Redesigning Highway Infrastructure Systems for Connected Autonomous Truck Lanes
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 12
Abstract
Previous studies on connected autonomous vehicles (CAVs) examined pavement performance and lane widths separately and in isolation, and without consideration for roadworks conditions. Hence, this study presents a holistic, optimal highway design solution for connected autonomous trucks (CATs) by testing pavement failure and traffic performance under different cross-sectional configurations incorporating a dedicated CAT lane for both normal and temporary traffic management (TTM) arrangements. Firstly, a dual three-lane motorway (D3M) was selected as a base case site. Next, previous research on substandard lanes was used to produce five nonstandard cross-section alternatives, which were then modeled using commercially available software. Capital investments to implement the alternatives were calculated by applying established industry construction cost models. Each cross-section was then subjected to different CATs penetration rates (PRs) and wheel wander regimes, and their pavement structural deterioration analyzed using the Texas Mechanistic-Empirical Asphalt Concrete Pavement Design and Analysis System (TxME) software. From this, maintenance frequencies and costs were determined. The study estimated delays and delay costs during TTM over a 20-year design period. Finally, initial investment, rehabilitation and delay costs were combined. It was found that the lowest life-cycle cost (LCC) of £19,091,470 occurred for high (80%) CAT PR operating under Standard D3M, whereas the highest LCC of £152,728,100 was also for high PR, but under Substandard D4M. Optimal LCC was found to change with different PRs. Hence cross-sections should be dynamically modifiable, given the anticipated gradual increase in PRs over time.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request:
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Construction cost estimates,
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Traffic data and prediction models, and
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Travel delay under temporary traffic management conditions.
Acknowledgments
The authors would like to thank the Engineering and Physical Sciences Research Council for funding this research under University of Southampton’s Centre for Doctoral Training in Sustainable Infrastructure Systems (CDT-SIS). The authors confirm contribution to the paper as follows: study conception and design: H. Jehanfo, I. Kaparias, J. Preston, and A. Stevens; data generation: H. Jehanfo, S. Hu, and F. Zhou; analysis and interpretation of results: H. Jehanfo, S. Hu, and F. Zhou; and draft manuscript preparation: H. Jehanfo. All authors reviewed the results and approved the final version of the manuscript.
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 12 • December 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Feb 25, 2022
Accepted: Jul 13, 2022
Published online: Sep 22, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 22, 2023
ASCE Technical Topics:
- Benefit cost ratios
- Business management
- Cross sections
- Design (by type)
- Engineering fundamentals
- Financial management
- Gravels
- Highway and road design
- Highway transportation
- Infrastructure
- Mathematics
- Pavement condition
- Pavement design
- Pavements
- Practice and Profession
- Sight distances
- Traffic engineering
- Traffic management
- Transportation engineering
- Trucks
- Vehicle-pavement interaction
- Vehicles
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