Using the Theory of Planned Behavior to Understand Traffic Violation Behaviors in E-Bike Couriers in China

This paper identifies salient beliefs that influence e-bike couriers’ traffic violation behavior based on the theory of planned behavior (TPB). Two surveys were conducted in Nanjing, China, in 2018. The first survey extracted the key psychological beliefs, which were used to design a questionnaire. The second survey assessed TPB components and reported e-bike couriers’ traffic violation behavior. A structural equation model was adopted to analyze the data. The results revealed that attitudes, descriptive norms, and perceived behavioral control explained 55.7% of the variance in intention to perform traffic violation behavior, and intentions together with perceived behavior control accounted for 28.5% of the variance in self-reported violation riding behavior. All of the belief composites had strong direct impacts on their respective TPB constructs. Salient beliefs were applied to develop effective intervention strategies. Age, education level, whether one possessed a driver’s license, and past traffic violation behaviors had significant effects on belief composites and behavior. The quantitative analysis results obtained in the study can provide theoretical support for designing more effective interventions for reducing the traffic violation rate of e-bike couriers.

The Role of Attitude, Behavior, and Road Conditions in Traffic Violation among Workers and Students in Bandung City, Indonesia

Introduction: This study aims to explore the attitudes towards riding safety, behavior regarding safety gear, documents, and vehicle and riding preparedness, and perceived road conditions among worker and student motorcyclists, and the influence of these on their violation behavior. Methods: To further explore the violation behavior, the effects of the infrastructure quality, personal and travel characteristics, and the experience of accidents were also included in the variables. This study collected data on motorcycle users’ behavior in Bandung City and used Structural Equation Modeling (SEM). Results and Discussion: This research underlines that behavior regarding safety gear, documents, and vehicle and riding preparedness is an important factor that decreases the violation behavior. Interestingly, a positive attitude towards safe riding does not straightforwardly lead to better behavior in preparing the vehicle, safety gear, and documents. Conclusion: Good quality infrastructure also promotes a reduction of traffic violations. Improving road infrastructure safety and both promoting and monitoring users’ safe riding behavior are suggested to lower the number of traffic violations.

Artificial Intelligence Software Application for Contactless Traffic Violation Apprehension in the Philippines

This paper presents a prototype of a centralized contactless traffic violation apprehension system composed of an artificial intelligence (AI) engine and a web application. The AI engine collects traffic data, primarily traffic violation data, through a contactless approach by using different video and image processing techniques and AI algorithms in its three modules: license plate detection, optical character recognition (OCR), and number coding violation detection. The web application consolidates all the data produced by the AI engine and provides a graphical user interface (GUI) for data management, visualization, and analysis. This contactless apprehension system aims to automate, standardize, and streamline the existing processes of law enforcement agencies and institutions for a more efficient apprehension of traffic violators and help them improve their traffic planning and management in the congested areas of the Philippines.