on such links in improving overall system performance (vehicle delay, travel time) to provide an adequate level of service (LOS). A real-world road network (Boise downtown) is investigated by applying lane interventions on roadways experiencing high congestion. Microscopic traffic simulation and analyses are conducted to estimate the traffic flow parameters hence the performance of the road segments. The findings of this study show that interventions applied to critical and congested road segments improve the serviceability from LOS F to LOS E as well as from LOS D to LOS C. Besides, reduced travel time and vehicular delay (after applying intervention on critical components) are also observed for high demand OD pairs of the road network. As such the proposed framework has the potential to incorporate the topological credentials with traffic flow parameters and improve the performance of the road network. This systematic approach will help traffic managers and practitioners to develop strategies that enhance road network performance.
Sustainability aspects of transportation infrastructure systems primarily focus on system perform... more Sustainability aspects of transportation infrastructure systems primarily focus on system performance based on environmental, social, and economic impacts. In contrast, resilience aspects demonstrate the ability to withstand external shocks i.e. robustness as well as to recover from the loss of functionality due to such disruptions i.e. rapidity. Therefore, sustainability and resilience are two key aspects which should be given adequate attention during the planning, design, construction, operations, and maintenance phases of any civil infrastructure system. As both concepts are equally important to sustain an infrastructure for a longer duration, their concurrent assessments within a unified framework are highly desirable. While there has been a recent focus towards solving this dilemma, review of existing studies revealed the lack of such unifying frameworks that can quantify sustainability and resilience indicators to simultaneously assess system performance. Moreover, a single decision or performance indicator could reinforce one and undermine another. As such, this study proposed a forward-looking unification framework, where the sustainability and resilience of transportation infrastructure systems can be analyzed simultaneously. In this regard, the proposed unifying framework is explained using seven critical indicators including emission, speed, temperature, energy consumption, delay, mobility, and accessibility. This study also investigates the interdependencies, relationships, and tradeoffs between sustainability and resilience based on these indices. While some indices would help the system to attain both at the same time, they are compromised in some cases. Finally, the study identifies immediate research needs as well as the ones in the long-term.
Exploring the Interdependencies Between Transportation and Stormwater Networks: The Case of Norman, Oklahoma
Transportation Research Record: Journal of the Transportation Research Board
The significance of critical infrastructure systems in maintaining productivity is undeniable. Ho... more The significance of critical infrastructure systems in maintaining productivity is undeniable. However, such systems remain susceptible to external disturbances and cascading failures. Instead of operating independently, these physical systems, such as transportation and stormwater systems, form an interdependent system. This interdependence, particularly important during flooding, illustrates that the failure of a stormwater system can disrupt traffic networks. To explore the extent of such interdependency, this study investigates the transportation and stormwater networks in Norman, Oklahoma. Using network science theories and concepts of multilayered networks, this paper analyzes these systems, both individually and in combination. The study identifies closely located components in the road and stormwater networks using Moran's I spatial autocorrelation metric. Next, the connectivity of these networks is represented in a graph format to investigate the topological credentials...
H-CTM for simulating non-lane-based heterogeneous traffic
Transportation Letters: The International Journal of Transportation Research, Sep 6, 2017
Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous ... more Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous cell transmission model) based on basic cell transmission model (CTM). The methodological calibration of the model considers the aggregate behavior of heterogeneous traffic under weak lane discipline. H-CTM incorporates a nonlinear fundamental diagram (FD), modeled for non-lane-based heterogeneous traffic, instead of traditional piecewise linear FD. For validating the model performance, high resolution traffic data were collected from a major arterial roadway (N3-Highway) of Dhaka city covering both peak and off-peak periods. Subsequently, the calibrated FD parameters were incorporated in the newly developed H-CTM to simulate the traffic. The estimated traffic states by the proposed model were then compared with basic model of CTM. Model performances, calculated in terms of mean absolute error based on ground truth values show that the H-CTM can be used to describe the traffic dynamics in the stated traffic system better than the basic model.
Identifying Crisis Response Communities in Online Social Networks for Compound Disasters: The Case of Hurricane Laura and COVID-19
Transportation Research Record: Journal of the Transportation Research Board
Online social networks allow different agencies and the public to interact and share the underlyi... more Online social networks allow different agencies and the public to interact and share the underlying risks and protective actions during major disasters. This study revealed such crisis communication patterns during Hurricane Laura compounded by the COVID-19 pandemic. Hurricane Laura was one of the strongest (Category 4) hurricanes on record to make landfall in Cameron, Louisiana, U.S. Using an application programming interface (API), this study utilizes large-scale social media data obtained from Twitter through the recently released academic track that provides complete and unbiased observations. The data captured publicly available tweets shared by active Twitter users from the vulnerable areas threatened by Hurricane Laura. Online social networks were based on Twitter’s user influence feature (i.e., mentions or tags) that allows notification of other users while posting a tweet. Using network science theories and advanced community detection algorithms, the study split these netw...
Risk communication in times of disasters is complex, involving rapid and diverse communication in... more Risk communication in times of disasters is complex, involving rapid and diverse communication in social networks (i.e. public and/or private agencies; local residents) as well as limited mobilization capacity and operational constraints of physical infrastructure networks. Despite a growing literature on infrastructure interdependencies and co-dependent social-physical systems, an in-depth understanding of how risk communication in online social networks weighs into physical infrastructure networks during a major disaster remains limited, let alone in compounding risk events. This study analyzes large-scale datasets of crisis mobility and activity-related social interactions and concerns available through social media (Twitter) for communities that were impacted by an ice storm (Oct. 2020) in Oklahoma. Compounded by the COVID-19 pandemic, Oklahoma residents faced this historic ice storm (Oct. 26, 2020-Oct. 29, 2020) that caused devastating traffic impacts (among others) due to excessive ice accumulation. By using Twitter's recently released academic Application Programming Interface (API) that provides complete and unbiased data, geotagged tweets (~210K) were collected covering the entire state of Oklahoma and ice storm related tweets (~14.2K) were considered. First, the study uses natural language processing and text quantification techniques to translate crisis narratives (i.e. tweets). Next, geotagged tweets are mapped into co-located road networks using traditional GIS techniques. Finally, insights are generated using network science theories and quantified social narratives to interpret different elements of road networks (e.g. local roads, freeways, etc.) for the Oklahoma communities that were impacted by the ice storm event during the pandemic.
Recent advancements in network science showed that the topological credentials of the elements (i... more Recent advancements in network science showed that the topological credentials of the elements (i.e., links) in a network carry important implications. Likewise, roadway segments (i.e., links) in a road network should be assessed based on their network position along with traffic conditions at a given geographic scale. The goal of this study is to present a framework that can identify and select critical links in a road network based on their topological importance such as centrality, and the effects of systematic interventions conducted on such links in improving overall system performance (vehicle delay, travel time) to provide an adequate level of service (LOS). A real-world road network (Boise downtown) is investigated by applying lane interventions on roadways experiencing high congestion. Microscopic traffic simulation and analyses are conducted to estimate the traffic flow parameters hence the performance of the road segments. The findings of this study show that intervention...
Sustainability aspects of transportation infrastructure systems primarily focus on system perform... more Sustainability aspects of transportation infrastructure systems primarily focus on system performance based on environmental, social, and economic impacts. In contrast, resilience aspects demonstrate the ability to withstand external shocks i.e. robustness as well as to recover from the loss of functionality due to such disruptions i.e. rapidity. Therefore, sustainability and resilience are two key aspects which should be given adequate attention during the planning, design, construction, operations, and maintenance phases of any civil infrastructure system. As both concepts are equally important to sustain an infrastructure for a longer duration, their concurrent assessments within a unified framework are highly desirable. While there has been a recent focus towards solving this dilemma, review of existing studies revealed the lack of such unifying frameworks that can quantify sustainability and resilience indicators to simultaneously assess system performance. Moreover, a single decision or performance indicator could reinforce one and undermine another. As such, this study proposed a forward-looking unification framework, where the sustainability and resilience of transportation infrastructure systems can be analyzed simultaneously. In this regard, the proposed unifying framework is explained using seven critical indicators including emission, speed, temperature, energy consumption, delay, mobility, and accessibility. This study also investigates the interdependencies, relationships, and tradeoffs between sustainability and resilience based on these indices. While some indices would help the system to attain both at the same time, they are compromised in some cases. Finally, the study identifies immediate research needs as well as the ones in the long-term.
H-CTM for simulating non-lane-based heterogeneous traffic
Transportation Letters, 2017
Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous ... more Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous cell transmission model) based on basic cell transmission model (CTM). The methodological calibration of the model considers the aggregate behavior of heterogeneous traffic under weak lane discipline. H-CTM incorporates a nonlinear fundamental diagram (FD), modeled for non-lane-based heterogeneous traffic, instead of traditional piecewise linear FD. For validating the model performance, high resolution traffic data were collected from a major arterial roadway (N3-Highway) of Dhaka city covering both peak and off-peak periods. Subsequently, the calibrated FD parameters were incorporated in the newly developed H-CTM to simulate the traffic. The estimated traffic states by the proposed model were then compared with basic model of CTM. Model performances, calculated in terms of mean absolute error based on ground truth values show that the H-CTM can be used to describe the traffic dynamics in the stated traffic system better than the basic model.
A Comparative Study of Operational Performance of Bangladesh Railway with Selected Regional Countries and Its Present Constraints, Potentials & Future Prospects
Recent advancements in network science showed that the topological credentials of the elements (i... more Recent advancements in network science showed that the topological credentials of the elements (i.e., links) in a network carry important implications. Likewise, roadway segments (i.e., links) in a road network should be assessed based on their network position along with traffic conditions at a given geographic scale. The goal of this study is to present a framework that can identify and select critical links in a road network based on their topological importance such as centrality, and the effects of systematic interventions conducted on such links in improving overall system performance (vehicle delay, travel time) to provide an adequate level of service (LOS). A real-world road network (Boise downtown) is investigated by applying lane interventions on roadways experiencing high congestion. Microscopic traffic simulation and analyses are conducted to estimate the traffic flow parameters hence the performance of the road segments. The findings of this study show that interventions applied to critical and congested road segments improve the serviceability from LOS F to LOS E as well as from LOS D to LOS C. Besides, reduced travel time and vehicular delay (after applying intervention on critical components) are also observed for high demand OD pairs of the road network. As such the proposed framework has the potential to incorporate the topological credentials with traffic flow parameters and improve the performance of the road network. This systematic approach will help traffic managers and practitioners to develop strategies that enhance road network performance.
Sustainability aspects of transportation infrastructure systems primarily focus on system perform... more Sustainability aspects of transportation infrastructure systems primarily focus on system performance based on environmental, social, and economic impacts. In contrast, resilience aspects demonstrate the ability to withstand external shocks i.e. robustness as well as to recover from the loss of functionality due to such disruptions i.e. rapidity. Therefore, sustainability and resilience are two key aspects which should be given adequate attention during the planning, design, construction, operations, and maintenance phases of any civil infrastructure system. As both concepts are equally important to sustain an infrastructure for a longer duration, their concurrent assessments within a unified framework are highly desirable. While there has been a recent focus towards solving this dilemma, review of existing studies revealed the lack of such unifying frameworks that can quantify sustainability and resilience indicators to simultaneously assess system performance. Moreover, a single decision or performance indicator could reinforce one and undermine another. As such, this study proposed a forward-looking unification framework, where the sustainability and resilience of transportation infrastructure systems can be analyzed simultaneously. In this regard, the proposed unifying framework is explained using seven critical indicators including emission, speed, temperature, energy consumption, delay, mobility, and accessibility. This study also investigates the interdependencies, relationships, and tradeoffs between sustainability and resilience based on these indices. While some indices would help the system to attain both at the same time, they are compromised in some cases. Finally, the study identifies immediate research needs as well as the ones in the long-term.
Exploring the Interdependencies Between Transportation and Stormwater Networks: The Case of Norman, Oklahoma
Transportation Research Record: Journal of the Transportation Research Board
The significance of critical infrastructure systems in maintaining productivity is undeniable. Ho... more The significance of critical infrastructure systems in maintaining productivity is undeniable. However, such systems remain susceptible to external disturbances and cascading failures. Instead of operating independently, these physical systems, such as transportation and stormwater systems, form an interdependent system. This interdependence, particularly important during flooding, illustrates that the failure of a stormwater system can disrupt traffic networks. To explore the extent of such interdependency, this study investigates the transportation and stormwater networks in Norman, Oklahoma. Using network science theories and concepts of multilayered networks, this paper analyzes these systems, both individually and in combination. The study identifies closely located components in the road and stormwater networks using Moran's I spatial autocorrelation metric. Next, the connectivity of these networks is represented in a graph format to investigate the topological credentials...
H-CTM for simulating non-lane-based heterogeneous traffic
Transportation Letters: The International Journal of Transportation Research, Sep 6, 2017
Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous ... more Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous cell transmission model) based on basic cell transmission model (CTM). The methodological calibration of the model considers the aggregate behavior of heterogeneous traffic under weak lane discipline. H-CTM incorporates a nonlinear fundamental diagram (FD), modeled for non-lane-based heterogeneous traffic, instead of traditional piecewise linear FD. For validating the model performance, high resolution traffic data were collected from a major arterial roadway (N3-Highway) of Dhaka city covering both peak and off-peak periods. Subsequently, the calibrated FD parameters were incorporated in the newly developed H-CTM to simulate the traffic. The estimated traffic states by the proposed model were then compared with basic model of CTM. Model performances, calculated in terms of mean absolute error based on ground truth values show that the H-CTM can be used to describe the traffic dynamics in the stated traffic system better than the basic model.
Identifying Crisis Response Communities in Online Social Networks for Compound Disasters: The Case of Hurricane Laura and COVID-19
Transportation Research Record: Journal of the Transportation Research Board
Online social networks allow different agencies and the public to interact and share the underlyi... more Online social networks allow different agencies and the public to interact and share the underlying risks and protective actions during major disasters. This study revealed such crisis communication patterns during Hurricane Laura compounded by the COVID-19 pandemic. Hurricane Laura was one of the strongest (Category 4) hurricanes on record to make landfall in Cameron, Louisiana, U.S. Using an application programming interface (API), this study utilizes large-scale social media data obtained from Twitter through the recently released academic track that provides complete and unbiased observations. The data captured publicly available tweets shared by active Twitter users from the vulnerable areas threatened by Hurricane Laura. Online social networks were based on Twitter’s user influence feature (i.e., mentions or tags) that allows notification of other users while posting a tweet. Using network science theories and advanced community detection algorithms, the study split these netw...
Risk communication in times of disasters is complex, involving rapid and diverse communication in... more Risk communication in times of disasters is complex, involving rapid and diverse communication in social networks (i.e. public and/or private agencies; local residents) as well as limited mobilization capacity and operational constraints of physical infrastructure networks. Despite a growing literature on infrastructure interdependencies and co-dependent social-physical systems, an in-depth understanding of how risk communication in online social networks weighs into physical infrastructure networks during a major disaster remains limited, let alone in compounding risk events. This study analyzes large-scale datasets of crisis mobility and activity-related social interactions and concerns available through social media (Twitter) for communities that were impacted by an ice storm (Oct. 2020) in Oklahoma. Compounded by the COVID-19 pandemic, Oklahoma residents faced this historic ice storm (Oct. 26, 2020-Oct. 29, 2020) that caused devastating traffic impacts (among others) due to excessive ice accumulation. By using Twitter's recently released academic Application Programming Interface (API) that provides complete and unbiased data, geotagged tweets (~210K) were collected covering the entire state of Oklahoma and ice storm related tweets (~14.2K) were considered. First, the study uses natural language processing and text quantification techniques to translate crisis narratives (i.e. tweets). Next, geotagged tweets are mapped into co-located road networks using traditional GIS techniques. Finally, insights are generated using network science theories and quantified social narratives to interpret different elements of road networks (e.g. local roads, freeways, etc.) for the Oklahoma communities that were impacted by the ice storm event during the pandemic.
Recent advancements in network science showed that the topological credentials of the elements (i... more Recent advancements in network science showed that the topological credentials of the elements (i.e., links) in a network carry important implications. Likewise, roadway segments (i.e., links) in a road network should be assessed based on their network position along with traffic conditions at a given geographic scale. The goal of this study is to present a framework that can identify and select critical links in a road network based on their topological importance such as centrality, and the effects of systematic interventions conducted on such links in improving overall system performance (vehicle delay, travel time) to provide an adequate level of service (LOS). A real-world road network (Boise downtown) is investigated by applying lane interventions on roadways experiencing high congestion. Microscopic traffic simulation and analyses are conducted to estimate the traffic flow parameters hence the performance of the road segments. The findings of this study show that intervention...
Sustainability aspects of transportation infrastructure systems primarily focus on system perform... more Sustainability aspects of transportation infrastructure systems primarily focus on system performance based on environmental, social, and economic impacts. In contrast, resilience aspects demonstrate the ability to withstand external shocks i.e. robustness as well as to recover from the loss of functionality due to such disruptions i.e. rapidity. Therefore, sustainability and resilience are two key aspects which should be given adequate attention during the planning, design, construction, operations, and maintenance phases of any civil infrastructure system. As both concepts are equally important to sustain an infrastructure for a longer duration, their concurrent assessments within a unified framework are highly desirable. While there has been a recent focus towards solving this dilemma, review of existing studies revealed the lack of such unifying frameworks that can quantify sustainability and resilience indicators to simultaneously assess system performance. Moreover, a single decision or performance indicator could reinforce one and undermine another. As such, this study proposed a forward-looking unification framework, where the sustainability and resilience of transportation infrastructure systems can be analyzed simultaneously. In this regard, the proposed unifying framework is explained using seven critical indicators including emission, speed, temperature, energy consumption, delay, mobility, and accessibility. This study also investigates the interdependencies, relationships, and tradeoffs between sustainability and resilience based on these indices. While some indices would help the system to attain both at the same time, they are compromised in some cases. Finally, the study identifies immediate research needs as well as the ones in the long-term.
H-CTM for simulating non-lane-based heterogeneous traffic
Transportation Letters, 2017
Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous ... more Abstract This paper developed a first-order deterministic macroscopic model H-CTM (heterogeneous cell transmission model) based on basic cell transmission model (CTM). The methodological calibration of the model considers the aggregate behavior of heterogeneous traffic under weak lane discipline. H-CTM incorporates a nonlinear fundamental diagram (FD), modeled for non-lane-based heterogeneous traffic, instead of traditional piecewise linear FD. For validating the model performance, high resolution traffic data were collected from a major arterial roadway (N3-Highway) of Dhaka city covering both peak and off-peak periods. Subsequently, the calibrated FD parameters were incorporated in the newly developed H-CTM to simulate the traffic. The estimated traffic states by the proposed model were then compared with basic model of CTM. Model performances, calculated in terms of mean absolute error based on ground truth values show that the H-CTM can be used to describe the traffic dynamics in the stated traffic system better than the basic model.
A Comparative Study of Operational Performance of Bangladesh Railway with Selected Regional Countries and Its Present Constraints, Potentials & Future Prospects
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