Vehicle Localization and Control on Roads with Prior Grade Map
This work addresses vehicle localization for autonomous systems in GPS-denied conditions, but it is incremental as it builds on existing map-aided methods.
The paper tackled vehicle localization in GPS-denied environments by using prior road grade maps and on-board sensors to estimate longitudinal position, and validated it in a hierarchical control system for energy-efficient velocity planning, achieving accurate real-time performance in simulations and experiments.
We propose a map-aided vehicle localization method for GPS-denied environments. This approach exploits prior knowledge of the road grade map and vehicle on-board sensor measurements to accurately estimate the longitudinal position of the vehicle. Real-time localization is crucial to systems that utilize position-dependent information for planning and control. We validate the effectiveness of the localization method on a hierarchical control system. The higher level planner optimizes the vehicle velocity to minimize the energy consumption for a given route by employing traffic condition and road grade data. The lower level is a cruise control system that tracks the position-dependent optimal reference velocity. Performance of the proposed localization algorithm is evaluated using both simulations and experiments.