Network reliability‐based optimal toll design

Hao, Li; Bliemer, Michiel C.J.; Bovy, Piet H. L.

doi:10.1002/atr.5670420307

Cited by 24 publications

(19 citation statements)

References 13 publications

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“… modeling decision making of travelers under uncertainty (Chen et al, 2002a; Lo et al, 2006; Lam et al, 2008; Shao et al, 2008; Siu and Lo, 2008; Zhou and Chen, 2008; Connors and Sumalee, 2009), evaluating the performance of transport systems and finding critical components (e.g., Bell, 2000; Cassir et al, 2003; Szeto et al, 2006; Heydecker et al, 2007; Sumalee and Watling, 2008; Shimamoto et al, 2008), transport network planning and design (e.g., Lam and Xu, 1999; Lo and Tung, 2003; Sumalee et al, 2006; Chen et al, 2007; Li et al, 2008), and traffic management and control (e.g., Taylor, 1999, 2000; Hoogendoorn et al, 2008). …”

Section: Problem Formulationmentioning

confidence: 99%

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Reliability-Based Transit Assignment for Congested Stochastic Transit Networks

Szeto

Solayappan

Jiang

2011

Computer-Aided Civil and Infrastructure Engineering

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This article proposes a nonlinear complementarity problem (NCP) formulation for the risk-aversive stochastic transit assignment problem in which in-vehicle travel time, waiting time, capacity, and the effect of congestion are considered as stochastic variables simultaneously and both their means and variances are incorporated into the formulation. A new congestion model is developed and captured in the proposed NCP formulation to account for different effects of on-board passengers and passengers waiting at stops. A reliabilitybased user equilibrium condition is also defined based on the proposed generalized concept of travel time budget referred to as effective travel cost, and is captured in the formulation. A column generation based algorithm is proposed to solve the NCP formulation. A survey was conducted to validate that the degree of risk aversion of transit passengers affects their route choices. Numerical studies were performed to demonstrate the problem and the effectiveness of the proposed algorithm. The results obtained show that underestimating the congestion effect and ignoring the risk aversion behavior can overestimate the patronage of transit service, which have profound im- * To whom correspondence should be addressed. E-mail: ceszeto@ hku.hk.plications on the profit of the operators involved and the development of transit network design models.

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Section: Problem Formulationmentioning

confidence: 99%

“…transport network planning and design (e.g., Lam and Xu, 1999; Lo and Tung, 2003; Sumalee et al, 2006; Chen et al, 2007; Li et al, 2008), and…”

Section: Problem Formulationmentioning

confidence: 99%

Reliability-Based Transit Assignment for Congested Stochastic Transit Networks

Szeto

Solayappan

Jiang

2011

Computer-Aided Civil and Infrastructure Engineering

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“…An important part in the delicate process of road pricing planning is the selection of tolling system, as an important ancillary asset. Just as different optimal tool schemes relate 2 Journal of Advanced Transportation to different policy objectives [15], toll collection system (TCS) directly affects the user's experience and consequently acceptance of road pricing scheme. Additional challenge in the decision-making process emerges from the fact that the choice of a particular TCS assumes the operational responsibility for the next 10 to 20 years.…”

Section: Introductionmentioning

confidence: 99%

Decision-Support Framework for Selecting the Optimal Road Toll Collection System

Milenković

Glavić

Mladenović

2018

Journal of Advanced Transportation

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One of the central decision-making questions in planning road tolling is the selection of the optimal toll collection system (TCS). The question of TCS selection arises in the situation when the existing TCS is to be upgraded or when TCS is selected for a newly constructed road. Considering that there are multiple TCS available nowadays, with their particular advantages and disadvantages, and that there is a range of often conflicting criteria for TCS selection, this decision-making issue belongs to the group of multicriteria decision-making (MCDM) problems. The MCDM-based methodology used in this research integrates Strengths-Weakness-Opportunities-Threat (SWOT) analysis and Fuzzy Preference Ranking Organization Method for Enrichment Evaluations (F-PROMETHEE). The expert-based decision-support framework includes a procedure for defining evaluation criteria and their weights, scoring of alternatives, and sensitivity analysis. Presented decision-support framework is tested with fourteen toll systems. Results indicate that the best-ranked TCS is the dedicated short-range communication multilane free flow. Decision-support framework is developed for transferability to different contexts, where local features can be taken into account by choosing specific alternatives, criteria, and criteria values. Finally, this development opens up opportunities for further analysis of criteria values and considerations of user attitudes in road pricing scheme planning.

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“…Recently, Li et al . investigated the network travel time reliability by proposing a bi‐level optimal toll design model. Liu et al .…”

Section: Introductionmentioning

confidence: 99%

A reinforcement learning approach for distance‐based dynamic tolling in the stochastic network environment

Zhu

Ukkusuri

2014

J of Advced Transportation

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SUMMARYThis paper proposes a novel dynamic tolling model based on distance and accounts for uncertain traffic demand and supply conditions. The distance-based tolling controller is modeled as an intelligent agent interacting within the stochastic network environment dynamically by taking actions, which are to decide different distance-based tolling rates of vehicles. The distance-based tolls are determined according to various metrics, for example, total traffic flow throughput, delay time, vehicular emissions, which are set as objectives in the modeling framework. The optimal tolling rate is determined by an R-Markov Average Reward Technique based reinforcement learning algorithm. In the numerical case study, we test the proposed tolling scheme on a benchmark test network-the Sioux Falls network-where specified links are candidate toll links. The result shows that the total travel time of tolling links reduces by 25% over simulation runs.

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Network reliability‐based optimal toll design

Cited by 24 publications

References 13 publications

Reliability-Based Transit Assignment for Congested Stochastic Transit Networks

Reliability-Based Transit Assignment for Congested Stochastic Transit Networks

Decision-Support Framework for Selecting the Optimal Road Toll Collection System

A reinforcement learning approach for distance‐based dynamic tolling in the stochastic network environment

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