Article
Ergonomics
Wooseok Do, Nicolas Saunier, Luis Miranda-Moreno
Summary: A pedestrian countdown signal (PCS) is designed to provide additional information to pedestrians and drivers at crossings. This paper investigates the effects of PCS on drivers' behaviors at signalized intersections, including speed patterns and safety implications. The study findings show that drivers tend to cross intersections at a higher speed when they can see the pedestrian countdown information.
ACCIDENT ANALYSIS AND PREVENTION
(2023)
Article
Ergonomics
Wei Yan, S. C. Wong, Becky P. Y. Loo, Connor Y. H. Wu, Helai Huang, Xin Pei, Fanyu Meng
Summary: This study assessed the short-term and long-term effects of green signal countdown timers (GSCTs) on road safety. It found that GSCTs reduced red-light-running violations in the short term but had no effect in the long term. However, the presence of GSCTs increased the risk of rear-end crashes at intersections.
JOURNAL OF SAFETY RESEARCH
(2022)
Article
Engineering, Civil
Raghavan Srinivasan, Bo Lan, Daniel Carter, Sarah Smith, Bhagwant Persaud, Kari Signor, Taha Saleem
Summary: The study utilized empirical Bayes analysis on data from treated intersections in Charlotte and Philadelphia to evaluate the safety effects of pedestrian countdown signals (PCS). It found significant reductions in total crashes, rear-end crashes, and pedestrian crashes following the implementation of PCS, with a benefit-cost ratio of 23, demonstrating the positive impact of PCS on road safety.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Transportation
Xueqin Long, Meng Zhou, Huan Zhao, Ya'nan Song
Summary: The study establishes a decision model of pedestrian crossing based on risk-cost and time-utility during flashing green-countdown signal, dividing pedestrians into different types and establishing crossing decision models for each based on comparison of risk cost and time utility. The accuracy rates of the models for adventurous, ordinary, and conservative pedestrians range from 60% to 90%, indicating their ability to predict decision behavior accurately. Additionally, pedestrians are less sensitive to risk and more sensitive to time when faced with urgent situations.
JOURNAL OF TRANSPORTATION SAFETY & SECURITY
(2022)
Article
Pediatrics
Sadiqa Kendi, Brian D. Johnston
Summary: This statement summarizes new evidence and strategies in the field of pedestrian safety, including pediatric pedestrian education, risks of distracted walking, safe routes to school, and the Vision Zero strategy. It aims to support pediatricians in offering evidence-based advice to families about active transportation and safety precautions for child pedestrians at different ages.
Article
Energy & Fuels
Tomasz Krukowicz, Krzysztof Firlag, Jozef Suda, Miroslaw Czerlinski
Summary: This article discusses the impact of signal countdown timers (SCT) on road safety and efficiency, with findings showing that SCTs increase red-light violations, decrease vehicle entries during the amber signal, and increase vehicle speed, among other issues.
Article
Psychology, Applied
Zixin Cui, Xiangling Zhuang, Wenxiang Chen, Guojie Ma
Summary: This study investigated the effect of feedback frequency of countdown progress bar in traffic light on time estimation. The results showed that lower feedback frequency led to shorter estimated duration, with slight changes in different contexts. This study has practical implications on the display design of red light and theoretical implications on time estimation processes.
TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR
(2022)
Article
Telecommunications
Abrar Alali, Stephan Olariu, Shubham Jain
Summary: Recent statistics show a worrying increase in accidents involving pedestrians, especially children, crossing the street. Unlike existing approaches, which expect moving cars to undertake pedestrian detection, we propose utilizing parked cars to detect and protect crossing pedestrians. Our system, ADOPT, establishes the theoretical foundations for using parked cars to detect crossing cohorts of pedestrians, predict their clearance time, send alert messages to approaching cars, and enable speed adjustments. Crucially, ADOPT relies on short-range and low-power communications. Extensive simulations using SUMO-generated traffic confirm the effectiveness of ADOPT in detecting and protecting crossing pedestrians.
VEHICULAR COMMUNICATIONS
(2023)
Article
Environmental Studies
Josh Roll, Nathan McNeil
Summary: Pedestrian injuries are increasing as a percentage of overall traffic injuries, and there are disparities in injury risk among different sociodemographic groups. This study examines pedestrian safety disparities in Oregon and finds that lower income and higher proportions of BIPOC residents are associated with higher rates of pedestrian injuries.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Engineering, Industrial
Mehmet Baran Ulak, Ayberk Kocatepe, Anil Yazici, Eren Erman Ozguven, Ashutosh Kumar
Summary: Despite the decrease in crashes and fatalities in the U.S. since 1990, pedestrian crashes have been on the rise, prompting initiatives to address pedestrian safety concerns. However, guidelines are limited by the lack of pedestrian data, highlighting the need to quantify safety of pedestrian facilities. This study proposes a safety index for public transportation bus stops to assess pedestrian safety and identify high-risk locations proactively.
Article
Transportation
Gang Xue, Huiying Wen
Summary: Pedestrian injury in pedestrian-vehicle crashes is closely related to the characteristics of the driver, pedestrian, vehicle, crash, and environment. This study analyzed two years of crash data in Yunnan Province and found that familiar and unfamiliar drivers have different factors that affect pedestrian injury severity. The findings suggest that targeted countermeasures should be implemented for familiar and unfamiliar drivers to reduce pedestrian injury severity.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Multidisciplinary Sciences
Feng Li, Wenjun Pan, Jiali Xiang
Summary: The study investigates the impact of external vehicle acceleration signal light on the interaction experience between pedestrians and vehicles. It shows that acceleration signal light helps pedestrians understand vehicle behavior intentions more quickly, leading to safer crossing decisions and improved perception of safety and trust in vehicle behavior.
SCIENTIFIC REPORTS
(2023)
Article
Ergonomics
Hatem Abou-Senna, Essam Radwan, Ayman Mohamed
Summary: In recent years, pedestrian safety has become a major concern at both the state and national level in the US. The presence of sidewalk gaps in Florida raises concerns about pedestrian safety, and research shows that the risk of pedestrian crashes is significantly higher on roadways without sidewalks.
ACCIDENT ANALYSIS AND PREVENTION
(2022)
Article
Engineering, Civil
Patrick A. Singleton, Ferdousy Runa
Summary: The study demonstrates the validity of using traffic signal controller data to estimate pedestrian crossing volumes with good accuracy, as shown through strong correlation and low mean absolute error between model-predicted volumes and observed volumes. This method can assist transportation agencies in monitoring pedestrian travel, multimodal transportation planning, traffic safety analyses, and health impact assessments.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Green & Sustainable Science & Technology
Byoung-Suk Kweon, Jody Rosenblatt-Naderi, Christopher D. Ellis, Woo-Hwa Shin, Blair H. Danies
Summary: The design of pedestrian environments, including sidewalks, buffer strips, and street trees, does impact parents' walking behavior, their perception of pedestrian safety, and their willingness to let their children walk to school. Parents are more cautious about their children's walking environments and safety than their own, and the effects of trees on parents' walking and perception of pedestrian safety are greater when there is a wide buffer.
Article
Engineering, Civil
Lusanni Acosta-Rodriguez, Valerian Kwigizile, Jun-Seok Oh, Timothy Gates
TRANSPORTATION RESEARCH RECORD
(2020)
Article
Computer Science, Interdisciplinary Applications
Keneth Morgan Kwayu, Valerian Kwigizile, Jiansong Zhang, Jun-Seok Oh
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2020)
Article
Public, Environmental & Occupational Health
Keneth Morgan Kwayu, Valerian Kwigizile, Jun-Seok Oh
TRAFFIC INJURY PREVENTION
(2020)
Article
Engineering, Civil
Md Mehedi Hasan, Jun-Seok Oh
TRANSPORTATION RESEARCH RECORD
(2020)
Article
Public, Environmental & Occupational Health
Md Mehedi Hasan, Jun-Seok Oh, Valerian Kwigizile
Summary: Recent walkability studies have focused on street-level microscopic analysis in North America, while in Asia and Europe, both large and small-scale walkability analysis is emphasized. Advanced images and instrument audit tools have been widely used in addition to traditional physical audit tools for measuring walkability.
JOURNAL OF TRANSPORT & HEALTH
(2021)
Article
Engineering, Civil
Raed Abdullah Hasan, Hafez Irshaid, Fadi Alhomaidat, Sangwoo Lee, Jun-Seok Oh
Summary: Transportation Mode Detection (TMD) is important for planning new transportation projects and improving existing ones. This study aims to develop predictive modes of transportation using smartphone data, smartwatches, and machine learning techniques. The results show that the Random Forest method performs better than other methods in predicting transportation modes.
KSCE JOURNAL OF CIVIL ENGINEERING
(2022)
Review
Transportation
Keneth Morgan Kwayu, Valerian Kwigizile, Jun-Seok Oh
Summary: This study aims to investigate pedestrian crossing behavior at non-intersection areas by analyzing crash data. The results reveal that lighting conditions, pedestrian age, and traffic volume are significant predictors of pedestrian fatalities, and pedestrians wearing dark clothing are more prone to accidents while crossing the road at undesignated areas.
JOURNAL OF TRANSPORTATION SAFETY & SECURITY
(2022)
Article
Ergonomics
Keneth Morgan Kwayu, Valerian Kwigizile, Kevin Lee, Jun-Seok Oh
Summary: This study utilizes crash narratives from a ten-year dataset of Michigan traffic fatal crash narratives to identify prevalent themes and interactions using structural topic modeling and network topology analysis. The centrality and association between topics varied across crash types, with event-related topics consistently central in articulating the crash occurrence. The high classification accuracy of extracted latent themes in classifying crashes by type suggests effective automation of crash typing and consistency checks.
ACCIDENT ANALYSIS AND PREVENTION
(2021)
Article
Public, Environmental & Occupational Health
Ahmad Feizi, Shinhye Joo, Valerian Kwigizile, Jun-Seok Oh
JOURNAL OF TRANSPORT & HEALTH
(2020)
Article
Ergonomics
Bandhan Dutta Ayon, Benjamin Ofori-Amoah, Lei Meng, Jun-Seok Oh, Kathleen Baker
ACCIDENT ANALYSIS AND PREVENTION
(2020)
Article
Public, Environmental & Occupational Health
Keneth Morgan Kwayu, Valerian Kwigizile, Jun-Seok Oh
INTERNATIONAL JOURNAL OF INJURY CONTROL AND SAFETY PROMOTION
(2020)
Article
Green & Sustainable Science & Technology
Ahmad Feizi, Jun-Seok Oh, Valerian Kwigizile, Shinhye Joo
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION
(2020)
Article
Ergonomics
Fadi Alhomaidat, Valerian Kwigizile, Jun-Seok Oh, Ron Van Houten
ACCIDENT ANALYSIS AND PREVENTION
(2020)
Article
Public, Environmental & Occupational Health
Raed Abdullah Hasan, Abbas Hadi Abbas, Keneth Morgan Kwayu, Jun-Seok Oh
JOURNAL OF TRANSPORT & HEALTH
(2019)
Article
Public, Environmental & Occupational Health
Richard Atta Boateng, Valerian Kwigizile, John S. Miller, Jun-Seok Oh
JOURNAL OF TRANSPORT & HEALTH
(2019)
Article
Public, Environmental & Occupational Health
Abdallah Kinero, Kabhabhela Bukuru, Enock E. Mwambeleko, Thobias Sando, Priyanka Alluri
Summary: This study examines the injury severity of golf cart (GC) crashes in a retirement community in Florida. The findings highlight the factors that influence GC crash severity and provide recommendations for improving GC safety.
TRAFFIC INJURY PREVENTION
(2024)
Article
Public, Environmental & Occupational Health
Tianzheng Wei, Tong Zhu, Miao Lin, Haoxue Liu
Summary: This study utilizes machine learning methods to model and analyze the severity of accident injuries in two-wheeled motorcyclists. The results show that the LightGBM algorithm has good prediction performance. The driver's annual kilometers traveled, the throwing distance of the motorcyclist, and the road speed limit are the three most important factors influencing the severity of accident injuries.
TRAFFIC INJURY PREVENTION
(2024)
Article
Public, Environmental & Occupational Health
John Mccombs, Haitham Al-Deek, Adrian Sandt
Summary: This study developed corridor-level network screening models to reduce fatal and injury crashes by identifying high-risk corridors for safety improvements. The corridor-level models were more accurate and statistically reliable than similar HSM models while requiring less data. Agencies can easily replicate the methods using readily available data to identify corridors in need of safety improvements.
TRAFFIC INJURY PREVENTION
(2024)
Article
Public, Environmental & Occupational Health
N. Mohamed Hasain, Mokaddes Ali Ahmed
Summary: The study aimed to evaluate the safety of heterogeneous traffic by identifying critical conflicts based on the speeds of the involved vehicles. The proposed Critical Following Speed method was validated using accident data and showed a correlation between critical conflicts and road accidents. The study highlighted the importance of considering vehicle speed in assessing traffic safety in mixed traffic conditions.
TRAFFIC INJURY PREVENTION
(2024)
