Abstract
We present our work on autonomous vehicles in an urban environment to provide mobility-on-demand as a solution to the first and last mile problem. The software architecture for our vehicles is reviewed with focus on new developments of speed and steering control algorithms to ensure robust performance for autonomous driving. For speed control, a brake/throttle switching controller based on velocity error and desired acceleration is implemented to achieve fast speed response without excessive switching. An iterative learning algorithm is used to train feedforward signals which are then used to compensate the repeated disturbances over a fixed route. For steering control, a revised pure pursuit steering control algorithm is designed to improve path tracking performance. The methods are validated though on-road experiments which demonstrate a speed control that is robust against changing road grade and a steering control that has smaller cross-track errors.
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Acknowledgment
This research was supported by the Future Urban Mobility project of the Singapore-MIT Alliance for Research and Technology (SMART) Center, with funding from Singapore’s National Research Foundation (NRF).
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Eng, Y.H., Andersen, H., Pendleton, S.D., Ang, M.H., Rus, D. (2017). Realizing Robust Control of Autonomous Vehicles. In: Kulić, D., Nakamura, Y., Khatib, O., Venture, G. (eds) 2016 International Symposium on Experimental Robotics. ISER 2016. Springer Proceedings in Advanced Robotics, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-50115-4_33
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DOI: https://doi.org/10.1007/978-3-319-50115-4_33
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