ETAPS

• April 27th, 2015
• in

The Alabama Department of Revenue’s Electronic Title Application and Processing System (ETAPS) is a web based application that allows designated agents of the state to electronically enter and submit vehicle title applications. It makes the application process faster and more efficient by including many validation rules that help avoid errors and lowers the chance of an application being rejected. ETAPS allows for integration with dealer management software, which can cut down on duplicate work by allowing the dealership’s existing software to push an application directly to the system. Applications coming from dealer software pass through the same validations as those that are directly typed, which cuts down on the time and effort at both ends of the process: it is easier for agents to create and submit applications and it is easier for the Department of Revenue to review them.

OIVS

• April 27th, 2015
• in

The goal of the Alabama Online Insurance Verification System (OIVS) was to create an effective method for implementing the Mandatory Liability Insurance (MLI) law that became effective on January 1, 2013. Development was a joint effort of CAPS and the Alabama Department of Revenue (ADOR) in FY2013.

OIVS includes a management portal and complete back-end infrastructure to support the new requirements of the law, including a role-based online portal for end-to-end management of the MLI process. It implemented a case management infrastructure so that all MLI case correspondences (calls, payments, images, etc.) are now being appropriately logged and retrieved. Citizens can now go online and respond to MLI issues that they have.

We continue to maintain, secure, and expand (as needed) the back-end servers, network, and security appliances that host various ADOR applications in order to provide a reliable, secure and redundant data storage and web infrastructure for ADOR.

CAPS has provided marketing campaigns to raise awareness about the forthcoming changes to the Mandatory Liability Insurance laws, chiefly the development and deployment of the Online Insurance Verification System (OIVS) and the enforcement mechanisms that will be put in place as a result.

The Alabama OIVS is integrated within the Motor Vehicle Title, Registration, and Insurance Portal (MVTRIP) system.

MVTRIP

• April 27th, 2015
• in

The Motor Vehicle Title, Registration, and Insurance Portal (MVTRIP) system was developed for the Alabama Department of Revenue (ADOR) in the FY2013 time frame. MVTRIP implemented the next evolution of Alabama’s vehicle titling system.  

Implementation meant the roll out of a new vehicle registration system that replaced the existing system and supported the addition of state and local government tags. MVTRIP provides the overall means of accessing the registration and title data that extended to user authentication and the generation of statistical access and records searches. 

MVTRIP is integrated with a Mandatory Licensing Insurance (MLI) verification component called OIVS.  Capabilities were also extended to:

• dealer licensing
• unclaimed vehicles
• scrap vehicle disposition
• personalized tag reservations
• document imaging

LETSGo

• March 19th, 2014
• in

The Law Enforcement Tactical System (LETS) is a secure web-based search engine that has been designed to provide law enforcement and criminal justice agencies information about individuals and vehicles by searching various databases. LETS is an integration mechanism for vehicle, driver, and violation data and even produces photos to aid in positive identification of apprehended or wanted individuals. It was released in mid-January of 2003 and it rapidly became a major tool. It currently has over 1,000 agencies and over 14,000 users and its success stories are numerous.

LETS is available to all law enforcement agencies over the Internet and to officers in the field through mobile devices used in patrol cars. LETSGo is a mobile version of LETS that is optimized for usage over air cards in the patrol cars. This version has commercial vehicle information and has a built-in text to speech engine that produces voice readout of the critical summary information. LETSGo is now under the domain of the Alabama Criminal Justice Information Center who directs CAPS on LETSGo development and enhancements

Features

• Built-in text to speech engine that produces voice readout of the critical summary information
• Commercial vehicle and carrier data
• Fast information returns
• Searches approximately 30 databases
• Integrated into MOVE (Mobile Officer Virtual Environment)
• Online Insurance Verification
• Commercial vehicle data
• Carrier data: detailed information about carriers and their associated vehicles

Download the LETSGo Flyer

CARE

• March 19th, 2014
• in

CARE Overview Video

Features

• • Statistical Generation: CARE retrieves summary information for the entire database or for any part (or subset) of it. Its Filters Menu allows the creation or combination of filters that restrict consideration to any specific subset of the database (e.g., alcohol, pedestrian, bicycle, motorcycle, particular counties or other geographical areas). Any attribute, or any combination of attributes, can be used to create filters, enabling the easy generation of literally any statistic.

• • Data Analysis: Charts and graphical displays are produced for any or all variables in the database. A frequency output of any variable or a cross-tabulation of any two variables is instantly displayed. (Note that the words variables and attributes are used interchangeably – for crash records, these are essentially the data elements collected on the crash report form.)

• • Information Mining Capability: One of the most useful capabilities of CARE lies in its unique information mining capability, called IMPACT. IMPACT automatically generates information from the data without users having to specify queries or, for that matter, even know what the attributes are in their databases. All the user has to do is to specify one or two filters. IMPACT can compare two subsets of data using a single filter, e.g., alcohol crashes vs. non-alcohol crashes. An example of this is given below for the impact speed attribute. In this example, the red bars in the chart are for the alcohol crash subset. The blue bars in the chart are for non-alcohol crashes. It is quite clear that the alcohol crashes have significantly and dramatically higher impact speeds, which clearly accounts for their higher severities.
    Users do not have to specify the attributes to be processed by IMPACT. Any or all can be processed simultaneously, and the results can be ordered according to the most significant first. Statistical tests are performed for all IMPACT results. Clearly, IMPACT provides the the ability to obtain crucial information from the database without having to generate endless queries. Latent information is mined out of the database, analyzed, and instantly presented in both graphical and tabular charts. The results are prioritized indicating areas where countermeasures will provide maximum gain. The information discovery potential is unlimited, offering decision-makers unprecedented information-generation power from their data warehouses.

• • Non-Categorical Variables: CARE is not limited to what are called “categorical” variables, i.e., those with discrete values, such as time of day, day of the week, contributing circumstances. Some applications require continuous variables, such as temperatures, distances or other such measurements. Non-categorical variables can be specified to the CARE ETL when creating a CARE dataset, allowing a list of values directly from the available raw data as opposed to being restricted to a known list of discrete values or ranges.

• • Narrative Data Searching: CARE can process narrative descriptions, such as that within traffic crash narratives. The goal is to generate filters to identify those records where particular words of word combinations occur. This can be quite useful since sometimes the narrative contains information that is not in the categorical variables. For example, a categorical variable may contain the fact that a deer was struck. However, it is rare that any categorical variable will contain the fact that a driver was taking evasive action to avoid a deer. This information is contained strictly in the narrative. CARE enables a word or phrase to be used to create the filter from the narrative. This filter can be combined (ORed) with all other related filters to produce the subset desired. In order to assure that the words or phrases are being used appropriately, users can view the context and either approve or disapprove the particular record. At that point, the “Generate Filter” button creates a filter that includes all of the records selected.

• • Hotspot Determination: A hotspot is a location that has a particularly high crash history, sometimes of a particular type of crash (e.g., hotspots for selective enforcement might be defined as those with excessive crashes caused by speed or alcohol). CARE uses a variety of techniques for identifying hotspots. As an example, for mileposted routes, one method is for users to specify a length of the segment and the number of crashes within the segment for it to qualify. For example, in the display given below, the criteria specified was a minimum of 20 crashes in 0.4 miles (note that this is over a four-year period). A map is given along with the strip map to assist engineers in locating the hotspots.

• • Report Generation: There are many options for producing various helpful reports with just the click of the mouse. Of course, the major reason for identifying hotspots is so that some countermeasure can be applied. Note the “Reports” icon in the upper right corner of the display above. This button leads to a very large number of reports that officers or engineers can take to the location in order to run down just exactly what the problems are. These reports range from overall summaries to detailed information on a per-crash basis. Any of the outputs discussed above can be exported to Microsoft Office products, including Word and Excel, enabling them to be formatted for reports or processed further.

• • Collision Diagram Generation: Intersection Magic is a powerful collision diagram generator that has been integrated into CARE to automatically draw collision diagrams for any location specified by CARE. This avoids the issues of having to understand all of the database ramifications of collision diagram generation, since once the location is defined within CARE the collision diagram is generated at the click of the mouse. A separate license must be obtained from Pd’ Programming in order to use this feature; Alabama has obtained a statewide license for the use of Intersection Magic.

• • GIS Integration: Quite analogous to the collision diagram integration, ESRI/ArcGIS has been integrated into CARE enabling analysis results from CARE to be mapped using ArcView with the click of the mouse. In addition, the GIS map can be used to create a filter so that a subset of the mapped crashes can be further analyzed in CARE. For more information on this aspect of CARE’s capabilities, see Crash Mapping Flyer.

• • Open Road: This application links roadway images to route-event data which is generated by the standard CARE software. Users can select a location on a mileposted route and view images along that route just as if they were driving down the road, as shown below.

    

    Along with the roadway images, OpenRoad also displays “events” that occur along the route. An event is defined as any object or occurrence that can be located with a specific route and milepost. Events are represented symbolically by a shape and color. Different types of events can be visually displayed with different symbols. For example, in the example above, fatal crashes are shown as red squares, while serious injury crashes are green triangles, and property damage only crashes are given by circles.

• Continued Innovations: The Center for Advanced Public Safety (CAPS) constantly strives to improve and enhance the CARE software. Essentially each previous version serves as a prototype for the next version that includes both minor and major improvements, many of which are suggested by CARE’s users. Recent improvements include the following:
  • Standard Printing options include: Page Setup, Print, and Print Preview
  • Standard Window manipulation capabilities including: Cascade, Tile Horizontally, Tile Vertically, Arrange Icons, and Close All
  • User control of the variable ordering, filter grouping and exit setting (all within the Tools menu)
  • Dynamic menus: items appear only when available
  • Current data set and filter can be changed in most dialogs without changing the default data set and filter or returning to the main screen
  • The suppress zero-value frequency checkbox has moved to the results screen allowing quick changes in eliminating non-relevant data
  • The variable selection dialogs contain new sorting capabilities
  • The tabular and graphical results data may be reordered by any column
  • The Over Representation, Max Gain, and Threshold Entries are on the results screen instead of in a pop-up window

Training Documentation

• Safety Portal Instructional Guide
• Safety Portal Training Intro
• CARE Training Documentation for Engineers

Training Videos

Running a Cross-Tabulation
VIDEO COMING SOON

Online Analysis

The Online version of CARE does not contain all the functionality of the desktop version but you can do frequency, crosstab and IMPACT analysis online with public datasets. Click here to do Online Analysis with CARE.

Other CARE Documentation

• CARE Overview Brochure
• Open Road Brochure
• Crash Mapping Flyer

An Analysis of Teen-Age Driver Crashes 2005-2008

• January 10th, 2010
• in

This study was conducted at the request of an advocate group that wanted information to assist them in developing public information and education countermeasuers for teen-age drivers. While most past CAPS studies of youth-involved drivers were limited to 16-20 year olds, the advocate group was also interested in 15 year olds, and they were not interested in 20 year olds since their projects were oriented around teen drivers. Several studies were conducted, including CARE IMPACT studies that compared 15, 16-19 and 15-19 year old causal drivers with causal drivers in the older age group.

CARE Driver Distractions Study

• November 21st, 2009
• in

This was a recent report requested to provide information for the Distracted Driver Summit held at UAB on December 3, 2009. A variety of driver distraction causes are discussed and compared.

HIT: A GIS-Based Hotspot Identification Taxonomy

• June 1st, 2009
• in

The authors have developed a Hotspot Identification Taxonomy (HIT) that organizes the various methods for viewing hotspots. Basically they are defined as follow:

• First order – high crash frequency road segments possibly filtered for specific event(s);
• Second order – road segments defined as those that have high event counts specifically related to a countermeasure under consideration (e.g., selective enforcement for the speed event);
• Third order – segments having a high frequency of countermeasure-related events and for which the countermeasure was historically effective.

Effective use of the HIT model required four interrelated activities: data-collection, linear hotspot identification, presentation and assessment.

A Review of Youth-Alcohol Traffic Crashes in Alabama During CY 2007

• January 15th, 2009
• in

As part of their youth-alcohol program, the Alabama Department of Economic and Community Affairs requested a special study to focus on the development of Youth-DUI countermeasures. This report is in three sections. The first is a summary of recommended countermeasures in prioritized order based upon estimated cost-benefit. The recommendations are based upon the detailed analysis performed for Alabama and reviews of potential countermeasures given in the literature. The second and third sections of this report provide the detailed data analysis that was originally performed for the State of Alabama for CY (calendar year) 2003. These have been updated using CY 2007 data.

A Host Architecture for Automobile License Plate Recognition

• May 1st, 2008
• in

The objective of this paper was to present an architecture that supports data transmission and data sharing among applications related to commodity tag recognition systems. These systems are used extensively in Great Britain and other countries to recognize automobile license plates and to notify security officials of suspicious activity or trafficking by known suspects. This architecture was tested in a successful pilot project.