Select High Risk Pedestrian Midblock Crossings and Perform Safety Evaluations for Developing Pedestrian Crossings
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Summary
This study addresses the urgent need to improve pedestrian safety at midblock crossings on high-speed, multi-lane roads in Texas, particularly in San Antonio, Houston, and Dallas. These locations frequently serve vulnerable populations and connect neighborhoods to essential services but are characterized by high crash risks due to speed, poor visibility, and insufficient infrastructure. The research aims to identify high-risk sites, evaluate safety interventions, and develop a comprehensive framework for prioritizing and implementing pedestrian crossing improvements statewide. The researchers conducted a multi-phase analysis involving a state-of-the-practice review, extensive data compilation, and field assessments. They aggregated pedestrian crash data from 2003 to 2022, roadway characteristics, census data, and pedestrian volumes across the three major Texas cities. Using geospatial tools, they identified the top ten crash hotspots in each city. Field assessments at these sites involved recording pedestrian and driver behaviors, including jaywalking patterns, and analyzing roadway conditions. The team also developed localized Safety Performance Functions (SPFs) and Crash Modification Factors (CMFs) using crash frequency and injury severity models, validated through cross-validation techniques to prevent overfitting. Additionally, they reviewed international case studies and conducted a survey on midblock crossing safety improvements. Key findings include the identification of specific high-risk corridors and the quantification of crash dynamics related to speed, lighting, and pedestrian demographics. The analysis revealed significant jaywalking patterns at identified hotspots, indicating a mismatch between infrastructure and pedestrian demand. The study successfully developed localized CMFs for various treatments, such as Pedestrian Hybrid Beacons (PHBs), Rectangular Rapid Flashing Beacons (RRFBs), raised medians, and high-visibility markings. Before-and-after analyses of existing midblock crossing installations demonstrated measurable reductions in crash frequencies, validating the effectiveness of these countermeasures. The research also highlighted the disproportionate impact of crashes on certain demographic groups and the critical role of visibility and speed management in preventing fatalities. The primary outcome of this research is the Midblock Crossing Pedestrian Safety Action Plan, a data-driven guide for Texas Department of Transportation (TxDOT) districts. This plan integrates site rankings, treatment prioritization strategies, and implementation pathways, including engineering upgrades, education, and enforcement. By providing localized CMFs and a systematic approach to safety evaluation, the study empowers decision-makers to allocate resources effectively, promote equitable access, and reduce pedestrian fatalities. The findings offer a replicable model for other jurisdictions facing similar challenges with midblock pedestrian safety on high-speed urban corridors.
Key finding
The development of localized Crash Modification Factors and a comprehensive Midblock Crossing Pedestrian Safety Action Plan provides a data-driven framework for prioritizing and implementing safety treatments at high-risk midblock crossings in Texas.
Methodology
mixed_methods
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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Information type
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- Empirical Findings: crash risk outcomes