ORCID Profile
0000-0002-6526-239X
Current Organisation
University of New South Wales
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Road Transportation and Freight Services | Transportation and Freight Services | Transport Planning | Operations Research | Urban and Regional Planning | Urban Design
ANZSRC Socio-Economic Objective (SEO)
Road Passenger Movements (excl. Public Transport) | Public Health (excl. Specific Population Health) not elsewhere classified | Road Safety | Road Freight | Urban Planning |
Related Links
Publications
A resource allocation problem to estimate network fundamental diagram in heterogeneous networks: Optimal locating of fixed measurement points and sampling of probe trajectories
Publisher: Elsevier BV
Date: 2018
Implementation and Evaluation of Weather-Responsive Traffic Management Strategies
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2396-11
Abstract: This study presents the development and application of methodologies to support weather-responsive traffic management (WRTM) strategies by building on traffic estimation and prediction system models. First, a systematic framework for implementing and evaluating WRTM strategies under severe weather conditions is developed. This framework includes activities for planning, preparing, and deploying WRTM strategies in three different time frames: long-term strategic planning, short-term tactical planning, and real-time traffic management center operations. Next, the evaluation of various strategies is demonstrated with locally calibrated network simulation-assignment model capabilities, and special-purpose key performance indicators are introduced. Three types of WRTM strategies [demand management, advisory and control variable message signs (VMSs), and incident management VMSs] are applied to multiple major U.S. areas, namely, Chicago, Illinois Salt Lake City, Utah and the Long Island area in New York. The analysis results illustrate the benefits of WRTM under inclement weather conditions and emphasize the importance of incorporating a predictive capability into selecting and deploying WRTM strategies.
Association between network characteristics and bicycle ridership across a large metropolitan region
Publisher: Center for Open Science
Date: 19-11-2021
Abstract: Background: Numerous studies have explored associations between bicycle network characteristics and bicycle ridership. However, the majority of these studies have been conducted in inner metropolitan regions and as such, there is limited knowledge on how various characteristics of bicycle networks relate to bicycle trips within and across entire metropolitan regions, and how the size and composition of study regions impact on the association between bicycle network characteristics and bicycle ridership.Methods: We conducted a retrospective analysis of household travel survey data and bicycle infrastructure in the Greater Melbourne region, Australia. Seven network metrics were calculated and Bayesian spatial models were used to explore the association between these network characteristics and bicycle ridership (measured as counts of the number of trips, and the proportion of all trips that were made by bike). Results: We demonstrated that bicycle ridership was associated with several network characteristics, and that these characteristics varied according to the outcome (count of the number of trips made by bike or the proportion of trips made by bike) and the size and characteristics of the study region.Conclusions: These findings challenge the utility of approaches based on spatially modelling network characteristics and bicycle ridership when informing the monitoring and evaluation of bicycle networks. There is a need to progress the science of measuring safe and connected bicycle networks for people of all ages and abilities.
The effect of variations in spatial units on unobserved heterogeneity in macroscopic crash models
Publisher: Elsevier BV
Date: 03-2017
Definition and Properties of Alternative Bus Service Reliability Measures at the Stop Level
Publisher: University of South Florida Libraries
Date: 03-2013
Modeling the airline hub location and optimal market problems with continuous approximation techniques
Publisher: Elsevier BV
Date: 06-2013
Understanding the impacts of a public transit disruption on bicycle sharing mobility patterns: A case of Tube strike in London
Publisher: Elsevier BV
Date: 2018
Vaccine allocation policy optimization and budget sharing mechanism using reinforcement learning
Publisher: Elsevier BV
Date: 02-2023
A macroscopic approach for calibration and validation of a modified social force model for bidirectional pedestrian streams
Publisher: Informa UK Limited
Date: 04-07-2019
Impact of Crime Statistics on Travel Mode Choice
Publisher: SAGE Publications
Date: 2015
DOI: 10.3141/2537-09
Abstract: Whether crime or the perception of it has any direct and significant influence on travelers’ mode choice is a topic for which the evidence remains inconclusive. Studies have revealed various, and in some cases counterintuitive, roles that safety concerns can play in in iduals’ travel behavior. In addition, characteristics of the physical environment such as land use and walkability are also influential factors in travelers’ decisions. This study explored these questions through the study of in idual travel behavior by using discrete choice models applied to the reported home-based work trips in the Chicago household travel survey. Mode choice was modeled as functions of variables such as sociodemographics, neighborhood crime density (as a safety measure), and walk score (as a measure of walkability). Different crime types were examined, and a crime index was introduced. Results suggest that both walk score and the crime index at the destination can be considered meaningful predictors of in iduals’ mode usage. The crime index at origin, however, does not show a significant and meaningful effect.
Congestion pricing practices and public acceptance: A review of evidence
Publisher: Elsevier BV
Date: 03-2018
Real-Time Traffic State Measurement Using Autonomous Vehicles Open Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
A Complex Network Methodology for Travel Demand Model Evaluation and Validation
Publisher: Springer Science and Business Media LLC
Date: 11-04-2018
Sensitivity-Based Linear Approximation Method to Estimate Time-Dependent Origin–Destination Demand in Congested Networks
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2669-08
Abstract: This paper presents a bi-level optimization problem to estimate offline time-dependent origin–destination (time-dependent O-D) demand on the basis of link flows and historical O-D matrices. The upper-level problem aimed to minimize the summation of errors in both traffic counts and O-D demand. Conventionally, O-D flows are linearly mapped to link flows with the assignment matrix proportions obtained from the dynamic traffic assignment, which is typically formulated as the lower-level problem. However, the linear relationship may be invalid when congestion builds up in the network, and a nonlinear relation between O-D flows and link flows may result. The nonlinearity may lead to a converged solution that is far from the global optimum. An accurate solution should be able to relax the linear assumption and to consider the effect of other O-D flows on the links’ traffic volumes. In this study, a solution method that relied on the sensitivity of assignment proportions to O-D flows was proposed and applied it required a number of further assignments. To overcome the extra computational requirement, a heuristic method to exclude the extra assignments and to improve the performance of the solution was proposed. The proposed algorithm was applied to multiple networks of varying sizes and congestion levels. The results demonstrated the efficiency of the proposed method for congested networks with less computation time.
Comparing Dynamic User Equilibrium and Noniterative Stochastic Route Choice in a Simulation-Based Dynamic Traffic Assignment Model: Practical Considerations for Large-Scale Networks
Publisher: Hindawi Limited
Date: 05-05-2021
DOI: 10.1155/2021/6667335
Abstract: Simulation-based dynamic traffic assignment (DTA) models play a vital role in transportation planning and operations. While the widely studied equilibrium-seeking DTA including dynamic user equilibrium (DUE) often provides robust and consistent outcomes, their expensive computational cost for large-scale network applications has been a burden in practice. The noniterative stochastic route choice (SRC) model, as a nonequilibrium seeking DTA model, provides an alternative for specific transportation operations applications that may not require equilibrium results after all (e.g., evacuation and major network disruptions) and thus tend to be computationally less expensive, yet may suffer from inconsistent outcomes. While DUE is a widely accepted approach for many strategic planning applications, SRC has been increasingly used in practice for traffic operations purposes. This paper aims to provide a comparative and quantitative analysis of the two modeling approaches. Specifically, a comparison has been made at two levels: link-level flows and network-level congestion patterns. Results suggest that adaptive driving improves the quality of the SRC solution, but its difference from DUE still remains significant at the link level. Results have practical implications for the application of large-scale simulation-based DTA models for planning and operations purposes.
Pedestrian crowd dynamics in merging sections: Revisiting the “faster-is-slower” phenomenon
Publisher: Elsevier BV
Date: 02-2018
Application of an exact gradient method to estimate dynamic origin-destination demand for melbourne network
Publisher: IEEE
Date: 11-2016
Calibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2391-09
Abstract: The weather-sensitive traffic estimation and prediction system (TrEPS) aims for accurate estimation and prediction of the traffic states under inclement weather conditions. Successful application of weather-sensitive TrEPS requires detailed calibration of weather effects on the traffic flow model. In this study, systematic procedures for the entire calibration process were developed, from data collection through model parameter estimation to model validation. After the development of the procedures, a dual-regime modified Greenshields model and weather adjustment factors were calibrated for four metropolitan areas across the United States (Irvine, California Chicago, Illinois Salt Lake City, Utah and Baltimore, Maryland) by using freeway loop detector traffic data and weather data from automated surface-observing systems stations. Observations showed that visibility and precipitation (rain–snow) intensity have significant impacts on the value of some parameters of the traffic flow models, such as free-flow speed and maximum flow rate, while these impacts can be included in weather adjustment factors. The calibrated models were used as input in a weather-integrated simulation system for dynamic traffic assignment. The results show that the calibrated models are capable of capturing the weather effects on traffic flow more realistically than TrEPS without weather integration.
Connecting Networkwide Travel Time Reliability and the Network Fundamental Diagram of Traffic Flow
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2391-08
Abstract: The existence of the network fundamental diagram (NFD) has been established at the urban network scale. It relates three traffic descriptors: speed, density, and flow. However, its deterministic nature does not convey the underlying variability within the network. In contrast, travel time reliability as a network performance descriptor is of growing concern to both the traveling public and traffic managers and policy makers. The objectives of this paper were to extend travel time reliability modeling from the link–path level to the network level and to connect overall network variability to NFD. Robust relationships between travel time variability and network density and flow rate were analytically derived, investigated, and validated with both simulated and real-world trajectory data. The distance-weighted standard deviation of travel time rate, as a measure of travel time variability, was found to increase monotonically with network density. A maximum network flow rate existed beyond which network travel time reliability deteriorated at a much faster pace. The results also suggest that these relationships are inherent network properties (signature) that are independent of demand level. The effects of en route information on the proposed relationships were also studied. The results showed that en route information reduced network travel time variability. The findings provide a strong connection between NFD and travel time variability, and this connection can be used further for modeling of network travel time reliability and assessment of measures intended to improve reliability of travel in a network.
Hysteresis and Capacity Drop Phenomena in Freeway Networks
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2391-05
Abstract: The objective of this study was to characterize hysteresis and capacity drop phenomena in freeway networks with the use of commonly available loop detector data from three networks: Chicago, Illinois Portland, Oregon and Irvine, California. For exploration of the effects of variations in network topology and size on the network fundamental diagram, a comparison was made by using the observed flow–occupancy diagrams of the selected freeway networks. The results provide further confirmation that findings from the literature for a limited number of networks are also valid for freeway networks not previously studied. Freeway networks have been found more likely to exhibit an inconsistent hysteretic pattern in shape and size that depends on the spatial distribution of congestion over the network. On the basis of empirical observations, hysteresis loops were characterized by their shape and size. Two shapes of hysteresis loops, H1 and H2, were identified and characterized. The size of each hysteresis loop was believed to be characterized by its width, height, and the area covered by the hysteresis loop. The authors postulated that the capacity drop phenomenon existed in freeway networks in a manner similar to that in in idual freeway sections. Two types of capacity drop were identified. Type 1 was associated with the inability of the freeway network to sustain its throughput at its peak value for a relatively long time, and therefore, capacity dropped while demand was still high and the network was loading. Type 2 was associated with the instability of network traffic when the network underwent reloading (e.g., afternoon peak period) after an incomplete recovery from the initial loading (e.g., morning peak period). In some cases, this reloading resulted in a lower capacity in the afternoon than in the morning. Empirical results showed that the observed phenomena were reproducible on different days and for different networks.
Revealing latent characteristics of mobility networks with coarse-graining
Publisher: Springer Science and Business Media LLC
Date: 17-05-2019
DOI: 10.1038/S41598-019-44005-9
Abstract: Previous theoretical and data-driven studies on urban mobility uncovered the repeating patterns in in idual and collective human behavior. This paper analyzes the travel demand characteristics of mobility networks through studying a coarse-grained representation of in idual trips. Building on the idea of reducing the complexity of the mobility network, we investigate the preserved spatial and temporal information in a simplified representations of large-scale origin-destination matrices derived from more than 16 million taxi trip records from New York and Chicago. We reduce the numerous in idual flows on the network into four major groups, to uncover latent collective mobility patterns in those cities. The new simplified representation of the origin-destination matrices leads to categorization of trips into distinctive flow types with specific temporal and spatial properties in each city under study. Collocation of the descriptive statistics of flow types within the two cities suggests the generalizability of the proposed approach. We extract an overall displacement metric from each of the major flows to analyze the evolution of their temporal attributes. The new representation of the demand network reveals insightful properties of the mobility system which could not have been identified from the original disaggregated representation.
Traffic assignment problem for footpath networks with bidirectional links
Publisher: Elsevier BV
Date: 11-2022
Pedestrian Crowd Dynamics Observed at Merging Sections: Impact of Designs on Movement Efficiency
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2622-05
Abstract: The need for reliable crowd simulation tools has necessitated an accurate understanding of human behavior and the rules that govern their movements under normal and emergency escapes. This paper investigates the dynamics of merging streams of pedestrians. In the merging sections, the interaction between pedestrians and geometric features of merging sections can significantly impede the collective motion and can increase the possibility of flow breakdown, particularly under emergency conditions. Therefore, to create safe and efficient designs, it is important to study human movement characteristics associated with these types of conflicting geometries. In this study, empirical data collected from large numbers of high-density experiments with people at different desired speed levels were used to explore the effect of different merging configurations (i.e., design and angle) on dynamics of merging crowds. For the first time, this study examined the impact of elevated speed regimes (as a behavioral proxy of emergency escapes) on the movement efficiency of crowds in merging sections with different geometric designs. In particular, this study investigated the impact of these conflicting geometric settings on the average waiting time in the system as a measure of movement efficiency. Results suggest that the experienced delay is dramatically greater in asymmetrical setups compared with the delay in symmetrical setups and that the difference is even more pronounced at elevated levels of pedestrians’ desired speed. These findings give significant insights into the implications of inefficient designs of merging sections for pedestrians’ safety, notably when quick movement of crowds is necessary (e.g., in emergencies).
Urban network gridlock: Theory, characteristics, and dynamics
Publisher: Elsevier BV
Date: 11-2013
Capacity allocation and tolling-rewarding schemes for the morning commute with carpooling
Publisher: Elsevier BV
Date: 09-2022
Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran
Publisher: Cold Spring Harbor Laboratory
Date: 06-05-2020
DOI: 10.1101/2020.05.02.20087270
Abstract: Iran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020. We developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay-adjusted case fatality ratio based on the distribution of the delay from hospitalization-to-death. Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60 – 1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available. The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak. Nil.
Exploring Areawide Dynamics of Pedestrian Crowds
Publisher: SAGE Publications
Date: 2014
DOI: 10.3141/2421-04
A systematic scoping review of methods for estimating link-level bicycling volumes
Publisher: Informa UK Limited
Date: 16-11-2022
Developing urban biking typologies: quantifying the complex interactions of bicycle ridership, bicycle network and built environment characteristics
Publisher: Center for Open Science
Date: 25-11-2021
Abstract: Background: Extensive research has been conducted exploring associations of built environment characteristics and biking. However, these approaches have often lacked the ability to understanding the interactions of built environment, population and bicycle ridership. To overcome these limitations, this study aimed to develop novel urban biking typologies using unsupervised machine learning methods.Methods: We conducted a retrospective analysis of travel surveys, bicycle infrastructure and population and land use characteristics in the Greater Melbourne region, Australia. To develop the urban biking typology, we used a k-medoids clustering method.Results: Analyses revealed 5 clusters. We highlight areas with high bicycle network density and a high proportion of trips made by bike (Cluster 1 reflecting 12% of the population of Greater Melbourne, but 57% of all bike trips) and areas with high off-road and on-road bicycle network length, but a low proportion of trips made by bike (Cluster 4, reflecting 23% of the population of Greater Melbourne and 13% of all bike trips).Conclusion: Our novel approach to developing an urban biking typology enabled the exploration of the interaction of bicycle ridership, bicycle network, population and land use characteristics. Such approaches are important in advancing our understanding of bicycling behaviour, but further research is required to understand the generalisability of these findings to other settings.
Activity-Based Model with Dynamic Traffic Assignment and Consideration of Heterogeneous User Preferences and Reliability Valuation
Publisher: SAGE Publications
Date: 2015
DOI: 10.3141/2493-09
Abstract: To forecast the impact of congestion pricing schemes, it is essential to capture user responses to these schemes and the resulting dynamics of traffic flow on the network. The responses of users must include route, departure time, and mode choices. To capture the effects of these decisions, this paper lays out a framework for the integration of the relevant elements of an activity-based model (ABM) with a dynamic traffic assignment (DTA) model and a simulation framework to support the analysis and evaluation of various pricing schemes. In this paper, a multicriterion dynamic user equilibrium traffic assignment model is used the model explicitly considers heterogeneous users who seek to minimize travel time, out-of-pocket cost, and travel time reliability in the underlying route choice framework. In addition to the methodological developments, various demand and supply parameters are estimated and calibrated for the selected application network (the Greater Chicago, Illinois, network). This paper showcases the integration of ABM components and a DTA in one coherent modeling framework for the implementation and evaluation of congestion pricing in an actual large-scale network.
Mapping Urban Environmental Performance with Emerging Data Sources: A Case of Urban Greenery and Traffic Noise in Sydney, Australia
Publisher: MDPI AG
Date: 10-01-2021
DOI: 10.3390/SU13020605
Abstract: Measuring urban environmental performance supports understanding and improving the livability and sustainability of a city. Creating a more livable and attractive environment facilitates a greater shift to active and greener transport modes. Two key aspects, among many others, that determine the environmental performance of an urban area are greenery and noise. This study aims to map street-level greenery and traffic noise using emerging data sources including crowd-sourced mobile phone-based data and street-level imagery data in Sydney, Australia. Results demonstrate the applicability of emerging data sources and the presented advanced techniques in capturing the seasonal variations in urban greenery and time-dependent nature of traffic noise. Results also confirm the presence of a negative correlation between urban greenery and traffic noise.
Macroscopic modeling of pedestrian and bicycle crashes: A cross-comparison of estimation methods
Publisher: Elsevier BV
Date: 08-2016
DOI: 10.1016/J.AAP.2016.05.001
Abstract: The paper presents a cross-comparison of different estimation methods to model pedestrian and bicycle crashes. The study contributes to macro level safety studies by providing further methodological and empirical evidence on the various factors that influence the frequency of pedestrian and bicycle crashes at the planning level. Random parameter negative binomial (RPNB) models are estimated to explore the effects of various planning factors associated with total, serious injury and minor injury crashes while accounting for unobserved heterogeneity. Results of the RPNB models were compared with the results of a non-spatial negative binomial (NB) model and a Poisson-Gamma-CAR model. Key findings are, (1) the RPNB model performed best with the lowest mean absolute deviation, mean squared predicted error and Akaiki information criterion measures and (2) signs of estimated parameters are consistent if these variables are significant in models with the same response variables. We found that vehicle kilometers traveled (VKT), population, percentage of commuters cycling or walking to work, and percentage of households without motor vehicles have a significant and positive correlation with the number of pedestrian and bicycle crashes. Mixed land use is also found to have a positive association with the number of pedestrian and bicycle crashes. Results have planning and policy implications aimed at encouraging the use of sustainable modes of transportation while ensuring the safety of pedestrians and cyclist.
A solution to the road network design problem for multimodal flow
Publisher: IEEE
Date: 11-2016
A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks
Publisher: Springer Science and Business Media LLC
Date: 14-05-2016
An Open GMNS Dataset of a Dynamic Multi-Modal Transportation Network Model of Melbourne, Australia
Publisher: MDPI AG
Date: 19-02-2021
DOI: 10.3390/DATA6020021
Abstract: Simulation-based dynamic traffic assignment models are increasingly used in urban transportation systems analysis and planning. They replicate traffic dynamics across transportation networks by capturing the complex interactions between travel demand and supply. However, their applications particularly for large-scale networks have been hindered by the challenges associated with the collection, parsing, development, and sharing of data-intensive inputs. In this paper, we develop and share an open dataset for reproduction of a dynamic multi-modal transportation network model of Melbourne, Australia. The dataset is developed consistently with the General Modeling Network Specification (GMNS), enabling software-agnostic human and machine readability. GMNS is a standard readable format for sharing routable transportation network data that is designed to be used in multimodal static and dynamic transportation operations and planning models.
Delay Variability Optimization Using Shockwave Theory at an Undersaturated Intersection
Publisher: Elsevier BV
Date: 07-2017
A big data approach for clustering and calibration of link fundamental diagrams for large-scale network simulation applications
Publisher: Elsevier BV
Date: 09-2018
Calibration and validation of a simulation-based dynamic traffic assignment model for a large-scale congested network
Publisher: Elsevier BV
Date: 08-2018
Insights Toward Characteristics of Merging Streams of Pedestrian Crowds Based on Experiments with Panicked Ants
Publisher: SAGE Publications
Date: 2016
DOI: 10.3141/2561-10
Abstract: Geometric design of egress and ingress configurations affects collective movement of pedestrians. Merging streams of pedestrian crowds is, in particular, one of the frequently observed features in public infrastructures and mass gatherings. However, few qualitative and quantitative studies have addressed this phenomenon in emergency situations because of the scarcity of data on human panic conditions. This paper studies the underlying geometric factors that affect dynamics and flow characteristics of merging streams in panic conditions through the use of nonhuman entities. Many experiments with panicked ants were performed in different angles and geometric characteristics. Flow rates, headway distributions, and escape speed of merging streams were studied. Results suggest that merging layouts can lead to the creation of stop-and-go phenomena and cause significant variation in the velocities of the joining paths over time. The authors also found that setups with tributary merging paths, in which a deviated stream joins a main branch, performed poorly compared with equivalent symmetrical setups. In addition, results show a dependency between traffic flow characteristics of the merged flow and the merging angle. Analyses also suggest nonexistence of a monotonic relation (or trend) between the merging angle and the merging throughput. This outcome specifically highlights the possibility of the presence of certain merging angles below and above which the overall flow performance is poorer (i.e., optimal angles). The findings provide a better understanding of the macroscopic characteristics of escaping flows in merging sections.
Continuous Approximation Model for the Vehicle Routing Problem for Emissions Minimization at the Strategic Level
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2012
Dynamic pedestrian traffic assignment with link transmission model for bidirectional sidewalk networks
Publisher: Elsevier BV
Date: 12-2022
Dynamics of Urban Network Traffic flow during a Large-Scale Evacuation
Publisher: SAGE Publications
Date: 2014
DOI: 10.3141/2422-03
Estimating Network Fundamental Diagram Using Three-Dimensional Vehicle Trajectories
Publisher: SAGE Publications
Date: 2014
DOI: 10.3141/2422-02
A Complex Network Analysis of Macroscopic Structure of Taxi Trips
Publisher: Elsevier BV
Date: 07-2017
Optimal distance- and time-dependent area-based pricing with the Network Fundamental Diagram
Publisher: Elsevier BV
Date: 10-2018
Exploring Properties of Networkwide Flow–Density Relations in a Freeway Network
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2315-16
Abstract: The objective of this study is to investigate the properties of network-level traffic flow relationships in a freeway network with the use of commonly available loop detector data. The impact of the spatial and temporal distribution of congestion in a selected network on the shape and properties of the flow–density relation is investigated, with emphasis on the formation and characterization of hysteresis patterns. Accordingly, a path-dependent characterization of hysteresis patterns in freeway networks is introduced and illustrated conceptually as well as through empirical observations. Comparison of the spatial and temporal distribution of congestion throughout a selected subnetwork on different days suggests a relationship between the size of the hysteresis loop and the inhomogeneity of the traffic distribution. The maximum network average flow is not a constant value but varies across different days. In addition, for the same value of average network occupancy, the variation of occupancy is higher during the recovery period compared with the loading period. The observed large variation in network occupancy during recovery implies the formation of fragmented queues and traffic instability. A chaotic pattern is also to be expected in the networkwide flow–occupancy plane when the spatial distribution of link densities is inhomogeneous and the average network occupancy remains consistently high and roughly unchanged for successive time intervals. Overall, the study results provide a deeper understanding of the properties of networkwide relations on freeway networks.
Measuring housing and transportation affordability: A case study of Melbourne, Australia
Publisher: Elsevier BV
Date: 12-2017
Spatial fluctuations of pedestrian velocities in bidirectional streams: Exploring the effects of self-organization
Publisher: Elsevier BV
Date: 09-2015
Calibration of traffic flow fundamental diagrams for network simulation applications: A two-stage clustering approach
Publisher: IEEE
Date: 11-2016
Analytical derivation of the optimal traffic signal timing: Minimizing delay variability and spillback probability for undersaturated intersections
Publisher: Elsevier BV
Date: 2019
Network capacity, traffic instability, and adaptive driving: findings from simulated urban network experiments
Publisher: Elsevier BV
Date: 10-2015
Understanding the Lived Experiences of Housing and Transport Stress in the “Affordable” Outer Ring: A Case Study of Melbourne, Australia
Publisher: Informa UK Limited
Date: 18-03-2021
Macroscopic dynamics and the collapse of urban traffic
Publisher: Proceedings of the National Academy of Sciences
Date: 10-12-2018
Abstract: Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the in idual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ , defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.
Calibration of the intelligent driver model (IDM) with adaptive parameters for mixed autonomy traffic using experimental trajectory data
Publisher: Informa UK Limited
Date: 08-12-2021
A Big Data Approach for Clustering and Calibration of Link Fundamental Diagrams for Large-Scale Network Simulation Applications
Publisher: Elsevier BV
Date: 2017
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