In Thailand and Laos, drivers frequently disregard international road traffic regulations, particularly the mandate to yield to pedestrians. This behavior compels pedestrians to rely on their judgment to assess safety gaps and cross independently, as drivers often do not prioritize them. Interestingly, many pedestrians choose to cross the road outside of designated crossings, which may reflect an adaptive behavior rooted in local cognitive and cultural contexts. In contrast, European countries have well-defined and strictly enforced regulations that require drivers to yield to pedestrians, resulting in safer pedestrian experiences. However, in Thailand and Laos, the lack of effective enforcement and compliance leads to hazardous pedestrian crossings. The disparity in pedestrian safety between these regions can be partly attributed to cognitive and behavioral factors, such as risk perception, learned behaviors, and cultural norms, which influence both pedestrian and driver actions. This study employed the field study method to analyze driver yielding rates at 12 locations in Udon Thani, Thailand, and Vientiane, Laos. Data collection encompassed traffic flow in both directions and was conducted under typical weather conditions on a standard working day, focusing on the rate and type of yielding by drivers. The findings reveal a minimal proportion of drivers who yield to pedestrians, with some locations exhibiting particularly low compliance rates. While a zero yielding rate theoretically increases road capacity by allowing continuous vehicle flow, it also endangers pedestrians, leading to potential accidents that can disrupt traffic flow. This situation underscores the need to consider cognitive and behavioral dimensions, such as how drivers perceive pedestrians and the habitual actions of both groups, in road design and traffic management policies. An understanding of these cognitive and behavioral aspects, alongside local cultural practices, is crucial for developing effective safety campaigns and infrastructural improvements that can enhance pedestrian safety in these regions.

This study explores road users’ behaviors and accident analyses on different travel modes in the Bangkok Metropolitan Region (BMR). The questionnaire survey was adopted and designed based on contributing factors related to risk behavior perceptions in different travel modes. A total of 3000 participants submitted questionnaires that provided data for a multiple regression model analysis. The results indicated that different travel modes have different risk behavior perceptions. Road users of vulnerable modes of travel, such as walking and cycling, were more aware of risky behaviors than users of others. Risky, violent behavior may occur due to fatigue, driving while taking drugs, or aggressive tactics where the driver may lose control and cause an accident. However, driver negligence, especially violating traffic rules, may sometimes cause risky behavior. The results show that age, gender, education level, income level, marital status, driving experience, accident experience, and attitude toward road safety affect risk behavior perception. In conclusion, the differentiation of vehicles plays a vital role as a critical issue that should be understood for effectively mitigating risks in different travel patterns.

This study applies an approximate queuing framework to analyze pedestrian flow at 24 crosswalks in Hungary. Data on pedestrian and vehicle volumes, crosswalk dimensions, and vehicle speeds were collected. Key parameters such as pedestrian arrival rates, crossing times, and waiting times were estimated using simplified queuing assumptions. The analysis reveals that pedestrian flow and occupancy significantly impact crosswalk capacity, with reductions ranging from 3% to 50%, particularly at locations with high pedestrian volumes and longer crossing durations. Findings highlight the importance of pedestrian flow characteristics in capacity estimation and demonstrate the practicality of this framework for assessing crosswalk performance. This study applies queuing-based flow analysis across multiple real-world sites using low-data, accessible methods. The results provide valuable insights for urban planners seeking to optimize pedestrian safety and improve crosswalk efficiency, emphasizing the need for targeted interventions like signal timing adjustments and crosswalk redesigns. This approach offers a cost-effective tool for preliminary capacity analysis, supporting informed decision-making in urban transportation planning and pedestrian management.