Autonomous Driving: Framework for Pedestrian Intention Estimationin a Real World Scenario
This addresses safety and interaction challenges for autonomous vehicles in real-world scenarios, but appears incremental as it builds on existing intention estimation methods.
The paper tackled the problem of autonomous vehicles lacking eye contact with pedestrians by developing a framework to estimate pedestrian crossing intentions, which was tested in a real vehicle and shown to be feasible in field tests.
Rapid advancements in driver-assistance technology will lead to the integration of fully autonomous vehicles on our roads that will interact with other road users. To address the problem that driverless vehicles make interaction through eye contact impossible, we describe a framework for estimating the crossing intentions of pedestrians in order to reduce the uncertainty that the lack of eye contact between road users creates. The framework was deployed in a real vehicle and tested with three experimental cases that showed a variety of communication messages to pedestrians in a shared space scenario. Results from the performed field tests showed the feasibility of the presented approach.