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Open access Aug 2026

Analyzing roadway factors influencing the severity of non-motorized road users' crashes in Charlotte, North Carolina, USA

As U.S. cities expand multimodal transportation networks and pursue Vision Zero goals, crash severity among pedestrians and bicyclists remains a critical public safety challenge. Charlotte, NC, offers a timely case study given its rapid urban growth, rising active transportation demand, and commitment to Vision Zero. This study investigates the human, behavioral, and environmental determinants of pedestrian and bicyclist crash severity in Charlotte, North Carolina, using a five-year crash dataset (2019–2023). Binary logistic regression was applied after evaluating and rejecting ordinal and multinomial approaches due to proportional odds violations and class imbalance. Two models were developed: a primary cause (behavioral) model and an environmental and primary cause model. Crash records were drawn from the Highway Safety Information System (HSIS), supplemented with historical weather data and site inspection to address missing values. The behavioral model found that crashes with no identified contributing circumstance had 2.32 times higher odds of severe injury compared to human-attributed crashes. This association is best interpreted as a crash-documentation artifact, as it attenuates to non-significance once road design and road-user type are controlled. The extended environmental model achieved an AUC of 0.78 (95% CI 0.74–0.82). Daylight reduced severe crash odds by 66%. Divided roads with positive median barriers increased severity risk more than twofold (OR = 2.52). Each additional travel lane raised severity odds by 18%. Urban locations and intersections were also statistically significant predictors, and bicyclists faced substantially lower severity odds than pedestrians (OR = 0.24). Infrastructure design (particularly road division, lane count, and lighting), is a stronger predictor of severe crash outcomes than behavioral fault assignment. Findings support targeted infrastructure interventions in Charlotte’s Vision Zero and active transportation planning efforts.

Fatemeh Abdous, R. Javid, Celeste Chavis et al. · 0 citations
Review Aug 2026

High Traffic, High Impact: Preliminary Data on Roadkill Rates from Murchison Falls National Park, Uganda.

Wildlife mortality by animal-vehicle-collisions in Uganda's protected areas is poorly understood. We present baseline roadkill data from Murchison Falls National Park collected over 32 consecutive days, 10 December 2024-10 January 2025, along an 86 km tarmac road and a 56 km murram (unpaved) road.Over 18 176 km of road were surveyed, we recorded 53 roadkill events (0.003 roadkill/km), comprising 31 species of vertebrates. Mortality was higher on tarmac (0.004 roadkill/km) than murram roads. Mammals and reptiles exhibited the highest mortality (0.002 roadkill/km each). Kernel density analysis identified 8 distinct high-risk and 14 medium-risk roadkill hotspots along the surveyed route. The total length of road classified as high risk was 19.08 km. Speed bumps were the primary mitigation measure. Plastic pollution was also concentrated on the tarmac road (84.25 kg).Traffic diversion through the park contributed to high roadkill rate (approximately two animals killed per day) and plastic waste pollution. Current mitigation measures appear inadequate to reduce wildlife mortality. This study highlights the impact of traffic on protected areas and provides a critical baseline for future monitoring.

Fred Safari, C. Bulafu · 0 citations
Open access Jul 2026

A Multi-Method Spatial and Statistical Assessment of Road Accident Risk and the Regional Accident Risk Index (RARI) in Tanzania

This study analyzes road traffic accident risk in Tanzania and introduces a composite Regional Road Accident Risk Index (RARI), defined as accidents per 100 km of road, to compare regional risk and assess progress toward SDG 3.6. A multi-method approach was used: national traffic fatality trends from 2000–2022 were modeled using ARIMA forecasting to 2030; a five-year regional panel of 30 regions from 2018–2022 was examined using fixed-effects Poisson regression; and spatial clustering of RARI values was assessed using GIS and Global Moran’s I. Results show that official fatalities declined markedly from the mid-2010s to 2020 but rose again in 2022–2023, suggesting that Tanzania is unlikely to sustain progress toward the SDG target without renewed interventions. Regression findings indicate that driver-related factors, especially speeding, reckless driving, and negligence, are the strongest predictors of accident counts, while vehicle defects and alcohol-related factors also increase risk. RARI reveals substantial regional disparities, with the national average close to one accident per 100 km annually, the highest-risk urban region reaching about 2.5 accidents per 100 km, and the lowest-risk regions around 0.3 accidents per 100 km. Spatial analysis confirms significant clustering, with high-risk areas concentrated around major urban centers and trunk highways. The study is limited by likely under-reporting in police data, lack of vehicle-kilometres-travelled data, and the short regional panel. Nevertheless, the combined forecasting, regression, and spatial approach provides actionable evidence for prioritizing enforcement, infrastructure improvements, vehicle safety checks, and protection of vulnerable road users in high-risk regions.

S. Hamisi · 0 citations
Review Jul 2026

Bicyclist overtaking in naturalistic riding data: Speed, clearance, and implications for injury risk.

OBJECTIVE Motor vehicle passing speed and lateral clearance jointly determine both bicyclist injury risk and perceived safety during overtaking events. Most prior studies have examined these factors separately and/or in limited settings. Real-world evidence describing how passing speed and clearance interact across heterogeneous roadway contexts remains limited. This study evaluates high-resolution naturalistic overtaking data within a kinetic-energy injury framework to evaluate whether roadway context and bicycle infrastructure modify both passing speed and lateral clearance, and whether spatial compensation meaningfully offsets energetic exposure. METHODS Following institutional review board approval, naturalistic cycling data were collected from six commuter cyclists riding as normal using a sensor suite including cameras, lidar, rear-facing radar, GPS, and inertial measurement unit. Approximately 9,900 km of riding were recorded over four months. Overtaking events were detected and characterized using time-synchronized radar and lidar data, yielding 8,753 passes with reliable vehicle speed estimates after quality filtering. Overtaking events were map-matched to OpenStreetMap roadway attributes and supplemented with image-based manual coding to classify functional class, posted speed limit, lane count, centerline configuration, and bicycle infrastructure type. Ordinary least-squares regression models with participant-clustered standard errors were applied to evaluate infrastructure effects and speed-distance relationships, including interactions with driver speeding behavior. RESULTS Passing speed varied substantially across roadway contexts, increasing with functional class and posted speed limit. Mean passing speed ranged from approximately 10 m/s (residential roads) to nearly 15 m/s (primary and four-lane facilities). In contrast, lateral clearance varied modestly across contexts, with mean values generally between 2.2 and 3.0 m and substantial overlap among categories. After adjustment for roadway characteristics, standard painted bicycle lanes were associated with reduced passing distance (β = -0.31 m) and higher passing speed (β = +1.36 m/s) relative to roads without bicycle accommodation. Shoulders were associated with the highest passing speeds and no meaningful increase in clearance. The overall compensation slope, defined as the increase in lateral clearance with increasing speed, was small: 0.016 m per 1 m/s (∼2.8 inches per 10 mph). Modest but statistically significant compensation was observed among drivers exceeding the speed limit and on higher-speed, higher-capacity roadways. CONCLUSIONS Roadway context strongly influenced passing speed, whereas lateral clearance adjustments were comparatively small and inconsistent. Across various naturalistic environments, lateral clearance did not increase proportionally at higher speeds. On-road bicycle infrastructure without accompanying speed management did not reliably reduce high-speed passing and, in some contexts, was associated with closer overtaking. These findings demonstrate the need for vehicle speed reduction and improved separation of bicycles from motor vehicle traffic to reduce crash injury risk.

Laura Hamm, Marty Miller · 0 citations
Oct 2026

Comprehensive Assessment Framework for Collision Risk in Wide-Range Expressway Diverging Area Using Two-Dimensional Vehicle Trajectory Data

Expressway diverging areas exhibit a higher vehicle collision risk than basic segments due to frequent weaving and diverging traffic. Existing studies rely on 1D indicators and focus on the exit ramp and adjacent downstream sections, underestimating collision risks in wide-range diverging areas. This study proposes a two-step framework for comprehensive collision risk assessment in such areas. First, global vehicle trajectories with 2D kinematic parameters are extracted from videos recorded by multiple roadside cameras. Then, anticipated collision time (ACT), a 2D surrogate safety indicator, is integrated with the spatiotemporal overlap interaction filter to detect conflicts using the extracted trajectories. A case study is conducted on a wide-range expressway diverging area, divided into three sections for risk comparison. Results show that most detected conflicts involve only passenger cars, while those involving heavy vehicles are more frequently associated with unsafe scenarios. The spatial distribution of the conflict frequency revealed significant variations across sections. The midstream section exhibits the highest frequency, followed by the downstream section, while the upstream section has the lowest. Conflict-prone zones expand longitudinally and laterally across all sections as the ACT threshold is relaxed, and their spatial distribution demonstrates heterogeneity. The proposed framework supports specific traffic safety improvements in wide-range expressway diverging areas.

Yuxuan Wu, Zhe Dai, Shi Dong et al. · 0 citations
Review Open access Aug 2026

Animal-vehicle collisions, roadkilled animals, and human health: A scoping review protocol

Background Animal-vehicle collisions (AVCs) are a growing global problem with significant implications for human, animal, and ecosystem health. In the United States, approximately one million vertebrates are killed by vehicles each day. Research on roadkilled animals has increased over time, especially regarding wildlife and ecosystem impacts, economic costs, and human physical health risks. However, less is known about how involvement with AVCs or encounters with roadkilled animals influences human health more broadly, including psychological, emotional, psychosocial, and community-level outcomes. Objectives Guided by the One Health framework, this study protocol presents the methodological plan to identify and synthesize current evidence on how AVCs and exposure to roadkilled animals affect human health. The scoping review has not yet been conducted. Search strategy The methodological approach follows PRISMA-ScR guidelines and Arksey and O’Malley’s five stage framework. A comprehensive, librarian‑assisted search will be conducted across six databases—Scopus, CABI Digital Library, Web of Science, Wildlife & Ecology Studies Worldwide, TRID, and PubMed—without restrictions on publication year or peer‑review status. Reference lists of included records will also be screened. Three reviewers will independently screen the titles, abstracts, and full texts, with each record reviewed by a combination of two reviewers. Eligibility criteria Records will be included if they examine how AVCs or roadkilled animals affect any dimension of human physical, mental, or social well‑being and are available in English. Charting methods Data will be extracted using a standardized form and analyzed through content analysis to describe the distribution of evidence and organize findings into themes. Conclusions By consolidating dispersed knowledge across disciplines, this review will provide the first comprehensive overview of how AVCs and roadkilled animal exposure affect human health. Findings will inform public policy, transportation planning, wildlife management, and future interdisciplinary research aimed at integrated One Health solutions.

F. Doherty, Travis R. Scheadler, Nadia Matin · 0 citations