Marginal cost congestion pricing based on the network fundamental diagram

Simoni, Michele D.; Pel, Adam J.; Waraich, Rashid A.; Hoogendoorn, Serge P.

doi:10.1016/j.trc.2015.03.034

Cited by 84 publications

(52 citation statements)

References 38 publications

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“…Recently, several works (Zheng et al, 2012;Simoni et al, 2015) are devoted to develop effective congestion pricing schemes similar to the one of Section 2.2, however without treating multimodality or user heterogeneity. Operating at a decent level of public transport (PT) services is important.…”

Section: Pricing Strategies With Accessibility Improvement and Incentmentioning

confidence: 99%

“…In this work, travelers could only change their time of departure and route but mode choice is not an option. A similar approach was later applied in Simoni et al (2015) who derived optimal pricing using MFD and marginal cost theory, without investigating the impact of pricing on multimodality either. Combining dynamic pricing with dynamic allocation of road space between multiple modes (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Zheng

Rérat

Geroliminis

2016

Transportation Research Part C: Emerging Technologies

122

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a b s t r a c tIn this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional-Integral type feedback controller, based on the level of vehicular traffic congestion and traveler's behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain.

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Section: Pricing Strategies With Accessibility Improvement and Incentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Zheng

Rérat

Geroliminis

2016

Transportation Research Part C: Emerging Technologies

122

View full text Add to dashboard Cite

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“…MFD-based traffic management strategies serve for this sustainable and global mobility goal. Recent studies have demonstrated the performance of such strategies, examples including congestion pricing (Zheng et al, 2012;Simoni et al, 2015), space allocation for bus lanes (Zheng and Geroliminis, 2013), and dynamic traffic signal perimeter control (refer to Ramezani et al, 2015 for a review).…”

Section: Parking Pricing Strategiesmentioning

confidence: 99%

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Zheng

Geroliminis

2016

Transportation Research Part B: Methodological

162

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a b s t r a c tCruising-for-parking constraints mobility in urban networks. Car-users may have to cruise for on-street parking before reaching their destinations. The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage). The cruising flow causes delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore important to understand the impact of parking limitation on mobility, and to identify efficient parking policies for travel cost reduction. Most existing studies on parking fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general, lack the treatment of dynamics of the cruising-for-parking phenomenon, or require detailed input data that are typically costly and difficult to collect. In this paper, we propose an aggregated and dynamic approach for modeling multimodal traffic with the treatment on parking, and utilize the approach to design dynamic parking pricing strategies. The proposed approach is based on the Macroscopic Fundamental Diagram (MFD), which can capture congestion dynamics at network-level for single-mode and bi-modal (car and bus) systems. A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion. Pricing strategies are developed with the objective of reducing congestion, as well as lowering the total travel cost of all users. A case study is carried out for a bi-modal city network with a congested downtown region. An elegant feedback dynamic parking pricing strategy can effectively reduce travel delay of cruising and the generic congestion. Remarkably, such strategy, which is applicable in real-time management with limited available data, is fairly as efficient as a dynamic pricing scheme obtained from system optimum conditions and a global optimization with full information about the future states of the system. Stackelberg equilibrium is also investigated in a competitive behavior between different parking facility operators. Policy indications on on-street storage capacity management and pricing are provided.

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“…See Aboudolas and Geroliminis (); Geroliminis et al. (); Keyvan‐Ekbatani, Kouvelas, Papamichail, and Papageorgiou (); Ramezani, Haddad, and Geroliminis () for NFD‐based perimeter control, and Gu, Shafiei, Liu, and Saberi (); Simoni, Pel, Waraich, and Hoogendoorn (); Zheng, Rérat, and Geroliminis (); Zheng, Waraich, Axhausen, and Geroliminis () for NFD‐based pricing.…”

Section: Introductionmentioning

confidence: 99%

“…To address this network design problem with an expensive‐to‐evaluate objective function featuring nonconvexity, nonlinearity, and nonclosed form, simulation optimization (SO) or simulation‐based optimization has recently been investigated and advocated (Amaran, Sahinidis, Sharda, & Bury, ; Osorio & Bierlaire, ). When SO is applied to solve the TLP, existing methods can be classified into two broad categories of feedback control (Gu, Shafiei, et al., ; Simoni et al., ; Zheng et al., ; Zheng et al., ) and surrogate‐based optimization (Chen et al., ; Chen, Xiong, He, Zhu, & Zhang, ; Chen, Zhang, He, Xiong, & Zhu, ; Chow & Regan, ; Ekström, Kristoffersson, & Quttineh, ; He, Chen, Xiong, Zhu, & Zhang, ).…”

Section: Introductionmentioning

confidence: 99%

Surrogate‐based toll optimization in a large‐scale heterogeneously congested network

Waller

Saberi

2019

Computer aided Civil Eng

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Toll optimization in a large‐scale dynamic traffic network is typically characterized by an expensive‐to‐evaluate objective function. In this paper, we propose two toll‐level problems (TLPs) integrated with a large‐scale simulation‐based dynamic traffic assignment model of Melbourne, Australia. The first TLP aims to control the pricing zone (PZ) through a time‐varying joint distance and delay toll such that the network fundamental diagram (NFD) of the PZ does not enter the congested regime. The second TLP is built upon the first TLP by further considering the minimization of the heterogeneity of congestion distribution in the PZ. To solve the two TLPs, a computationally efficient surrogate‐based optimization method, that is, regressing kriging with expected improvement sampling, is applied to approximate the simulation input–output mapping, which can balance well between local exploitation and global exploration. Results show that the two optimal TLP solutions reduce the average travel time in the PZ (entire network) by 29.5% (1.4%) and 21.6% (2.5%), respectively. Reducing the heterogeneity of congestion distribution achieves higher network flows in the PZ and a lower average travel time or a larger total travel time saving in the entire network.

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Marginal cost congestion pricing based on the network fundamental diagram

Cited by 84 publications

References 38 publications

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Surrogate‐based toll optimization in a large‐scale heterogeneously congested network

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