Research Studies & Reports

DMV’s Research & Development Branch has been conducting research and producing studies and reports since the 1950s. Research & Development reports help DMV to measure the impact of new laws on making drivers safer. We also identify areas where we can improve our processes, explore new approaches to solving existing problems, and branch out into new opportunities to serve you better. 

Request printed copies of studies and reports by mail at:

Department of Motor Vehicles
Research and Development Branch
2415 1st Ave. Mail Station: F-126
Sacramento, CA 95818
(916) 914-8125

Please include the report number, the number of copies requested, and your name, address, and phone number.

393 Results

Report ID Date Published Title Section Links
50 1974/ 01

The Prediction of Driving Record Following Driver Improvement Contacts

By: William C. Marsh & David M. Hubert

To construct prediction equations for post-contact driving records based on three data sources-prior driving record, driver questionnaire responses, and driver improvement analyst (DIA) interview information.

IV
79 1981/ 12

Factors Associated with Fatal Accident Involvement Among California Drivers

By: Marilee E. Garretson & Raymond C. Peck

To identify possible factors of fatal accident causation and to isolate common patterns or characteristics for use in developing accident countermeasures.

IV
NRN047 1972/ 11

Measuring Attitudinal Response to Several Types of Driver Improvement Techniques

By: Ronald R. Payne

To develop a quantified evaluation system for measuring subject-oriented psychological differences in response to treatment techniques.

IV
NRN054 1990/ 05

The General and Specific Deterrent Effects of DUI Sanctions: A Review of California’s Experience

By: Raymond C. Peck

To provide an overview of the findings and policy implications of departmental studies on drunk driving.

IV
254 2017/ 07

Predicting Traffic Crash Involvement Using Individual Driving Habits, Driving Record, and Territorial Risk Indices

By: Michael A. Gebers, Jeff Moulton

This study surveyed a sample of California drivers to determine their habits and opinions on selected traffic issues. The study also assessed the importance of exposure and territorial risk indices as predictors of traffic crashes beyond that of driver record factors. The information provided in this report is intended to assist traffic safety administrators and lawmakers in improving services and in developing more effective driver safety programs.

IV
114 1987/ 12

Basic California Traffic Conviction and Accident Record Facts

By: Michael A. Gebers & Raymond C. Peck

To provide traffic safety administrators with information for developing program and policy decisions, and to provide information to the insurance industry and to scholars and researchers in traffic safety

IV
166 1995/ 05

Exploratory Multivariable Analyses ofCalifornia DriverRecord Accident Rates

By: Michael A. Gebers

Since 1964, the California Department of Motor Vehicles has issued several monographs on driver characteristics and accident risk factors as part of a series of analyses known as the California Driver Record Study. This paper presents the results of a number of regression analyses of driving record variables measured over a 6-year time period (1986-91). The techniques presented consist of ordinary least squares, weighted least squares, Poisson, negative binomial, linear probability, and logistic regression models. T he objective of the analyses was to compare the results obtained from several different regression techniques under consideration for use in the in-progress California Driver Record Study. The results are informative in determining whether the various regression methods produce similar results for different sample sizes and to explore whether reliance on ordinary least squares techniques in past California Driver Record Study analyses have produced biased significance levels and parameter estimates. The results indicate that, for these data, the use of the different regression techniques do not lead to any greater increase in individual accident prediction beyond that obtained through application of ordinary least squares regression. In addition, the methods produce almost identical results in terms of the relative importance and statistical significance of the independent variables. It therefore appears safe to employ ordinary least squares multiple regression techniques on driver accident-count distributions of the type represented by California driver records, at least when the sample sizes are large.

IV
190 2001/ 05

Medical Conditions and Other Factors in Driver Risk

By: Mary K. Janke

This report addresses the effects of medical conditions and medications on the ability to operate a motor vehicle safely. It presents crash rates and crash odds ratios for broadly defined groups of drivers known to the Department of Motor Vehicles as having physical or mental conditions that potentially impair driving. It also reviews the scientific literature dealing with medical conditions and driving. Finally, the report briefly discusses a tiered assessment system under study by the department that holds promise for identifying and evaluating medically impaired drivers.

IV
20.2 1965/ 03

The 1964 California Driver Record Study (Part 2: Accidents, Traffic Citations and Negligent Operator Count by Sex)

By: California Department of Motor Vehicles

The basic purpose of the overall study was threefold: (1) to provide data for operational and budgetary planning, (2) to provide basic descriptive and baseline data on drivers and driving record variables, and (3) to further understanding and knowledge about the nature and causes of traffic accidents.

IV
20.4 1965/ 05

The 1964 California Driver Record Study (Part 4: The Relationship between Concurrent Accidents and Citations)

By: California Department of Motor Vehicles

The basic purpose of the overall study was threefold: (1) to provide data for operational and budgetary planning, (2) to provide basic descriptive and baseline data on drivers and driving record variables, and (3) to further understanding and knowledge about the nature and causes of traffic accidents.

IV