Study guide
Planning Evaluations and Collecting Credible Evidence
Road Safety Professional RSP
Track your progress as you read
Finished sections get a check mark.
1 Exam Orientation and Preparation
RSP1 Exam, Eligibility, and Certification Preparing Across the Five RSP1 Domains
2 Foundations: Definitions, Evidence, and Standards
Road Safety Definitions and the Public Health Burden Evaluating Road Safety Literature and Information Nominal and Substantive Safety: Standards and Performance
3 Foundations: Contributing Factors, Energy, and Users
Interacting Crash Contributing Factors Collision Severity, Speed, and Protective Layers Road User Characteristics, Abilities, and Vulnerability
4 Foundations: Partners and Safety Frameworks
Safety Partners, Responsibilities, and Multidisciplinary Perspectives Haddon Matrix and the Development of Safety Management Safe System Principles and Protective Layers Vision Zero, Toward Zero Deaths, and Safety Culture
5 Measurement: Data Collection and Quality
Safety Data Types, Sources, and Users Collecting Quantitative and Qualitative Safety Data The Six Safety Data Quality Attributes Data Process Reviews, Governance, and Investment Decisions
6 Measurement: Exposure, Severity, Models, and Effects
Crash Frequency, Exposure, and Rates Injury Severity, Crash Costs, and Weighted Measures Safety Performance Functions and Suitable Models Regression to the Mean and Empirical Bayes Interpretation CMF Definitions, Scope, and Evidence Quality
7 Human Factors: Perception and the Driving Task
Sensory Perception, Attention, and Workload Driving Task and Perception-Response Time
8 Human Factors: Behavior and Programs
Impairment, Distraction, Fatigue, and Speed Choice Enforcement, Licensing, and Behavioral Countermeasures Outreach, Social Norms, and Audience-Centered Programs
9 Human Factors: Infrastructure, Multimodal Design, and Guidance
Roadway Features, Expectancy, and Behavioral Adaptation Human Factors in Multimodal Planning, Design, and Operations Positive Guidance and Driver Expectancy
10 Problem Solving: Management, Screening, and Diagnosis
The Road Safety Management Process Site-Specific and Systemic Network Screening Crash Patterns, Collision Diagrams, and Diagnostic Hypotheses Field Investigation and Surrogate Safety Measures
11 Problem Solving: Countermeasures and Safety Audits
Countermeasure Sources, Mechanisms, and Selection Combining CMFs and Evaluating Treatment Trade-Offs Road Safety Audits and Documented Owner Responses
12 Problem Solving: Economics and Project Selection
Economic Appraisal: Benefits, Costs, and Discounting Prioritizing Projects and Nonmonetized Impacts
13 Problem Solving: Evaluation Methods and Planning
Evaluating Countermeasures: Before–After and Cross-Sectional Studies Planning Evaluations and Collecting Credible Evidence
14 Implementation: Statewide and Local Plans
Developing Strategic Highway Safety Plans Local, Tribal, and Regional Safety Action Plans
15 Implementation: Funding, Policies, and Practicality
Infrastructure Safety Funding and Program Eligibility Safety Policies, Behavioral Programs, and Practicality
16 Implementation: Teams, Communication, and Learning
Teams, Champions, Leadership, and Organizational Safety Culture Communication, Public Support, and Implementation Consensus Program Monitoring, Safety Targets, and Plan Updates
Planning Evaluations and Collecting Credible Evidence
Key Takeaways Explain This Topic AI
Plan the question, outcomes, comparison, data, and responsibilities before treatment.
Use compatible exposure, crash definitions, periods, and location identifiers.
Document actual implementation and concurrent changes; package effects are not component effects.
Report uncertainty, adverse effects, deviations, and lessons for future decisions.
Last updated: October 2026
- Planning Evaluations and Collecting Credible Evidence
- Design the evaluation before implementation
A good evaluation begins while a project or program is being planned. Decide what change is expected, why it should occur, how it will be measured, and what comparison will help attribute it to the intervention. Waiting until the project is complete can leave missing baseline data, no suitable comparison group, or ambiguous implementation dates. The FHWA CMF development guide provides a foundation for matching study design to the safety question.
Write an explicit question: “Does this crossing treatment reduce pedestrian injury crashes at comparable uncontrolled crossings?” is more useful than “Did safety improve?” Specify the treatment, users, crash types, severity, sites, period, and intended mechanism. A program aimed at seat-belt use may initially measure observed use, while its long-term safety objective concerns occupant injuries. Those outcomes are related but not interchangeable.
Distinguish a project-level treatment effect from a broader program's delivery performance. Evaluating a portfolio can reveal whether agencies delivered projects on time and reached priority networks, but identifying one treatment's causal effect may require a separate study. Define each purpose rather than forcing one dashboard to answer every question.
Collect a stable baseline and comparison
Obtain crash records, exposure data, roadway and traffic-control characteristics, and contextual information for the required periods. Preserve definitions and identifiers so that records can be consistently located and classified. Verify crash severity, geocoding, study boundaries, reporting thresholds, and data completeness. Document changes in police reporting or injury coding that could create an apparent trend.
Exposure should match the outcome: entering vehicles for an intersection, vehicle-miles for a segment, and relevant pedestrian or bicycle activity where available. Collect seasonal and time-of-day patterns when they affect the mechanism. A one-day fair-weather pedestrian count may poorly represent annual activity near a school. If exposure is unavailable, describe the limitation rather than manufacturing an exact risk rate.
Select untreated comparison sites before learning which ones produce the preferred result. Check their treatment histories and changes in traffic, land use, or reporting. For EB studies, verify SPF applicability, calibration, variables, and prediction periods. Keep treatment and comparison data in compatible units; annual predictions cannot be combined directly with multi-year observed totals without conversion.
Record what was actually implemented
Plans describe intended treatment; evaluations need the delivered treatment. Record installation dates, locations, dimensions, operational settings, maintenance interruptions, and deviations from design. A campaign's scheduled media plan is not the same as measured message exposure. A camera program's authorized extent is not the same as its operating hours or actual enforcement locations.
For a corridor redesign, record whether speed limits, signals, crossings, lighting, and enforcement changed together. If the package's effect is evaluated, label it as a package effect. Without a study design that separates components, do not assign the entire reduction to one feature or claim independent CMFs for every component. Treatment fidelity also matters: an installed but nonfunctioning beacon does not provide the intended intervention.
Separate construction periods and transition effects from the intended stable after period when the study method warrants it. Construction can alter exposure, routes, and reporting. A temporary decrease caused by closing the road should not be attributed to the permanent safety design. State exclusion decisions in advance or justify them transparently.
Choose periods and measures with enough information
Fatal and serious-injury events are relatively rare at individual locations. Very short studies may have too little information to distinguish an effect from random variation. Larger samples, multiple appropriate sites, or longer periods can improve precision, but longer periods can also introduce more background changes. There is no universal rule that every evaluation requires exactly three before years and three after years.
Use intermediate measures where they are relevant, while recognizing their limits. Speeds, yielding, conflicts, seat-belt use, and emergency response intervals can test parts of a causal pathway. A reduction in measured conflicts supports a behavioral observation; it does not by itself establish a particular fatal-crash CMF. Ensure the measurement protocol is consistent, observers or devices are trained and checked, and the metric's definition is recorded.
Define success using both a meaningful magnitude and uncertainty, rather than declaring success after any decrease. For instance, an estimated small reduction with a very wide interval may justify further monitoring rather than a definitive effectiveness claim. Record adverse effects, other crash categories, nearby displacement, and impacts on different users.
Preserve the evidence before construction
Define the primary question, outcome, and comparison.
Collect compatible baseline crashes, exposure, and context.
Record delivered treatment, dates, and concurrent changes.
Plan analysis, review, privacy, and reporting responsibilities.
Manage analysis, transparency, and learning
Assign responsibility for data collection, analysis, independent review, and publication. Budget for the evaluation, including access agreements and privacy safeguards. Set a schedule that allows complete after-period data to become available. Do not confuse a project completion date with the date when injury outcomes can be reliably evaluated.
Predefine key analysis choices to reduce selective reporting: primary outcomes, sites, periods, comparison method, and handling of missing data. Explain deviations. An evaluation that tests many outcomes and reports only the most favorable one can mislead even when individual calculations are correct. Preserve reproducible records and calculations without releasing personally identifiable information.
Report estimates and limitations in language the decision maker can use. If a study finds improved yielding but inconclusive injury effects, present both results. If the package underperforms, distinguish a weak underlying intervention from incomplete delivery or changed conditions. Feed the findings into treatment selection, design standards where appropriate, training, and future program priorities. Evaluation is most useful when it changes the next decision rather than merely closing a grant file.