Bi-level programming model of truck congestion pricing at container terminals

Zhang, Hao; Zhang, Qian; Chen, Wenhao

doi:10.1007/s12652-017-0641-y

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…This means that, although some of them work as time-of-day tolls, the price of a HOT lane can change in real-time depending on the actual traffic conditions of the highway in which the system is installed. Purely dynamic, responsive toll charging systems are only theoretical (Shirazi, Aashtiani, & Quadrifoglio, 2017), (Zhang, Zhang, & Chen, 2019), and are not deployed, tested and validated in real-world applications or reflect the real purposes and knowledge of a real road infrastructure operator (Shirazi, Aashtiani, & Quadrifoglio, 2017), (Zhang, Zhang, & Chen, 2019), (Bracher & Bogenberger, 2017).…”

Section: State Of the Art On Dynamic Toll Chargingmentioning

confidence: 99%

Novel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highways

Figueiras

Gonçalves

Costa

et al. 2019

Computers & Industrial Engineering

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Traffic congestion is a huge problem in many countries. It affects not only the inner workings of cities but also the quality of life of the people that endure it. In Portugal, traffic congestion happens mainly on national/urban roads, and this phenomenon has increased since the introduction of the so called shadow-toll systems in highways that were free to use. This work proposes a toll charging system that relies on a novel dynamic congestion charging scheme, supported by state of the art Big Data technologies, in order to shift traffic from national/urban roads to tolled highways, taking into account not only the Quality of Service of the highways and national roads, but also the competitiveness of toll prices for users. This Intelligent Transportation System was tested and validated in a real-world scenario with one of the biggest freight logistics companies in Portugal and with the Portuguese public road infrastructure operator. Highlights A novel dynamic toll charging scheme applied to freight vehicles for Portugal's shadow-toll highways  A Big Data platform supporting the Dynamic Toll Charging system  Real-world test and validation of the Dynamic Toll Charging system, through the participation of a road operator and a freight logistics company

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Section: State Of the Art On Dynamic Toll Chargingmentioning

confidence: 99%

Novel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highways

Figueiras

Gonçalves

Costa

et al. 2019

Computers & Industrial Engineering

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show abstract

“…The numerical results show that the proposed method can achieve acceptable accuracy, but the computation speed is relatively low, restricting the use for rapid evaluations. Zhang et al (2019a) extend the application of B-PSFFA to determine the optimal toll rates in a container terminal. The objective is to minimize the truck waiting times by optimizing different toll rates for different periods.…”

Section: Performance Analysis Methodsmentioning

confidence: 99%

“…Therefore, it attempts to change the truck arrival behavior through several incentives, such as time-varying tolls, time-windows assignment, and TAS implementation. Time-varying tolls aim to reduce truck arrivals at the gate during the busy period by charging different fees during peak and off-peak hours (Chen et al 2011;Zhang et al 2019a). Time-windows assignment aims to shorten the truck waiting time by allocating specific time windows for truck arrivals to match storage 1 3…”

Section: Truck Congestion Problemmentioning

confidence: 99%

Performance analysis of a drop-swap terminal to mitigate truck congestion at chemical sites

Wibowo

Fransoo

2021

Flex Serv Manuf J

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“…Zhang et al [27] proposed a bi-level truck congestion pricing model to optimize toll rates at the terminal. The upper-level problem sought to minimize the average truck waiting time while the lower-level problem sought to minimize the drayage cost via a utility function.…”

Section: Tas Modeled As Multi-player Gamementioning

confidence: 99%

Modeling the Truck Appointment System as a Multi-Player Game

2022

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Background: Random truck arrivals at maritime container terminals are one of the primary reasons for gate congestion. Gate congestion negatively affects the terminal’s and drayage firms’ productivity and the surrounding communities in terms of air pollution and noise. To alleviate gate congestion, more and more terminals in the USA are utilizing a truck appointment system (TAS). Methods: This paper proposes a novel approach to modeling the truck appointment system problem. Unlike previous studies which largely treated this problem as a single-player game, this study explicitly models the interplay between the terminal and drayage firms with regard to appointments. A multi-player bi-level programming model is proposed, where the terminal functions as the leader at the upper-level and the drayage firms function as followers at the lower-level. The objective of the leader (the terminal) is to minimize the gate waiting cost of trucks by spreading out the truck arrivals, and the objective of the followers (drayage firms) is to minimize their own drayage cost. To make the model tractable, the bi-level model is transformed to a single-level problem by replacing the lower-level problem with its equivalent Karush–Kuhn–Tucker (KKT) conditions and the model is solved by finding the Stackelberg equilibrium in one-shot simultaneous-moves among players. For comparison purposes, a single-player version of the TAS model is also developed. Results: Experimental results indicate that the proposed multi-player model yields a lower gate-waiting cost compared to the single-player model, and that it yields higher cost savings for the drayage firms as the number of appointments per truck increases. Moreover, the solution of the multi-player model is not dependent on the objective function coefficients, unlike the single player model. Conclusions: This study demonstrates that a TAS is more effective if it considers how the assigned appointment slot affects a truck’s drayage cost. It is recommended that terminal operators and port authorities initiate conversations with their TAS providers about incorporating this element into their TAS.

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Bi-level programming model of truck congestion pricing at container terminals

Cited by 10 publications

References 18 publications

Novel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highways

Novel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highways

Performance analysis of a drop-swap terminal to mitigate truck congestion at chemical sites

Modeling the Truck Appointment System as a Multi-Player Game

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