Promoting pedestrian safety in Bangladesh: Identifying factors for drivers' yielding behavior at designated crossings
DOI: 10.1080/15389588.2024.2355630
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study addresses the critical issue of pedestrian safety in Bangladesh, where drivers’ failure to yield at designated crossings significantly increases injury risks and discourages the use of safe crossing infrastructure. Motivated by the high road traffic fatality rates in low- and middle-income countries and the specific challenges of interdependent driver-pedestrian behaviors, the research aims to identify factors influencing drivers’ yielding behavior. Unlike previous studies that often overlook psychological dimensions, this work applies behavior change theories, specifically the Capability, Opportunity, and Motivation-Behavior (COM-B) model, to establish a consensus between competing road users and inform effective safety interventions. The researchers employed a mixed-methods design involving quantitative surveys and qualitative focus group interviews. A self-reported attitudinal survey was administered to 202 drivers on two high-risk highways (N-540 and N-2), utilizing a questionnaire based on the COM-B model to assess physical and psychological capability, physical and social opportunity, and automatic and reflective motivation. Additionally, focus group interviews were conducted with 40 pedestrians and 19 drivers to gather in-depth perspectives on crossing behaviors. Data analysis involved Principal Component Analysis (PCA) to validate the questionnaire constructs and stepwise multiple regression to identify significant predictors of yielding behavior. The qualitative data were analyzed using a deductive thematic coding framework mapped to the Theoretical Domains Framework. The regression model explained 45.1% of the variance in drivers’ yielding behavior, identifying eight significant factors. Seven of these factors positively contributed to yielding. Key motivational factors included pedestrians avoiding random crossing, the presence of vulnerable groups (such as children or women), pedestrian assertiveness, and pedestrians displaying facial expressions of fear. Significant opportunity factors included the presence of traffic signs or advanced yield lines, pedestrians crossing in groups at specific times, and the enforcement of traffic rules. Conversely, the number of crossing users was a negative predictor. The study found that drivers were more likely to yield when pedestrians used designated areas and exhibited fear or assertiveness, while random crossing and long waits triggered driver anger and non-compliance. The findings highlight the importance of integrating behavior change theories into road safety planning, particularly in contexts with institutional weaknesses. The study concludes that highway designers and policymakers should utilize the identified thematic coding framework to develop interventions that address both driver motivations and pedestrian opportunities. By acknowledging the psychological needs of pedestrians and the behavioral triggers of drivers, stakeholders can design people-oriented road systems that reduce conflicts and promote mutual compliance, thereby enhancing overall pedestrian safety in Bangladesh.
Key finding
A regression model explained 45.1% of the variance in drivers' yielding behavior, identifying eight significant factors including pedestrian assertiveness, avoidance of random crossing, presence of vulnerable groups, facial fear expressions, traffic signs, group crossing, enforcement, and crossing frequency.
Methodology
mixed_methods
Sample size: 202
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 scout_discovery on 2026-05-08.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | partial | scout | — | — | 2 | 2026-05-08 |
| archive | success | core_acuk | — | — | 2 | 2026-06-04 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | semantic_scholar | — | — | 2 | 2026-06-04 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: observational prevalence