Simulating High-Occupancy Toll Lane Operations

Lane changes (LCs) are important in traffic flow operations. They cause differences in flow over lanes and in some cases determine the start of congestion. Whereas calibration and validation are commonly used with car-following models, this is not common practice with LC models. Even then, it is not clear what calibration and validation entails for probabilistic LC models. Therefore, this paper reviews methodologies to calibrate and validate probabilistic LC models, both microscopically and macroscopically. A likelihood is often used in calibration but does not intuitively show the quality of the model. An example shows that it is possible to have the model calibrated and validated with accurate parameters all having the same error in the validation as in the calibration, but the quality of the model is still bad. Using a likelihood ensures the stochastic effects are well captured, but the conclusion is that for validation purposes, one can better use a measure that has physical interpretation and gives a value indicating the quality of the model for the purpose for which it needs to be used.

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“…A global match of those values with the ones reported in literature is taken as a proof of validation [6].…”

Section: A Theory Of the Calibration And Validation Processmentioning

confidence: 99%

Calibration and Validation of Probabilistic Discretionary Lane-Change Models

Knoop

Buisson

2014

IEEE Trans. Intell. Transport. Syst.

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“…where the toll price π(k) (in monetary units) is defined by a controller, being the control variable an occupancy parameter. A similar concept was applied in [11], where the optimal HOT flow ratio to set the dynamic toll is defined by a control-based piecewise linear function, in [50] and in [52]. Also in [14][15][16] the control mechanism is based on a piecewise linear function but with variable revenue-maximizing optimal gains.…”

Section: Control-based Algorithmsmentioning

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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“…Michalaka et al [ 53 ] introduced an add-on for the traffic simulation software CORSIM to model multi-segmented ELs with various pricing strategies considering motorists’ lane choice between ELs and GP lanes. To perform various congestion pricing studies on the New York City (NYC) network, a virtual testbed for New York City was developed by He et al [ 54 ] using an agent-based simulation ‘MATSim’, an open-source simulation toolkit coded in Java and developed by the Federal Highway Administration (FHWA) [ 54 ].…”

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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Simulating High-Occupancy Toll Lane Operations

Cited by 15 publications

References 10 publications

Calibration and Validation of Probabilistic Discretionary Lane-Change Models

Calibration and Validation of Probabilistic Discretionary Lane-Change Models

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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