Interaction-aware game-theoretic motion planning for automated vehicles using bi-level optimization
Planning an interactive and cooperative behavior in the vicinity of multiple decision-makers
is a challenging task. The game-theoretic perspective provides a suitable framework to …
is a challenging task. The game-theoretic perspective provides a suitable framework to …
Human-centric autonomous driving in an av-pedestrian interactive environment using svo
As Autonomous Vehicles (AV) are becoming a reality, the design of efficient motion control
algorithms will have to deal with the unpredictable and interactive nature of other road users …
algorithms will have to deal with the unpredictable and interactive nature of other road users …
Coordination and trajectory prediction for vehicle interactions via bayesian generative modeling
Coordination recognition and subtle pattern prediction of future trajectories play a significant
role when modeling interactive behaviors of multiple agents. Due to the essential property of …
role when modeling interactive behaviors of multiple agents. Due to the essential property of …
Learning responsibility allocations for safe human-robot interaction with applications to autonomous driving
Drivers have a responsibility to exercise reasonable care to avoid collision with other road
users. This assumed responsibility allows interacting agents to maintain safety without …
users. This assumed responsibility allows interacting agents to maintain safety without …
Generic prediction architecture considering both rational and irrational driving behaviors
Accurately predicting future behaviors of surrounding vehicles is an essential capability for
autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others …
autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others …
An interaction-aware evaluation method for highly automated vehicles
It is important to build a rigorous verification and validation (V&V) process to evaluate the
safety of highly automated vehicles (HAVs) before their wide deployment on public roads. In …
safety of highly automated vehicles (HAVs) before their wide deployment on public roads. In …
Interaction and decision making-aware motion planning using branch model predictive control
Motion planning for autonomous vehicles sharing the road with human drivers remains
challenging. The difficulty arises from three challenging aspects: human drivers are 1) multi …
challenging. The difficulty arises from three challenging aspects: human drivers are 1) multi …
Socially compatible control design of automated vehicle in mixed traffic
In the car-following scenarios, automated vehicles (AVs) usually plan motions without
considering the impacts of their actions on the following human drivers. This letter aims to …
considering the impacts of their actions on the following human drivers. This letter aims to …
Interactive planning for autonomous urban driving in adversarial scenarios
Autonomous urban driving among human-driven cars requires a holistic understanding of
road rules, driver intents and driving styles. This is challenging as a short-term, single …
road rules, driver intents and driving styles. This is challenging as a short-term, single …
Bounded risk-sensitive markov games: Forward policy design and inverse reward learning with iterative reasoning and cumulative prospect theory
Classical game-theoretic approaches for multi-agent systems in both the forward policy
design problem and the inverse reward learning problem often make strong rationality …
design problem and the inverse reward learning problem often make strong rationality …