Using GPU to Accelerate Backward Induction for Vehicle Speed Optimal Control
2022-01-0091
03/29/2022
- Event
- Content
- This paper proposes a method to adapt backward induction, which is used to solve the vehicle speed optimal control problem for energy efficiency, to a computer with GPU to accelerate the computation. A common application of this type of problem is to control a vehicle on a given route with surrounding vehicles, road grades, traffic signals, stop signs, speed limits, and other conditions. Several indicators can be used to determine the performance of the controller, such as the driving speed smoothness, time consumption to a given target, or the energy consumption of the trip. Solving this optimization problem globally by backward induction is time-consuming, due to its’ large searching space of the vehicle’s distance, velocity, and acceleration. The proposed method converts the single thread implementation to a parallel process that runs on a consumer-level GPU. This is done by choosing the problem scale, separate independent sub-processes, and prune the data to accommodate the GPU programming requirement. The method is tested on a simulated route with a leading vehicle, a traffic light, and speed limits. The historical behaviors of the leading vehicle are known and they are used to predict its future behaviors in a stochastic way. Comparing to the CPU-based backward induction, the proposed GPU-based version solves the given problem 15 to 30 times faster, depends on the preset granularities of variables.
- Citation
- Ma, Z., and Zeng, X., "Using GPU to Accelerate Backward Induction for Vehicle Speed Optimal Control," SAE Technical Paper 2022-01-0091, 2022, .