Search Results

After the COVID-19 pandemic, leisure activities and cultures have undergone significant transformations. Particularly, there has been an increased demand for outdoor camping. Consequently, the need for capabilities that allow vehicles to navigate not only paved roads but also unpaved and rugged terrains has arisen. In this study, we aim to address this demand by utilizing AI to introduce a 'Stuck Probability Estimation Algorithm' for vehicles on off-road. To estimate the 'Stuck Probability' of a vehicle, a mathematical model representing vehicle behavior is essential. The behavior of off-road driving vehicles can be characterized in two main aspects: firstly, the harshness of the terrain (how uneven and rugged it is), and secondly, the extent of wheel slip affecting the vehicle's traction.

This paper describes the effects of diverse driving modes and vehicle component characteristics impact on fuel efficiency and emissions of light commercial vehicles. The AVL's vehicle and powertrain system level simulation tool (CRUISE) was adopted in this study. The main input data such as the fuel consumption & emission map were based on the experimental value and vehicle components characteristic data (full load characteristic curves, gear shifting position curves, torque conversion curve etc.) and basic specifications (gross weight, gear ratio, tire radius etc.) were used based on the database or suggested value. The test database for two diesel vehicles adopted whether prediction accuracy of simulation data were converged in acceptable range. These data had been acquired from the portable emission measurement system, the exhaust emission and operating conditions (engine speed, vehicle speed, pedal position etc.) were acquired at each time step.