Using speech, GUIs and buttons in police vehicles

Abstract

The Project54 mobile system for law enforcement developed at the University of New Hampshire integrates the control of disparate law enforcement devices such as radar, VHF radio, video, and emergency lights and siren. In addition it provides access to state and national law enforcement databases via wireless data queries. Officers using Project54 are free to intermix three different user interface modes: the device native controls; an LCD touchscreen with keyboard and mouse; and voice commands with voice feedback. The Project54 system was utilized by the New Hampshire State Police agency wide for a period of seven years spanning 2005 through 2011. This paper presents an analysis of user preferences in regard to user interface modes during the three years 2009 through 2011, obtained through logs of daily system use in approximately 200 police cruisers. Results indicate that most officers chose to use the touch screen controls frequently instead of the device native controls, but only a minority chose to use the speech command interface.

A Model Relating Pupil Diameter to Mental Workload and Lighting Conditions

“…Estimating the user's workload is helpful for many situations where people interact with computing devices or machines. One example is the automotive domain where it is important not to overload the driver as they interact with in-vehicle devices [28] or communicate with remote conversants [21,38], since performance degrades with increasing workload [6]. With automated driving modes and non-driving-related activities [37], workload estimation can be useful to track and support the driver's reengagement in the driving task [20].…”

Measuring Cognitive Workload of Novice Law Enforcement Officers in a Naturalistic Driving Study

“…Prior studies have found officers' use of in-vehicle technologies while driving (Yager et al, 2015), fatigue (Vila & Kenney, 2002), and lack of sufficient training in handling high-demand situations (e.g., pursuit situations, multi-tasking) (Hembroff et al, 2018) are major contributors of motor vehicle crashes for LEOs. In addition, LEOs are continuously surrounded by the high noise level inside the police vehicles which can lead to poor speech recognition, and complexity of tasks which can interrupt their concentration on tasks and ultimately increase their CW (Miller & Kun, 2013;Shahini et al, 2020).…”