摘要: |
Freight and the efficient movement of freight is a critical component to the economy of the southern U.S. – especially to states in the South-Central region (AR, LA, NM, OK, and TX). Several challenges exist in supporting a strong freight economy: (1) efficiency of freight movement muffled by an infrastructure system in need of repair, limited capacity, and severe congestion and (2) mitigating negative community impacts. Connected and automated vehicle (CAV) technologies offer potentially transformative societal impacts including significant mobility, safety, and environmental benefits. One CAV application of particularly interest to the freight industry is truck platooning. Benefits of truck platooning include energy savings from aerodynamic drag reduction, reduced highway congestion due to short following distances, and safety improvements from faster reaction times and automated support systems (i.e., truck platooning has great potential in addressing current challenges facing freight movement). However, the short following distances maintained between vehicles and more precise lane-keeping lead to a higher concentration of load being placed on the transportation infrastructure. It is unclear how these greater weight concentrations and new load configurations will impact the deterioration/damage to pavements.
The main objectives of this study are: (1) through a series of modeling case studies located in the South-Central region, the operational and environmental (fuel savings/emissions) impacts of various truck platooning implementations, configurations, and assumptions will be quantified at both the corridor- and network-level, (2) impacts to the structural pavement resulting from these truck platooning implementations will be investigated and quantified using finite element modeling (FEM), and (3) a feasibility study for implementation will be performed comparing the (potential) operational and environmental (fuel savings/emissions) benefits of truck platooning with the (potential) costs associated with increased pavement loads. This will also be compared with an equivalent “base case” with human-driven trucks. |