Intelligent Policing Strategy for Traffic Violation Prevention
Police officer presence at an intersection discourages a potential traffic violator from violating the law. It also alerts the motorists' consciousness to take precaution and follow the rules. However, due to the abundant intersections and shortage of human resources, it is not possible to assign a police officer to every intersection. In this paper, we propose an intelligent and optimal policing strategy for traffic violation prevention. Our model consists of a specific number of targeted intersections and two police officers with no prior knowledge on the number of the traffic violations in the designated intersections. At each time interval, the proposed strategy, assigns the two police officers to different intersections such that at the end of the time horizon, maximum traffic violation prevention is achieved. Our proposed methodology adapts the PROLA (Play and Random Observe Learning Algorithm) algorithm [1] to achieve an optimal traffic violation prevention strategy. Finally, we conduct a case study to evaluate and demonstrate the performance of the proposed method.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Edge-AI Perception Node for Cooperative Road-Safety Enforcement and Connected-Vehicle Integration
Rapid motorization in emerging economies such as India has created severe enforcement asymmetries, with over 11 million recorded violations in 2023 against a human policing density of roughly one officer per 4000 vehicle…
Object DetectionShort-Term Traffic Flow Prediction Using Variational LSTM Networks
Traffic flow characteristics are one of the most critical decision-making and traffic policing factors in a region. Awareness of the predicted status of the traffic flow has prime importance in traffic management and tra…
Decision MakingManagementMissing ValuesPredictionThe 8th AI City Challenge
The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (ITS), presenting significant research opp…
Dense Video CaptioningVideo CaptioningINTACT: Intent-Aware Representation Learning for Cryptographic Traffic Violation Detection
Security monitoring systems typically treat anomaly detection as identifying statistical deviations from observed data distributions. In cryptographic traffic analysis, however, violations are defined not by rarity but b…
Representation LearningAnomaly DetectionImproving Policing with Natural Language Processing
This article explores the potential for Natural Language Processing (NLP) to enable a more effective, prevention focused and less confrontational policing model that has hitherto been too resource consuming to implement …