Evaluation of Alternative Methods for Dynamic I-95 Express Lane Pricing

Developing dynamic toll algorithms is a major task for express lanes (EL) policy makers. The majority of pricing methods applied in the field utilize traffic data collected at several points along an EL segment to estimate traffic conditions (mainly traffic density) and calculate tolls. While travel time (TT) data can directly capture field conditions and users’ delay on a segment, such data are rarely utilized to calculate tolls for EL users. The literature suggests minor utilization of TTs in EL toll calculations, but not as the main target performance measure. More importantly, there is a need to look at performance of EL tolls from a multi-criteria perspective where the goal is not only to maintain certain level of service on the ELs. To address these topics, this study tests alternative toll calculation methods that rely mainly on TT data and compare their performance with the currently utilized toll calculation algorithm on I-95 EL in South Florida, U.S. In addition, this study proposes an evaluation framework which includes five different criteria to select the best-performing algorithms: 1. policy, 2. efficiency, 3. capacity utilization, 4. cost recovery, and 5. reliability. Results of the study show that a TT-based algorithm, which is less sensitive than conventional methods, performs similarly to a density-based algorithm, and that a travel time savings (TTS)-based algorithm maintains speeds on the ELs more efficiently than the alternative methods. Future research should apply and validate similar methods on other EL cases around the country.

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    • The opinions, findings, and conclusions expressed in this publication are those of the authors and not necessarily those of FDOT or the U.S. Department of Transportation. © National Academy of Sciences: Transportation Research Board 2020.
  • Authors:
    • Mitrovic, Djurdjija
    • Stevanovic, Aleksandar
    • Glavic, Drazenko
  • Publication Date: 2020-10


  • English

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  • Accession Number: 01749128
  • Record Type: Publication
  • Files: TRIS, TRB, ATRI
  • Created Date: Aug 19 2020 3:04PM