Robust trajectory planning of autonomous vehicles at intersections with communication impairments
Paper in proceeding, 2019

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.

unreliable communications.

Intersection crossing

robust trajectory planning


Neha Chohan

Aalto University

Mahmood Nazari

Student at Chalmers

Henk Wymeersch

Aalto University

Themistoklis Charalambous

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019

832-839 8919923
978-172813151-1 (ISBN)

57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
Monticello, USA,

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing



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