Redesigning Highway Infrastructure Systems for Connected Autonomous Truck Lanes

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 pound occurred for high (80%) CAT PR operating under Standard D3M, whereas the highest LCC of 152,728,100 pound 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.