A Probabilistic Framework for Trajectory Prediction in Traffic Utilizing Driver Characterization

While autonomously operated vehicles are on the horizon, they will be required to share the road with human drivers for a foreseeable future. To ensure safe operation beyond human capabilities, interaction with other traffic participants will be required to navigate cooperatively through complex traffic situations. Identification and characterization of driving styles in combination with the behavior of other traffic participants is anticipated to aid in effectively analyzing risks under autonomous driving. This study presents a novel, interaction-aware framework fulfilling this need for combined behavior identification and driving style characterization of other participants.

[1]  Pierluigi Pisu,et al.  Evaluation of Navigation in Mobile Robots for Long-Term Autonomy in Automotive Manufacturing Environments , 2019 .

[2]  Jerome M. Lutin,et al.  Not if, but when: Autonomous driving and the future of transit , 2018 .

[3]  Rüdiger Dillmann,et al.  A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[4]  Mashrur Chowdhury,et al.  Review of Microscopic Lane-Changing Models and Future Research Opportunities , 2013, IEEE Transactions on Intelligent Transportation Systems.

[5]  Dizan Vasquez,et al.  A survey on motion prediction and risk assessment for intelligent vehicles , 2014, ROBOMECH Journal.

[6]  John J. Leonard,et al.  Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age , 2016, IEEE Transactions on Robotics.

[7]  Luke Fletcher,et al.  The MIT - Cornell Collision and Why It Happened , 2009, The DARPA Urban Challenge.

[8]  Pierluigi Pisu,et al.  Behavior Identification and Prediction for a Probabilistic Risk Framework , 2019, Volume 2: Modeling and Control of Engine and Aftertreatment Systems; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Validation; Motion Planning and Tracking Control; Multi-Agent and Networked Systems; Renewable and Smart Energ.