{"title":"调查不同交通环境下城市十字路口行人的闯红灯意图:以理论框架为指导的情景分析","authors":"Zeinab Karami , Sina Rejali , Kayvan Aghabayk","doi":"10.1016/j.trf.2024.09.003","DOIUrl":null,"url":null,"abstract":"<div><p>Pedestrian risky behaviors are one of the contributing factors to crashes involving pedestrians. Therefore, it is crucial to comprehend the mechanisms by which pedestrians interact with many influential components in the traffic environment. This study aimed to evaluate pedestrians’ red light running intentions and related factors under different traffic flow scenarios, including straight traffic flow, right-turning traffic flow, and left-turning traffic flow. A theoretical approach based on the theory of planned behavior (TPB) and the prototype willingness model (PWM) was employed. Data were collected from an online survey of 2250 participants in Tehran, Iran. Structural equation modeling (SEM) was used to identify the significant factors that explain intentions. All models successfully explained the behavioral intention for red light running violation; however, the findings revealed that the integrated model was the best-performing model to represent violation and, thus, was selected for interpreting the results and drawing relevant conclusions. Different traffic flow scenarios had varied effects on violation intentions for individual characteristics and model constructs. Previous crash experiences and driving-related background variables emerged to impact pedestrian violation intention across three scenarios. The findings also suggested that the rational constructs (attitude, perceived behavioral control, and facilitating conditions) had a more robust impact on violation intention compared to reactive constructs (prototype similarity, prototype favorability), with facilitating conditions being the strongest predictor of the model, followed by attitudes toward violation as a significant predictor of intention for red light violation. According to the results, the mechanism of risk-taking varies depending on the direction of the traffic flow. Higher risk was associated with the violation at the intersections with straight traffic flow compared to the intersections with turning traffic flow. Based on the findings of this study, several implications, including interventions focusing on individuals’ transportation safety attitudes, countermeasures to increase the risk perception of pedestrians toward turning vehicles, and countermeasures regarding the use of mobile phones while walking for the context of this study were proposed.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 196-223"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigating pedestrians’ red light running intentions at urban intersections in different traffic Environments: A scenario-based analysis guided by theoretical frameworks\",\"authors\":\"Zeinab Karami , Sina Rejali , Kayvan Aghabayk\",\"doi\":\"10.1016/j.trf.2024.09.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Pedestrian risky behaviors are one of the contributing factors to crashes involving pedestrians. Therefore, it is crucial to comprehend the mechanisms by which pedestrians interact with many influential components in the traffic environment. This study aimed to evaluate pedestrians’ red light running intentions and related factors under different traffic flow scenarios, including straight traffic flow, right-turning traffic flow, and left-turning traffic flow. A theoretical approach based on the theory of planned behavior (TPB) and the prototype willingness model (PWM) was employed. Data were collected from an online survey of 2250 participants in Tehran, Iran. Structural equation modeling (SEM) was used to identify the significant factors that explain intentions. All models successfully explained the behavioral intention for red light running violation; however, the findings revealed that the integrated model was the best-performing model to represent violation and, thus, was selected for interpreting the results and drawing relevant conclusions. Different traffic flow scenarios had varied effects on violation intentions for individual characteristics and model constructs. Previous crash experiences and driving-related background variables emerged to impact pedestrian violation intention across three scenarios. The findings also suggested that the rational constructs (attitude, perceived behavioral control, and facilitating conditions) had a more robust impact on violation intention compared to reactive constructs (prototype similarity, prototype favorability), with facilitating conditions being the strongest predictor of the model, followed by attitudes toward violation as a significant predictor of intention for red light violation. According to the results, the mechanism of risk-taking varies depending on the direction of the traffic flow. Higher risk was associated with the violation at the intersections with straight traffic flow compared to the intersections with turning traffic flow. Based on the findings of this study, several implications, including interventions focusing on individuals’ transportation safety attitudes, countermeasures to increase the risk perception of pedestrians toward turning vehicles, and countermeasures regarding the use of mobile phones while walking for the context of this study were proposed.</p></div>\",\"PeriodicalId\":48355,\"journal\":{\"name\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"volume\":\"107 \",\"pages\":\"Pages 196-223\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1369847824002468\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part F-Traffic Psychology and Behaviour","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1369847824002468","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, APPLIED","Score":null,"Total":0}
Investigating pedestrians’ red light running intentions at urban intersections in different traffic Environments: A scenario-based analysis guided by theoretical frameworks
Pedestrian risky behaviors are one of the contributing factors to crashes involving pedestrians. Therefore, it is crucial to comprehend the mechanisms by which pedestrians interact with many influential components in the traffic environment. This study aimed to evaluate pedestrians’ red light running intentions and related factors under different traffic flow scenarios, including straight traffic flow, right-turning traffic flow, and left-turning traffic flow. A theoretical approach based on the theory of planned behavior (TPB) and the prototype willingness model (PWM) was employed. Data were collected from an online survey of 2250 participants in Tehran, Iran. Structural equation modeling (SEM) was used to identify the significant factors that explain intentions. All models successfully explained the behavioral intention for red light running violation; however, the findings revealed that the integrated model was the best-performing model to represent violation and, thus, was selected for interpreting the results and drawing relevant conclusions. Different traffic flow scenarios had varied effects on violation intentions for individual characteristics and model constructs. Previous crash experiences and driving-related background variables emerged to impact pedestrian violation intention across three scenarios. The findings also suggested that the rational constructs (attitude, perceived behavioral control, and facilitating conditions) had a more robust impact on violation intention compared to reactive constructs (prototype similarity, prototype favorability), with facilitating conditions being the strongest predictor of the model, followed by attitudes toward violation as a significant predictor of intention for red light violation. According to the results, the mechanism of risk-taking varies depending on the direction of the traffic flow. Higher risk was associated with the violation at the intersections with straight traffic flow compared to the intersections with turning traffic flow. Based on the findings of this study, several implications, including interventions focusing on individuals’ transportation safety attitudes, countermeasures to increase the risk perception of pedestrians toward turning vehicles, and countermeasures regarding the use of mobile phones while walking for the context of this study were proposed.
期刊介绍:
Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.