Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for 23%. In developing countries, most pedestrian deaths occur on urban arterial roads, particularly at midblock crossings. This study analyzes the factors influencing driver yielding behavior at midblock crosswalks on urban arterial roads in Thailand. This study analyzed the factors influencing driver yielding behavior at the midblock crosswalk before and after the upgrade from a zebra crossing (C1) to a smart pedestrian crossing (C2), which is a smart traffic signal detecting and controlling pedestrians and vehicles entering the crosswalk. Video-based observations were used to assess driver yielding behavior, with multinomial logistic regression applied to develop driver yielding behavior models. The results revealed that the chances of a driver yielding at C2 were higher than at C1, and the yielding rate increased by 74%. The models indicate that the number and width of traffic lanes, width and length of crosswalks, vulnerable group, number of pedestrians, pedestrian crossing time, number of vehicles, vehicle speed, headway, post-encroachment time between a vehicle and pedestrian, and roadside parking are the significant factors influencing yielding behavior. These findings propose measures to set proper crosswalk improvements (e.g., curb extensions), speed reduction measures, enforcement (e.g., parking restrictions), public awareness campaigns, and education initiatives.

Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for nearly one-quarter (23%) of these fatalities. This casualty proportion highlights the critical importance of adhering to traffic regulations. This study analyzes the factors influencing driver yielding behavior at midblock crosswalk improvements, comparing (1) a typical zebra crossing (C1) and (2) an intelligent signalized crosswalk (C2). The study used video-based observational data to investigate driver behaviors and factors influencing driver behaviors. The study applied multinomial logistic regression to formulate yielding behavior models. The results indicate that the number of traffic lanes, width of the traffic lanes, width and length of the crosswalk, vulnerable group, the number of pedestrian crossings, pedestrian crossing time, the number of vehicles approaching a crosswalk, speed of vehicle, headway, the post-encroachment time (PET) between vehicles and pedestrian, and roadside parking are the significant factors influence yielding behavior. These findings provide a better understanding of the factors influencing driver yielding behavior and propose measures to set proper physical improvements (e.g., curb extensions, raised pedestrian platforms, and pedestrian fencing), enforcement (e.g., parking restriction, speed violation detection), public awareness campaigns, and education initiatives.

Traffic rule violations at midblock crosswalks by road users are a critical road safety issue, particularly in developing countries like Thailand. This study aims to explore the factors that influence the intentions behind these violations. Data were collected from 500 pedestrians, 300 motorcycle riders, and 350 car drivers through a questionnaire survey based on the theory of planned behavior (TPB). To assess the validity, reliability, and consistency of the factors, confirmatory factor analysis (CFA) was employed, followed by structural equation modeling (SEM) to examine the factors influencing the intentions to violate traffic rules. The results indicated that attitude was the key predictor of pedestrians’ intentions to cross outside the designated crosswalks. Subjective norms were most influential for motorcycle riders, while perceived behavioral control significantly affected car drivers’ intentions to not yield to pedestrians. Moreover, the study found that raised platforms and signalized crosswalks have significantly increased pedestrians’ and drivers’ compliance with traffic rules compared to zebra crossings. These findings suggest that effective road safety interventions could include altering road users’ attitudes through licensing programs and road safety campaigns. The subjective norm can communicate the dangers and consequences of traffic rule violations. Traffic engineering measures (e.g., lane narrowing) and strict law enforcement by police officers (e.g., surveillance cameras, license plate recognition cameras) should be used to enhance perceived behavioral control.