This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Movement Prediction Hypotheses for Pedestrians and Trajectory Planning for Cooperative Driving Systems

Journal Article
12-02-01-0002
ISSN: 2574-0741, e-ISSN: 2574-075X
Published December 19, 2018 by SAE International in United States
Movement Prediction Hypotheses for Pedestrians and Trajectory Planning for Cooperative Driving Systems
Sector:
Citation: Hartmann, M., Stolz, M., and Watzenig, D., "Movement Prediction Hypotheses for Pedestrians and Trajectory Planning for Cooperative Driving Systems," SAE Intl. J CAV 2(1):17-26, 2019, https://doi.org/10.4271/12-02-01-0002.
Language: English

Abstract:

It is a challenge to find a safe trajectory for automated vehicles in urban environments with pedestrians. The prediction of future movements with 100% certainty is impossible, if the intention is unknown. A Gaussian process approach is used to formulate future movement hypotheses of the pedestrian based on historical movements. A mixed integer linear programming (MILP) optimization approach is used for the trajectory planning of the vehicle. The collision probability between the ego-vehicle and pedestrian is used as constraints in the optimization. This approach is useful for cooperative vehicle systems, with historical movement data in a fixed urban environment (e.g., intersection) and the premise that pedestrians follow typical movement data.