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J.P.T. van der Gun
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14 records found
1
Journal article
(2020)
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Jeroen P.T. van der Gun, Adam J. Pel, Bart van Arem
By extending static traffic assignment with explicit capacity constraints, quasi-dynamic traffic assignment yields more realistic results while avoiding many disadvantages of a dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models. We formulate and check requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We demonstrate that existing approaches for travel time computation in the literature fail to satisfy all requirements and derive a new link travel time formula from the vertical queuing theory that does meet all requirements. We discuss expected changes to assignment results and methodological advantages for pathfinding and model extensions, including horizontal queuing. The new link travel time formulation is finally applied to three example scenarios from literature.
...
By extending static traffic assignment with explicit capacity constraints, quasi-dynamic traffic assignment yields more realistic results while avoiding many disadvantages of a dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models. We formulate and check requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We demonstrate that existing approaches for travel time computation in the literature fail to satisfy all requirements and derive a new link travel time formula from the vertical queuing theory that does meet all requirements. We discuss expected changes to assignment results and methodological advantages for pathfinding and model extensions, including horizontal queuing. The new link travel time formulation is finally applied to three example scenarios from literature.
By extending static traffic assignment with explicit capacity constraints, quasidynamic traffic assignment yields more realistic results while avoiding many disadvantages of dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models.
We formulate and check requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We demonstrate that existing approaches for travel time computation in literature fail to satisfy all requirements and derive a new link travel time formula from vertical queuing theory that does meet all requirements.
We discuss expected changes to assignment results and methodological advantages for pathfinding and model extensions, including horizontal queuing. The new link travel time formulation is finally applied to three example scenarios from literature.
...
By extending static traffic assignment with explicit capacity constraints, quasidynamic traffic assignment yields more realistic results while avoiding many disadvantages of dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models.
We formulate and check requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We demonstrate that existing approaches for travel time computation in literature fail to satisfy all requirements and derive a new link travel time formula from vertical queuing theory that does meet all requirements.
We discuss expected changes to assignment results and methodological advantages for pathfinding and model extensions, including horizontal queuing. The new link travel time formulation is finally applied to three example scenarios from literature.
By extending static traffic assignment with explicit capacity constraints, quasi-dynamic traffic assignment yields more realistic results while avoiding many disadvantages of dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models. We formulate requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We derive a new link travel time formula from vertical queuing theory that meets all requirements, unlike existing approaches in literature.
...
By extending static traffic assignment with explicit capacity constraints, quasi-dynamic traffic assignment yields more realistic results while avoiding many disadvantages of dynamic assignment. We analyse the computation of travel times in quasi-dynamic assignment models. We formulate requirements for the correctness of resulting travel times, addressing both the calculation of travel times for individual routes and links itself, as well as the differences between travel times of different travel choices. We derive a new link travel time formula from vertical queuing theory that meets all requirements, unlike existing approaches in literature.
Mobility Impacts of Automated Driving and Shared Mobility
Explorative Model and Case Study of the Province of North-Holland
Conference paper
(2019)
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Maaike Snelder, Isabel Wilmink, Jeroen van der Gun, Hendrik Jan Bergveld, Parvin Hoseini, Bart van Arem
This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of the authors’ knowledge, it is the first model that combines a network fundamental diagram with choice models. A second contribution is the inclusion of automated vehicles, automated (shared) taxis, automated shared vans and new parking concepts in the model as well as the way in which they affect mobility choices and traffic conditions. The insights into the direct mobility impacts are the third contribution. The short computation time of the model enables exploration of large numbers of scenarios, sensitivity analyses and assessments of the impacts of interventions. The model was applied in a case study of the Dutch Province of North-Holland, in which the potential impacts of automated and shared vehicles and mitigating interventions were explored. In this case study, four extreme scenarios were explored, in which 100% of the vehicles have SAE-level 3/4 or 5 and people have a low or high willingness to share. The extremes were chosen to get insights into maximum effects. The results show that if automated vehicles and sharing are accepted, it is likely that there will be considerable changes in mobility patterns and traffic performance, with both positive and problematic effects.
...
This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of the authors’ knowledge, it is the first model that combines a network fundamental diagram with choice models. A second contribution is the inclusion of automated vehicles, automated (shared) taxis, automated shared vans and new parking concepts in the model as well as the way in which they affect mobility choices and traffic conditions. The insights into the direct mobility impacts are the third contribution. The short computation time of the model enables exploration of large numbers of scenarios, sensitivity analyses and assessments of the impacts of interventions. The model was applied in a case study of the Dutch Province of North-Holland, in which the potential impacts of automated and shared vehicles and mitigating interventions were explored. In this case study, four extreme scenarios were explored, in which 100% of the vehicles have SAE-level 3/4 or 5 and people have a low or high willingness to share. The extremes were chosen to get insights into maximum effects. The results show that if automated vehicles and sharing are accepted, it is likely that there will be considerable changes in mobility patterns and traffic performance, with both positive and problematic effects.
Mobility Impacts of Automated Driving and Shared Mobility
Explorative Model and Case Study of the Province of North-Holland
Journal article
(2019)
-
Maaike Snelder, Isabel Wilmink, Jeroen van der Gun, Hendrik Jan Bergveld, Parvin Hoseini, Bart van Arem
This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of the authors’ knowledge, it is the first model that combines a network fundamental diagram with choice models. A second contribution is the inclusion of automated vehicles, automated (shared) taxis, automated shared vans and new parking concepts in the model as well as the way in which they affect mobility choices and traffic conditions. The insights into the direct mobility impacts are the third contribution. The short computation time of the model enables exploration of large numbers of scenarios, sensitivity analyses and assessments of the impacts of interventions. The model was applied in a case study of the Dutch Province of North-Holland, in which the potential impacts of automated and shared vehicles and mitigating interventions were explored. In this case study, four extreme scenarios were explored, in which 100% of the vehicles have SAE-level 3/4 or 5 and people have a low or high willingness to share. The extremes were chosen to get insights into maximum effects. The results show that if automated vehicles and sharing are accepted, it is likely that there will be considerable changes in mobility patterns and traffic performance, with both positive and problematic effects.
...
This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of the authors’ knowledge, it is the first model that combines a network fundamental diagram with choice models. A second contribution is the inclusion of automated vehicles, automated (shared) taxis, automated shared vans and new parking concepts in the model as well as the way in which they affect mobility choices and traffic conditions. The insights into the direct mobility impacts are the third contribution. The short computation time of the model enables exploration of large numbers of scenarios, sensitivity analyses and assessments of the impacts of interventions. The model was applied in a case study of the Dutch Province of North-Holland, in which the potential impacts of automated and shared vehicles and mitigating interventions were explored. In this case study, four extreme scenarios were explored, in which 100% of the vehicles have SAE-level 3/4 or 5 and people have a low or high willingness to share. The extremes were chosen to get insights into maximum effects. The results show that if automated vehicles and sharing are accepted, it is likely that there will be considerable changes in mobility patterns and traffic performance, with both positive and problematic effects.
Journal article
(2018)
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Jeroen van der Gun, Adam Pel, Bart van Arem
The link transmission model is a macroscopic network traffic flow simulation tool based on Lighthill–Whitham–Richards theory. While its efficiency and accuracy are superior to the well-known cell transmission model, applications of its current numerical formulations are limited by the inability to apply changes to the fundamental diagrams of links within a simulation and the need to start the simulation with an empty network. We resolve both limitations by developing a methodology for initialising the discrete-time link model with a non-empty initial condition and for computing within-link densities during the simulation, which can then serve as an initial condition for continued simulation with a new fundamental diagram. Since the computation of within-link densities is algebraic, no new numerical errors are introduced. Optional support for multiple commodities, subcritical delays and platoon dispersion, are retained. The resulting model is demonstrated on a motorway corridor network with variable speed limits and dynamic lane management.
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The link transmission model is a macroscopic network traffic flow simulation tool based on Lighthill–Whitham–Richards theory. While its efficiency and accuracy are superior to the well-known cell transmission model, applications of its current numerical formulations are limited by the inability to apply changes to the fundamental diagrams of links within a simulation and the need to start the simulation with an empty network. We resolve both limitations by developing a methodology for initialising the discrete-time link model with a non-empty initial condition and for computing within-link densities during the simulation, which can then serve as an initial condition for continued simulation with a new fundamental diagram. Since the computation of within-link densities is algebraic, no new numerical errors are introduced. Optional support for multiple commodities, subcritical delays and platoon dispersion, are retained. The resulting model is demonstrated on a motorway corridor network with variable speed limits and dynamic lane management.
Conference paper
(2018)
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Wei Gu, Jie Yu, Yuxiong Ji, Jeroen van der Gun, Adam Pel, H. Michael Zhang, Bart van Arem
Metro disruptions due to unexpected events reduce transit system reliability, resulting in significant productivity loss and long passenger delays. Bus bridging strategy is often used to connect stations affected by metro disruptions such that passengers could continue their journey. The literature usually designed bridging routes and then allocated buses to designed routes with specific frequencies. The restriction that each bus can only operate on a route greatly limits the service flexibility and decreases operation efficiency. We propose a flexible bus bridging strategy to deal with the disruptions of metro networks. The proposed strategy optimizes a tailored bridging path for each bus. The path dictates the stations that a bus should visit in sequence once it is dispatched from the depot. A two-stage model that balances the needs of transit agency and passengers is developed to optimize the tailored bridging paths based on affected metro stations, reserved buses, bus capacity, passenger demands and bus travel times. The Stage I model produces schematic bridging paths by minimizing the maximum bus bridging time. The Stage II model further details the paths by minimizing average passenger delay. The superiority of the proposed strategy to a traditional strategy is demonstrated in a case study in Rotterdam, The Netherlands.
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Metro disruptions due to unexpected events reduce transit system reliability, resulting in significant productivity loss and long passenger delays. Bus bridging strategy is often used to connect stations affected by metro disruptions such that passengers could continue their journey. The literature usually designed bridging routes and then allocated buses to designed routes with specific frequencies. The restriction that each bus can only operate on a route greatly limits the service flexibility and decreases operation efficiency. We propose a flexible bus bridging strategy to deal with the disruptions of metro networks. The proposed strategy optimizes a tailored bridging path for each bus. The path dictates the stations that a bus should visit in sequence once it is dispatched from the depot. A two-stage model that balances the needs of transit agency and passengers is developed to optimize the tailored bridging paths based on affected metro stations, reserved buses, bus capacity, passenger demands and bus travel times. The Stage I model produces schematic bridging paths by minimizing the maximum bus bridging time. The Stage II model further details the paths by minimizing average passenger delay. The superiority of the proposed strategy to a traditional strategy is demonstrated in a case study in Rotterdam, The Netherlands.
Emergencies disrupting urban transportation systems cause management problems for authorities. This thesis develops simulation methods that permit analysis thereof and evaluation of candidate management plans, tested in three case studies. It formulates a methodological framework using agent-based choice models and multimodal macroscopic dynamic network loading models, and develops extensions of the Link Transmission Model to deal with more complex and variable fundamental diagrams and initially non-empty roads.
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Emergencies disrupting urban transportation systems cause management problems for authorities. This thesis develops simulation methods that permit analysis thereof and evaluation of candidate management plans, tested in three case studies. It formulates a methodological framework using agent-based choice models and multimodal macroscopic dynamic network loading models, and develops extensions of the Link Transmission Model to deal with more complex and variable fundamental diagrams and initially non-empty roads.
The original Link Transmission Model as formulated by Yperman et al. (2006) simulates traffic according to Lighthill-Whitham-Richards theory with a very small numerical error, yet only supports triangular fundamental diagrams. This paper relaxes that restriction in two steps. Firstly, we extend the model to handle any continuous concave fundamental diagram, and prove that this extension is still consistent with Lighthill-Whitham-Richards theory. Secondly, we extend the theory and model to handle a capacity drop, explicitly looking into the handling of both the onset and release of congestion. The final model is still first-order and suitable for general networks. Numerical examples show that it qualitatively improves on the original model due to uniquely featuring complex traffic patterns including stop-and-go waves, with crisp shockwaves between traffic states, as well as acceleration fans.
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The original Link Transmission Model as formulated by Yperman et al. (2006) simulates traffic according to Lighthill-Whitham-Richards theory with a very small numerical error, yet only supports triangular fundamental diagrams. This paper relaxes that restriction in two steps. Firstly, we extend the model to handle any continuous concave fundamental diagram, and prove that this extension is still consistent with Lighthill-Whitham-Richards theory. Secondly, we extend the theory and model to handle a capacity drop, explicitly looking into the handling of both the onset and release of congestion. The final model is still first-order and suitable for general networks. Numerical examples show that it qualitatively improves on the original model due to uniquely featuring complex traffic patterns including stop-and-go waves, with crisp shockwaves between traffic states, as well as acceleration fans.
Het oorspronkelijke Linktransmissiemodel zoals geformuleerd door Yperman c.s. (2006) simuleert verkeer nauwkeurig volgens de verkeersstroomtheorie van Lighthill, Whitham en Richards, maar ondersteunt slechts driehoekige fundamentele diagrammen. Deze beperking versoepelen we in twee stappen. Ten eerste breiden we het model uit zodat het met elk continu concaaf fundamenteel diagram kan omgaan. Ten tweede breiden we zowel de eersteordeverkeersstroomtheorie als het numerieke model uit met een capaciteitsval. Het resulterende model is nog steeds een eersteordemodel, is nog steeds geschikt voor algemene netwerken en heeft nog steeds slechts een kleine numerieke fout. Rekenvoorbeelden laten zien dat dit nieuwe simulatiemodel desondanks in staat is om complexe verkeerspatronen te reproduceren met zowel staande files als filegolven en inclusief subkritische vertraging. Dit model positioneert zich daarmee tussen de traditionele modellen voor meer strategische toepassingen en hogereordemodellen voor operationele toepassingen.
Deze presentatie zal gebaseerd zijn op onze recente bijgevoegde publicatie in Transportation Research Part B [Van der Gun, Pel & Van Arem (2017), Extending the Link Transmission Model with non-triangular fundamental diagrams and capacity drops, jaargang 98, pagina's 154-178].
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Het oorspronkelijke Linktransmissiemodel zoals geformuleerd door Yperman c.s. (2006) simuleert verkeer nauwkeurig volgens de verkeersstroomtheorie van Lighthill, Whitham en Richards, maar ondersteunt slechts driehoekige fundamentele diagrammen. Deze beperking versoepelen we in twee stappen. Ten eerste breiden we het model uit zodat het met elk continu concaaf fundamenteel diagram kan omgaan. Ten tweede breiden we zowel de eersteordeverkeersstroomtheorie als het numerieke model uit met een capaciteitsval. Het resulterende model is nog steeds een eersteordemodel, is nog steeds geschikt voor algemene netwerken en heeft nog steeds slechts een kleine numerieke fout. Rekenvoorbeelden laten zien dat dit nieuwe simulatiemodel desondanks in staat is om complexe verkeerspatronen te reproduceren met zowel staande files als filegolven en inclusief subkritische vertraging. Dit model positioneert zich daarmee tussen de traditionele modellen voor meer strategische toepassingen en hogereordemodellen voor operationele toepassingen.
Deze presentatie zal gebaseerd zijn op onze recente bijgevoegde publicatie in Transportation Research Part B [Van der Gun, Pel & Van Arem (2017), Extending the Link Transmission Model with non-triangular fundamental diagrams and capacity drops, jaargang 98, pagina's 154-178].
Many possible emergency conditions, including evacuations, negatively affect the urban transportation system by substantially increasing the travel demand and/or reducing the supplied capacity. A transportation model can be used to quantify and understand the impact of the underlying disasters and corresponding management strategies. To this end, we develop an efficient methodology suitable for simulating multimodal transportation systems affected by emergencies, based on the novel integration of an activity-based choice model with both pre-trip and en-route choices, and a macroscopic or mesoscopic dynamic network loading model. The model structure first estimates the daily equilibrium and then uses that result as a starting point to simulate the emergency situation without further iterations. Unlike previous efforts, our methodology satisfies all requirements identified from literature regarding transportation modeling for emergencies, and is sufficiently general to investigate a wide range of emergency situations and management strategies. An evacuation case study for Delft shows the feasibility of applying the methodology. Furthermore, it yields practical insights for urban evacuation planning that stem from complex system dynamics, such as important interactions among travel directions and among modes. This supports the need for a comprehensive modeling methodology such as the one we present in this paper.
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Many possible emergency conditions, including evacuations, negatively affect the urban transportation system by substantially increasing the travel demand and/or reducing the supplied capacity. A transportation model can be used to quantify and understand the impact of the underlying disasters and corresponding management strategies. To this end, we develop an efficient methodology suitable for simulating multimodal transportation systems affected by emergencies, based on the novel integration of an activity-based choice model with both pre-trip and en-route choices, and a macroscopic or mesoscopic dynamic network loading model. The model structure first estimates the daily equilibrium and then uses that result as a starting point to simulate the emergency situation without further iterations. Unlike previous efforts, our methodology satisfies all requirements identified from literature regarding transportation modeling for emergencies, and is sufficiently general to investigate a wide range of emergency situations and management strategies. An evacuation case study for Delft shows the feasibility of applying the methodology. Furthermore, it yields practical insights for urban evacuation planning that stem from complex system dynamics, such as important interactions among travel directions and among modes. This supports the need for a comprehensive modeling methodology such as the one we present in this paper.
While agent-based modelling of traffic demand is gaining attention, a macroscopic dynamic network loading model may be beneficial, particularly in large-scale applications. We investigate the implications of coupling such models, with inclusion of en-route choices, for the modelling of links and the determination of turning fractions, yielding useful recommendations to help select an appropriate solution scheme of the macroscopic traffic flow theory and overcome other practical challenges specifically associated with the coupling of agent-based traffic demand and macroscopic traffic propagation.
...
While agent-based modelling of traffic demand is gaining attention, a macroscopic dynamic network loading model may be beneficial, particularly in large-scale applications. We investigate the implications of coupling such models, with inclusion of en-route choices, for the modelling of links and the determination of turning fractions, yielding useful recommendations to help select an appropriate solution scheme of the macroscopic traffic flow theory and overcome other practical challenges specifically associated with the coupling of agent-based traffic demand and macroscopic traffic propagation.
Kinematic wave theory consists of two main equations: the conservation of vehicles and the equilibrium flow-density relationship. Assuming that each traffic state along a road at each point in time is an equilibrium state, these combine into a single partial differential equation for the propagation of traffic along a network link. Newell (1993) proposed a solution scheme using cumulative numbers of vehicles as the primary variable, which later led to the development of the Link Transmission Model (Yperman, 2007). Daganzo (2005) implicitly shows that for triangular fundamental diagrams, this model indeed leads to the correct solution.
This requirement of triangular fundamental diagrams is restrictive. Firstly, it imposes the speed in subcritical traffic to be constant instead of more realistically, depending on the traffic density. Secondly, it impedes any discontinuity between the free-flow capacity and the queue discharge rate, i.e. a capacity drop. We therefore extend the Link Transmission Model to handle arbitrary concave fundamental diagrams, optionally including capacity drops. The resulting model, which converges to kinematic wave theory if there is no capacity drop, can be used in a network simulation and features both standing queues and moving jams.
Building upon the proofs in Daganzo, we derive a finite set of space-time paths that form an exact solution network for continuous concave fundamental diagrams. This solution method is more general than those proposed by Yperman for piecewise-linear diagrams and Gentile (2010) for continuously-differentiable diagrams and better at reproducing acceleration fans or rarefaction waves.
We further extend this model to include capacity drops. By applying a node model without memory effects and using inverted-lambda style fundamental diagrams, we permit the head of a queue to move upstream. We ensure that the queue discharge rates before and after a discontinuity in an inhomogeneous road are both taken into account.
...
Kinematic wave theory consists of two main equations: the conservation of vehicles and the equilibrium flow-density relationship. Assuming that each traffic state along a road at each point in time is an equilibrium state, these combine into a single partial differential equation for the propagation of traffic along a network link. Newell (1993) proposed a solution scheme using cumulative numbers of vehicles as the primary variable, which later led to the development of the Link Transmission Model (Yperman, 2007). Daganzo (2005) implicitly shows that for triangular fundamental diagrams, this model indeed leads to the correct solution.
This requirement of triangular fundamental diagrams is restrictive. Firstly, it imposes the speed in subcritical traffic to be constant instead of more realistically, depending on the traffic density. Secondly, it impedes any discontinuity between the free-flow capacity and the queue discharge rate, i.e. a capacity drop. We therefore extend the Link Transmission Model to handle arbitrary concave fundamental diagrams, optionally including capacity drops. The resulting model, which converges to kinematic wave theory if there is no capacity drop, can be used in a network simulation and features both standing queues and moving jams.
Building upon the proofs in Daganzo, we derive a finite set of space-time paths that form an exact solution network for continuous concave fundamental diagrams. This solution method is more general than those proposed by Yperman for piecewise-linear diagrams and Gentile (2010) for continuously-differentiable diagrams and better at reproducing acceleration fans or rarefaction waves.
We further extend this model to include capacity drops. By applying a node model without memory effects and using inverted-lambda style fundamental diagrams, we permit the head of a queue to move upstream. We ensure that the queue discharge rates before and after a discontinuity in an inhomogeneous road are both taken into account.