Method for designing fuel-efficient highway longitudinal slopes for intelligent vehicles in eco-driving scenarios

Reasonable road design can not only improve traffic efficiency, ensure driving safety, reduce construction costs, but also reduce the energy consumption of road transportation. However, existing road design research mainly focuses on safety, efficiency, and economic factors, with few studies considering the actual construction difficulty as well as energy saving and emission reduction of transportation. To fill the research gap, this paper proposes a longitudinal slope design method for highway sections that considers both vehicle fuel consumption minimization and construction feasibility. First, the passenger car trajectory data and fuel consumption data from the Beihuan Highway in Guangzhou, Guangdong Province, China were collected, and the optimal combination features of the random forest algorithm were extracted using parameters such as vehicle operating conditions and road grades, thus establishing a fuel consumption estimation model for passenger cars on highways. Second, by combining the fuel consumption estimation model with dynamic programming algorithm, an ecological speed planning model for passenger cars on highways was developed. Finally, for the scenario of ecological driving of intelligent vehicles, a fuel-efficient slope design (FSD) method was proposed based on the Nested Monte Carlo Tree Search algorithm, and the best fuel-efficient slope design was selected considering the balance of cut and fill factors. The results show that FSD can reduce the fuel consumption of passenger cars on the section by about 4.50%–6.52%; the fuel-efficient slope design considering the balance of cut and fill not only can reduce the fuel consumption of passenger cars on the section by about 5.21%, but also has the advantage of lower engineering volume. The research results conduce to establish a theory and standards for fuel-efficient slope design of highways suitable for ecological driving scenarios of intelligent vehicles, which can reduce the trip fuel consumption of highway traffic flow in the long run while considering traffic efficiency, and have great significance for reducing carbon emissions, saving travel costs, and protecting non-renewable resources.