Program Profile: Automated Vehicle Locator (AVL) Information to Aid Patrol Allocations (Dallas, Texas)

This program examined whether access to deployment data collected through technology impacted police commanders’ management of resources and led to reductions in crime. The program is rated Ineffective. There was a statistically significant decrease in crime at the hot spot level. However, there were no significant differences in crime at the beat level, in consistency between patrols assigned and delivered per beat and per hot spot, or in number of hours of patrol on beats or in hot spots.

An Ineffective rating implies that implementing the program is unlikely to result in the intended outcome(s).

This program's rating is based on evidence that includes at least one high-quality randomized controlled trial.

An Ineffective rating implies that implementing the program is unlikely to result in the intended outcome(s).

This program's rating is based on evidence that includes at least one high-quality randomized controlled trial.

Program Goals /Program Components

The Dallas Automated Vehicle Locator (AVL) experiment evaluated how access to and use of deployment data collected through AVL technology impacted police commanders’ management of police resources and whether this data-informed management strategy could lead to a reduction in crime.

The AVL experiment was implemented to address the gap in knowledge surrounding allocation and concentration of police patrols and resources. Police commanders’ were given access to AVL-measured deployment information, which was hypothesized to result in better management of police resources and thereby lead to a reduction in crime. The experiment employed a hotspot-policing strategy to detect and prevent criminal activity more effectively.

The first component of the program involved equipping police vehicles with AVL technology. As a police vehicle moved, a data point was created every 300 meters for moving vehicles, or every 15 seconds for stationary vehicles. Information collected on the monitored vehicles included longitude/latitude, speed, and a vehicle identification number. These data were entered into a computer program that computed aggregate information summarizing how much time was spent by police in quarter-mile-square grid cells across the city. This information was then also computed for larger beats and for hotspots (which served as the units of analysis in this experiment). 

The second component of the experiment involved disseminating the aggregated AVL information to division commanders weekly. The objective was to see if the detailed information provided to the division commanders would allow them to allocate police patrol resources more effectively and to ensure that an appropriate level of patrol was concentrated in crime hotspots that had been identified during Compstat meetings.

Key Personnel/Target Sites

Participants included members of the Dallas Police Department (DPD), which comprised 3,266 sworn officers and 617 civilians. Dallas is divided into seven patrol divisions across a 385-square-mile area and has a population of 1.2 million. A total of 232 beats were used in the experiment. Beats range in size from 0.13 to 8.84 square miles, with an average of 1.40 square miles. A total of 873 vehicles were equipped with AVL technology.

AVL deployment information collected from DPD vehicles on patrol was disseminated to the division commanders, who were responsible for delegating patrol assignments. The DPD had a “directed patrol” philosophy, which means that division commanders are responsible for actively manipulating patrols in response to emerging problems. This process was reviewed weekly. The framework underlying this philosophy is that vehicles or other modes of police presence should be available to service each beat at all times to provide efficient response time to calls for service (Weisburd et al. 2015).

Study

Weisburd and colleagues (2015) used a block-randomized experimental design in their evaluation of the Automated Vehicle Locator (AVL) technology. The experiment took place in Dallas, Texas, which is the third-largest city in the state and ninth largest in the country.

Study participants included members of the Dallas Police Department (DPD). The city is divided into seven patrol divisions across a 385-square-mile area and has a population of 1.2 million, the majority of which (51 percent) are white. A total of 232 beats were used in the study: 21 very low crime beats, 94 low crime beats, 100 medium crime beats, and 17 high crime beats. A beat ranges in size from 0.13 to 8.84 square miles, but on average is about 1.40 square miles. A total of 873 vehicles were equipped with AVL technology.

Trajectory analysis was used to identify beats with similar crime trajectories. Each beat within a trajectory was randomly assigned to a treatment or control group. There were 116 beats in the treatment group and 116 beats in the control group. The treatment included weekly dissemination of AVL-collected deployment information, at both the beat level and the hot spot level, to DPD division commanders. AVL deployment information was not collected for the control condition beats and hotspots, and police patrolled these areas as usual. The experiment lasted a total of 13 weeks.

Data were collected at both the beat level and hot spot level. Beat-level data were collected using a web-based, intranet application only accessible internally by DPD. Personnel entered the intended deployment information based on available resources. This information was compared with actual deployment dosage measured via AVL data collected from police vehicles. Hot spot-level data were collected via weekly Compstat meetings hosted by division commanders. A form was developed and used to capture high-crime locations that would be focused on that week. Actual patrol dosage in hot spots was measured via AVL data collected from the vehicles. AVL data were measured for each cell within a grid consisting of quarter-mile cells that spanned the whole city. The block randomized design of the study helped to account for the large variation in crime rates across beats.

Two categories of outcomes were measured; the first dealt with the impact of AVL information on police patrols and the second with the impact on crime via the altered patrol assignments. The police patrol outcomes were measured by investigating if AVL information led to an increase in patrol expected by commanders, and if those expectations were then actualized by police. Patrol dosage was measured based on the number of hours of patrol. The crime measure included homicide, rape, robbery, aggravated assault, burglary, theft, unauthorized use of a motor vehicle, auto theft, burglary of a motor vehicle, narcotics/drugs, vandalism/criminal mischief, and assault. No subgroup analyses were conducted.

These sources were used in the development of the program profile: