The role of vehicle cues in road user-vehicle interaction

Background The aim of this study is to provide communication design basis for human-like Automated Vehicle (AV) while understanding the interaction between the pedestrians and human driven cars, and the interaction between the pedestrians and the AV using nonverbal vehicle cues (NVC). Based on the literature review, this study amalgamate NVCs as vehicle cues (including ‘dynamic cues’ and ‘physical attributes’) and driver cues. Within dynamic cues, interactions are dependent on vehicle kinematics (e.g. speed, distance), motion behaviours (e.g. a short deceleration, a well-balanced acceleration), and/or vehicle movement information (conflict lane and direction, vehicle trajectory). The identified cues are going to be used in development of (human-like) AV behaviour model and serve as an input to develop different pedestrian-vehicle interaction scenarios to understand what, why and how NVCs can be used by pedestrians to decide whether to cross or not. Method This study will be conducted using the Highly Immersive Kinematic Experimental Research (HIKER) pedestrian lab and the desktop driving simulator. In total, 50 participants will be recruited; 25 pedestrian (waiting to cross the road (or not) between the approaching cars in virtual environment) and 25 car drivers (sitting at the desktop simulator, following the car in front and maintaining at a specific speed). In half of the trials, the car will be engaged to automation mode and the driver will be asked to monitor the road and the behaviour of the car, whereas in the other half of the trials, the driver will be instructed to either yield or not yield to the pedestrian. Results Pedestrians’ mean accepted time gap, initiation time, percentage of crossing/yielding, crossing duration and safety margin will be calculated. Drivers’ lateral and longitudinal position and any emergency yielding behaviour will be recorded. In addition, videos of the crossings and driving will also be recorded. Conclusions The study will provide understanding of the role of implicit communication cues of vehicle used by pedestrians in making their crossing decisions with the traffic, and provide communication design basis for human-like AV to facilitate interaction with vulnerable road users.