Multi-objective cordon price design to control long run adverse traffic effects in large urban areas

Amirgholy, Mahyar; Rezaeestakhruie, Hojjat; Poorzahedy, Hossain

doi:10.1007/s11066-015-9092-9

Cited by 17 publications

(10 citation statements)

References 59 publications

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“…On the other hand, such identification would help authorities to implement effective strategies to alleviate network congestion, especially in peak-hour periods. Flexible work hours, telecommuting, and dynamic congestion pricing are among the policies that require information on the implications of activity timing behavior to be effective in congestion-mitigation scenarios (3)(4)(5)(6)(7)(8)(9)(10)(11).…”

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confidence: 99%

Dynamics of Activity Time-of-Day Choice

Shabanpour

Golshani

Auld

et al. 2017

Transportation Research Record

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This study explored travelers’ decision behavior in selecting activity start times. The study examined the problem in the context of the Agent-based Dynamic Activity Planning and Travel Simulation (ADAPTS) activity-based travel demand model for the Chicago, Illinois, metropolitan area. A unique feature of the ADAPTS framework is its consideration of planning horizons for various activity attributes. Naturally, the various attributes of an activity—such as start time, duration, location, party involvement, and mode of travel—can be planned in different time horizons. An attribute that is planned affects the choice of other activity attributes. Therefore, developing a true behavioral time-of-day choice model would not be possible unless the planning order of activity attributes and the dynamics of travelers’ decision-making processes are taken into account. Similarly, it can be argued that there should be fundamental differences in the time-of-day decision process when other attributes of the activity are not yet planned but are to be decided at a later time. The presented time-of-day model aims to capture the dynamics of this decision process by considering the planning time horizons of other attributes of the activity, as well as the outcomes of the decisions. The study adopted the discrete choice approach to model activity timing decisions and a hybrid utility maximization and developed a regret minimization model to account for the heterogeneity of decision rules across choice variables. Analysis of the estimation results and parameter elasticities indicates that higher expected travel time, variations in travel time, and schedule occupancy rates for different time choices can significantly increase the regret value of the corresponding choice and therefore affect the time-of-day choice.

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confidence: 99%

Dynamics of Activity Time-of-Day Choice

Shabanpour

Golshani

Auld

et al. 2017

Transportation Research Record

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“…In the review of the literature, we try to be selective of papers that speci cally deal with pricing automobiles for air pollution control, and not pricing transportation networks in general that cover a wide range of objectives. Amirgholy et al [5], based on the review of over 100 references, discuss the matter quite extensively under wide ranges of topics. Tsekeris and Vo [6] also present a rather recent review of road pricing studies and research, covering over 400 references of which few papers have focused on the air quality and car emission aspects of the network pricing.…”

Section: A Review Of the Literaturementioning

confidence: 99%

“…Amirgholy et al [5] show the popularity and e ectiveness of cordon pricing in targeting speci c problems, including air pollution. Their conclusions include the following: (a) Actual implementation of this pricing method veri ed that emission reduction (leading to environmental and health improvements) was a byproduct of the implemented scheme [28]; (b) Public transportation alone could not reduce the network congestion appreciably even in its ideal condition [29]; (c) Paying for the roads based on the level of use is technically successful, and tends to gain public acceptance when introduced.…”

Section: A Review Of the Literaturementioning

confidence: 99%

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Dynamic Network Pricing to Contain Urban Air Pollutionin Stochastic Environment

2016

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Network pricing is an e ective transportation demand management scheme to reduce tra c and control air pollution, particularly in CBDs. In this study, congested area cordon entry and Park-and-Ride (P/R) facility use are priced for automobiles. Increase in these prices may reduce private auto demand by impelling some of the auto passengers to use public transport from the origin of their trips, or encouraging them to park their cars at the P/R facilities and use buses, or pay the entrance fee and drive inside the cordon. A Markov decision process has been devised to nd an optimal policy for pricing the P/R facilities and cordon entry in a city within a variable demand context. This process is sensitive to weather condition (more favorable atmospheric condition allows lower prices). It leads to a balance between the costs of pollution hazards to the public at large on one side and the cost imposed upon auto drivers to take the next best decisions and their travel times and costs on the other side, thus giving a resilient character to the city. The model has been applied to the network of a large urban area and the results are analyzed. Suggestions for further research end the discussion.

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“…Besides the equity issue, environmental considerations are often included for sustainable development. Amirgholy et al [15] presented an equilibrium model to estimate the long-run adverse traffic effects of a cordon pricing scheme on consumer welfare and air pollution. Gühnemann et al [16] analyzed the application of cordon pricing for the reduction of local air pollution in addition to social welfare maximization.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Cordon Sanitaire for Regular Epidemic Control

Lin

2021

Advances in Civil Engineering

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The outbreak of COVID-19 has disrupted our regular life. Many state and local authorities have enforced a cordon sanitaire for the protection of sensitive areas. Travelers can only travel across the cordon after being qualified. This paper aims to propose a method to determine the optimal deployment of cordon sanitaire in terms of the number of parallel checkpoints at each entry link for regular epidemic control. A bilevel programming model is formulated where the lower-level is the transport system equilibrium with queueing to predict traffic inflow, and the upper-level is queueing network optimization, which is an integer nonlinear programming. The objective of this optimization is to minimize the total operation cost of checkpoints with a predetermined maximum waiting time. Note that stochastic queueing theory is used to represent the waiting phenomenon at each entry link. A heuristic algorithm is designed to solve the proposed bilevel model where the method of successive averages (MSA) is adopted for the lower-level model, and the genetic algorithm (GA) is adopted for the upper-level model. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that the methods can find a good heuristic optimal solution. These methods are useful for policymakers to determine the optimal deployment of cordon sanitaire for hazard prevention and control.

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Multi-objective cordon price design to control long run adverse traffic effects in large urban areas

Cited by 17 publications

References 59 publications

Dynamics of Activity Time-of-Day Choice

Dynamics of Activity Time-of-Day Choice

Dynamic Network Pricing to Contain Urban Air Pollutionin Stochastic Environment

Optimal Design of Cordon Sanitaire for Regular Epidemic Control

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