Effects of Augmented Situational Awareness on Driver Trust in Semi-Autonomous Vehicle Operation

Although autonomy has the potential to help military drivers travel safely while performing other tasks, many drivers refuse to rely on the technology. Military drivers sometimes fail to leverage a vehicle’s autonomy because of a lack of trust. To address this issue, the current study examines whether augmenting the driver’s situational awareness will promote their trust in the autonomy. Results of this study are expected to provide new insights into promoting trust and acceptance of autonomy in military settings. INTRODUCTION Autonomous and semi-autonomous vehicles have the potential to help drivers successfully and safely complete many military missions while providing the drivers with the flexibility to address other pressing issues not possible while actively driving [12]. Following the SAE definition (SAE J3016), driving automation systems are those that “perform part or all of the dynamic driving task on a sustained basis”, ranging in level from no driving automation (level 0) to full driving automation (level 5). The “dynamic driving task” includes things such as sensing, navigation, steering, and speed control. Unfortunately, drivers have failed to fully leverage a vehicle’s autonomy because of a lack of trust in the vehicle’s autonomy [5]. Trust in a vehicle’s autonomy allows the driver to handle the uncertainty and risk associated with giving driving control to the vehicle’s autonomy [3]. Generally, trust is one of the most vital components in understanding how to promote successful teaming between humans and robots [6]. Specifically, drivers need to be comfortable relying on the vehicle’s autonomy in order to make better decisions regarding whether or not to employ it [3]. Trust in automation has been studied in the past, primarily in the domains of aviation and production processes. However, less is known about trust in automated vehicles specifically. Proceedings of the 2017 Ground Vehicle Systems Engineering and Technology Symposium (GVSETS) [Unclassified] Effects of Augmented Situational Awareness on Driver Trust in Semi-Autonomous Vehicle Operation, Petersen et al. Page 2 of 7 Previously developed methods for evaluating trust in automation provide a good starting place for considering this specific domain, but there are three major shortcomings. Firstly, models of human trust in autonomy typically only consider the human's trust in the autonomy [1]. Yet, trust between two agents is reciprocal and mutual [13], especially given the highly sophisticated sensing, decision-making, and acting functions that autonomous vehicles are expected to have in the future. Second, current models of trust between a driver and the vehicle’s autonomy are neither contextualized nor personalized [8]. Finally, the degree to which mutual trust between the driver and the vehicle’s autonomy exists and changes as a function of how expectations are met. Prior research has recognized the importance of human expectations of automation in determining the trust humans have in automation [3]. Less is known about what expectations drivers have for their vehicle’s autonomy in general, and no known research has been conducted that has examined the expectations a vehicle’s autonomy should have for its driver. This pilot study is positioned to lay the groundwork for developing sophisticated and robust models of mutual trust between driver and semi-autonomous vehicle. The ultimate goal of the larger project is to develop methods to predict when a driver is likely to seize control from or relinquish control to the vehicle and to predict when the vehicle should relinquish control to or seize control from the driver. The purpose of this study is to begin this investigation by examining how a driver’s trust in their semi-autonomous vehicle is impacted when the driver’s situational awareness is purposefully augmented by the vehicle. The hypothesis of this study is that by augmenting the driver’s situational awareness using effective communication, the driver will demonstrate more trust in the vehicle’s autonomous capabilities. METHOD This study is designed to evaluate driver trust in semi-autonomous driving when the driver’s situational awareness is purposefully augmented by the vehicle. The study employs an experimental design using three different conditions of communication content from the vehicle. These conditions will be counterbalanced using a Latin Square design to minimize learning and ordering effects. Participants will be asked to operate a simulated vehicle while attending to a visually demanding non-driving task. Trust will be evaluated from survey responses and analysis of