A bi-level distributed approach for optimizing time-dependent congestion pricing in large networks: A simulation-based case study in the Greater Toronto Area

Aboudina, Aya; Abdulhai, Baher

doi:10.1016/j.trc.2017.10.004

Cited by 19 publications

(7 citation statements)

References 25 publications

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“…Optimization Model Based on Regional Road Network Traffic Diversion Technology e core of the Internet of things is to electronically connect people's various life objects to the Internet by creating an intelligent network that can optimize them by retrieving, searching and requesting information. English is "Internet of things," also known as "Internet of everything" [12]. Simply put, "the Internet of things is the Internet connected with things."…”

Section: Research and Application Of The Trafficmentioning

confidence: 99%

Traffic Optimization Model Based on Regional Road Network Traffic Diversion Technology and Internet of Things

2022

Mobile Information Systems

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Today’s traffic control system is developing in a more intelligent direction. The progress of electronic technology has created a traffic control and management system using a variety of control methods. The development of computers creates a more intelligent traffic optimization model for optimizing network traffic. In the limited road space, traffic control research will focus on maximizing the use of existing traffic management equipment to improve vehicle circulation efficiency and avoid congestion. In this context, combined with the temporal and spatial characteristics of traffic congestion, this study investigates the storage capacity of existing road space and seeks the optimal control method for local regional road network congestion. For the technical problems of traffic diversion in the existing two-phase control method and the queuing order in the adjacent lanes in the four-phase control method, the optimal control method is proposed, which solves the technical problems of traffic control and the phenomenon of “queuing injustice” in the adjacent lanes in one direction. The safety degree and traffic efficiency of vehicle operation are improved. The traffic flow from the same entrance to the main intersection forms a signal phase while slowing down or blocking these traffic flows can effectively improve traffic safety and traffic efficiency. Combined with the development of traditional traffic control system, this study introduces the development status of Internet of things technology and puts forward an intelligent traffic control system based on Internet of things technology. Real-time vehicle traffic information is sent to the Lora gateway through Lora wireless network, which is responsible for data transmission and protocol conversion.

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Section: Research and Application Of The Trafficmentioning

confidence: 99%

Traffic Optimization Model Based on Regional Road Network Traffic Diversion Technology and Internet of Things

2022

Mobile Information Systems

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“…In (11), x i (t) identifies the position of vehicle i at time t. Microscopic modeling is at the base of simulation platforms that have been often used in dynamic toll pricing studies at the network level: car-following-based VISSIM [11,[14][15][16]23,36], Paramics [21,27], CORSIM [29,52] and MITSIM [30]. A mesoscopic modeling-based simulator, DynusT, is employed in [53] and a regional mesoscopic dynamic traffic assignment simulation environment is adopted in [54,56]. DynaMIT, a mesoscopic dynamic traffic simulator is applied in [30] toghether with microscopic simulation.…”

Section: Traffic Simulationmentioning

confidence: 99%

“…The authors of [60] present a dynamic user equilibrium, where travelers engage in a Nash-like game choosing routes and departure times aiming to minimize selfishly their travel costs, which account for travel time, early/late arrival penalties and tolls. The authors of [54,56] adopt an econometric model considering drivers' socioeconomic characteristics and the network level-of-service to capture the drivers' departure time choice in consequence of the toll. In [30], a path-size logit model is used for route choice, considering the similarities between overlapping paths.…”

Section: Driver Behaviormentioning

confidence: 99%

Model-Based Dynamic Toll Pricing: An Overview

2021

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In this paper, we review some of the most recent research regarding design, simulation, implementation and evaluation of dynamic tolling schemes. Analyzing the structure of the reviewed studies, we identify the common elements and the differences in the approaches chosen by different authors, presenting an overview of the methods for price definition and of the simulation techniques as well as a discussion on the newest technology applications in the field. Optimization revealed to be the dominant price definition method, while control-based algorithms are notably employed for managed lanes toll pricing schemes. Regarding traffic and driver behavior simulation we observed a great variety of solutions throughout the reviewed papers, with a prevalence of macroscopic models for the former and logit models for the latter. Still few papers include models for externalities quantification, while AI paradigms are gaining importance in the field.

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“…Sheu and Yang [ 25 ] integrated a ramp control strategy with a dynamic pricing algorithm to better manage the dynamic freeway congestion. Applicable dynamic pricing algorithms on large-scale networks were proposed in [ 26 , 27 , 28 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of Accurate Detection of Freeway Traffic Conditions on the Dynamic Pricing: A Case Study of I-95 Express Lanes

Alshayeb

Stevanovic

Mitrović³

et al. 2021

Sensors

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Express lanes (ELs) implementation is a proven strategy to deal with freeway traffic congestion. Dynamic toll pricing schemes effectively achieve reliable travel time on ELs. The primary inputs for the typical dynamic pricing algorithms are vehicular volumes and speeds derived from the data collected by sensors installed along the ELs. Thus, the operation of dynamic pricing critically depends on the accuracy of data collected by such traffic sensors. However, no previous research has been conducted to explicitly investigate the impact of sensor failures and erroneous sensors’ data on toll computations. This research fills this gap by examining the effects of sensor failure and faulty detection scenarios on ELs tolls calculated by a dynamic pricing algorithm. The paper’s methodology relies on applying the dynamic toll pricing algorithm implemented in the field and utilizing the fundamental speed-volume relationship to ‘simulate’ the sensors’ reported data. We implemented the methodology in a case study of ELs on Interstate-95 in Southeast Florida. The results have shown that the tolls increase when sensors erroneously report higher than actual traffic demand. Moreover, it has been found that the accuracy of individual sensors and the number of sensors utilized to estimate traffic conditions are critical for accurate toll calculations.

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A bi-level distributed approach for optimizing time-dependent congestion pricing in large networks: A simulation-based case study in the Greater Toronto Area

Cited by 19 publications

References 25 publications

Traffic Optimization Model Based on Regional Road Network Traffic Diversion Technology and Internet of Things

Traffic Optimization Model Based on Regional Road Network Traffic Diversion Technology and Internet of Things

Model-Based Dynamic Toll Pricing: An Overview

Impact of Accurate Detection of Freeway Traffic Conditions on the Dynamic Pricing: A Case Study of I-95 Express Lanes

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