Projects per year
In this paper, we consider the trajectory planning of an autonomous vehicle to cross an intersection within a given time interval. The vehicle communicates its sensor data to a central coordinator which then computes the trajectory for the given time horizon and sends it back to the vehicle. We consider a realistic scenario in which the communication links are unreliable, the evolution of the state has noise (e.g., due to the model simplification and environmental disturbances), and the observation is noisy (e.g., due to noisy sensing and/or delayed information). The intersection crossing is modeled as a chance constraint problem and the stochastic noise evolution is restricted by a terminal constraint. The communication impairments are modeled as packet drop probabilities and Kalman estimation techniques are used for predicting the states in the presence of state and observation noises. A robust sub-optimal solution is obtained using convex optimization methods which ensures that the intersection is crossed by the vehicle in the given time interval with very low chance of failure.
|Title of host publication||Proceedings of the 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019|
|Number of pages||8|
|Publication status||Published - 1 Sep 2019|
|MoE publication type||A4 Article in a conference publication|
|Event||Allerton Conference on Communication, Control, and Computing - Monticello, United States|
Duration: 29 Sep 2015 → 2 Oct 2015
Conference number: 53
|Conference||Allerton Conference on Communication, Control, and Computing|
|Period||29/09/2015 → 02/10/2015|
- Intersection crossing
- Robust trajectory planning
- Unreliable communications.
01/09/2018 → 31/08/2021
Project: Academy of Finland: Other research funding