Human factors in police mobile computer terminals: A systematic review and survey of recent literature, guideline formulation, and future research directions

Highlights

• MCT improves officer productivity but the system has increased physical discomfort.

• Current MCT interfaces are not optimized for use while driving.

• Studies found MCTs to increase officer driving distraction and compromise safety.

• This study proposed a set of design guidelines and an enhanced MCT interface.

Abstract

The objectives of this research were to: (1) identify Mobile Computer Terminal (MCT) human factors issues, (2) formulate guidelines and an enhanced MCT for improving interface design and implementation in police patrols, and (3) identify areas of future research to fill gaps in the literature. A systematic literature search was conducted leading to results categorized in four groups including: productivity, physical discomfort, interface usability, and driving distraction. Although MCT use has increased officer productivity, several usability issues need to be resolved. The MCT has also increased officer physical discomfort and distraction. MCT design and implementation guidelines that resolve human factors issues in police patrols were identified along with an enhanced design concept. Guidelines for MCT design were validated with an online survey completed by 81 police officers. Future research directions were proposed to recognize police officer needs and work context.

Introduction

In the United States, a majority of police vehicles contain a mobile computer terminal (MCT). The MCT is a computer in the vehicle accessible from the driver's seat that provides information to a police officer—information that, prior to MCTs, would have to be requested via radio communication, stored in the officer's working memory, and/or potentially required repeated information requests. The MCT provides a portal for communication among responders, verbal and auditory notifications, Global Positioning System data, information relevant to a case, personnel assignment information, video recording module, and other task-specific functionalities (such as plate number checking). An example of MCT implemented in police vehicles is shown in Fig. 1.

While the MCT was introduced to make the officer more efficient in specific tasks, there are several potential human factors issues that need to be addressed to ensure there is no degradation in safety associated with its use. In our previous empirical investigations using driving simulations (Zahabi and Kaber, 2018a; 2018b), we investigated the effect of a specific MCT task (i.e., reading plate number information) on officer driving distraction and identified the most visually and cognitively demanding MCT tasks using decision tree analysis and cognitive performance modeling approaches. Although not a focus of the work, officers in those studies anecdotally emphasized MCT effects on their productivity and physical discomfort. However, the data collected in our previous studies were from one police department, so there is a need to investigate these issues with more diverse populations to derive more generalizable recommendations for MCT design. In this study, we reviewed investigations conducted in different states in the US and in collaboration with different police departments to provide generalizable guidelines. Furthermore, the guidelines and the enhanced MCT interface developed in our previous studies were focused on one specific MCT task (reading plate number information), whereas the guidelines provided in this study are comprehensive and target various issues including police training and education, software/hardware, MCT location, MCT interface design, vehicle configuration, etc. Given this background, the current study focuses on the following potential human factors issues related to officer use of MCTs: (1) officer productivity, (2) physical discomfort, (3) MCT interface usability, and (4) driver distraction.

The MCT is a form of information automation, replacing tasks that had to be done manually and/or via radio communication with another remote party. The goal of any form of automation is to, “carry out more or less independently a task that would otherwise require increased human attention or effort” (Billings, 1996). The officers interviewed by Zahabi and Kaber (2018a) stated that MCTs made their jobs easier and made them more productive, but there exists a need to empirically ensure that MCTs increase officer productivity in the tasks that they are designed to support.

As mentioned in the introduction, the officers interviewed by Zahabi and Kaber (2018a) emphasized the physical discomfort caused by the MCT in the vehicle. Mitsopoulos-Rubens et al. (2009) conducted a survey study with 476 police officers and found 75% of responders indicated spending at least half of their shift in police vehicles and about 70% of these officers mentioned spending at least 75% of their shifts in vehicles. Police vehicles are not designed to include a computer workspace, so there are several aspects of the vehicle that could promote discomfort while using the MCT. For example, displays need to be positioned so that they do not obstruct the driver's out-window view or access to driving controls, requiring the police officer to turn his/her head to use the MCT and potentially promoting neck stiffness. In addition, it may not be possible to install arm rests, promoting discomfort in the shoulders and upper arms (Helander, 2005). Other aspects of the vehicle that could cause physical discomfort include noise, vibration, improper lighting, screen glare, and screen reflections (Sanders and McCormick, 1993; Wickens et al., 2004). Research has shown that the design of vehicle seats and the physical demands of operating a computer in a vehicle constrain postural adjustments more than office-based seated work (Callaghan et al., 2010). Few investigations have assessed occupational issues and muscular disorders that officers experience due to the use of MCTs in their vehicles.

A well-designed interface promotes effectiveness, efficiency, and satisfaction in a specified context for use (International Organization for Standardization, 1998). Police departments have reported concerns about the usability of MCT interfaces (e.g., complexity, working memory overload; Zahabi and Kaber, 2018a), and designs that are non-user centered (Marcus and Gasperini, 2006). Work needs to be done to ensure usability findings are generalizable to MCTs used by the police officer population as a whole.

Although the MCT is not designed to use while the vehicle is in motion, several police officers admit using it while driving (e.g., Callander and Zorman, 2007). Many state- and city-level crash reports have identified in-vehicle distraction as the main cause of law enforcement accidents. Yager et al. (2015) collected most of these data through public information requests to police departments in different metropolitan areas across United States. For example, in a report from the Austin (Texas) police department from 2010 to 2014, there were 48 patrol crashes. In 25 out of 48 cases, the police officer was interacting with the MCT while driving, and in 8 other instances, the officers were interacting with a cell phone or other on-board equipment. The Kansas City (Missouri) Police Department identified 181 crashes from 2009 to 2014 in which in-vehicle distraction was the main cause for these crashes. In another report from 378 police-involved crash claims between 2006 and 2010 in Minnesota, 7% of crashes were reportedly attributed to officer use of MCT while driving, the most frequently cited technology (Citrowski et al., 2011).

MCTs are also used in other emergency vehicles including ambulances and fire trucks and have been found to be one of the major causes of accidents. For example, Illinois Department of Transportation (DOT) recorded a total of 137 emergency vehicle (police, ambulance, fire trucks) crashes that were caused by in-vehicle distraction and use of electronic devices from 2010 to 2012. In Texas, 1021 crashes of emergency vehicles were reported from 2010 to 2014 as a result of distraction/inattention (Yager et al., 2015). In South Carolina, 803 emergency vehicle crashes occurred between the year 2001 and 2010. Fatigue and distraction were mentioned as main causes of these accidents (Abdelwanis, 2013). Although many studies have assessed the use of in-vehicle technologies on civilian drivers (e.g., Kaber et al., 2012; Salvucci et al., 2007), there are few investigations that have focused on distraction due to in-vehicle technology in emergency vehicles.

Although the National Highway Traffic Safety Administration (National Highway Traffic Safety Administration, 2012c, National Highway Traffic Safety Administration, 2012b, National Highway Traffic Safety Administration, 2012a) and other researchers (e.g., Llaneras and Singer, 2002; Pankok and Kaber, 2018; Stevens et al., 2002) provide guidelines for design and implementation of in-vehicle technology for civilian drivers (i.e., drivers with regular non-commercial driver license), there is no established set of guidelines for such systems in emergency vehicles. There are several differences between vehicle and driver states among the police and private operator domains. These differences include temporal demands placed on officers, travel speeds of vehicles, and the level of driver training. Prior studies have found that officers’ psychological stress (measured by above-resting heart rate) increases as the severity of the pursuit driving condition increases (Anderson et al., 2002). Police officers need to access critical case information before arriving on scene, which poses higher temporal demands as compared to use of typical in-vehicle technologies, such as media players or navigation aids. Because technologies used in emergency vehicles are more complex than technologies used by civilian drivers, they require greater physical and mental workload for officers. In addition, the study by Liu and Donmez (2011) based on national crash database showed that crashes involving emergency vehicles due to in-vehicle sources are more severe than crashes involving civilian driver distraction by in-vehicle sources. Although the crash data were based on observation and did not provide causation, the increased severity of crashes might be due to the complexity of police in-vehicle technologies and greater physical and mental workload for officers when using such devices as compared to traditional information sources. Therefore, there is a need to investigate human factors issues in design and implementation of technologies in emergency vehicles. Since the MCT is the most important and frequently used in-vehicle technology by first responders (Zahabi and Kaber, 2018a), this study examined the analysis of this device and how the design and implementation of such technology can be improved. The focus of the current study is mainly on the MCT use for police officers since many police vehicles are operated by a single individual, as compared to other emergency vehicles that have two people in the vehicle. In addition, crash reports have found police vehicles to be involved in substantially more crashes as compared to fire trucks and EMS (NHTSA, 2010, 2011, National Highway Traffic Safety Administration, 2012a, National Highway Traffic Safety Administration, 2012b, National Highway Traffic Safety Administration, 2012c). Therefore, the objectives of this research were to: (1) identify MCT human factors issues, (2) formulate guidelines and an enhanced MCT for improving interface design and implementation in police patrols, and (3) identify areas of future research to fill the current gaps in the literature.