In the context of rail transit operations, real-time passenger flow prediction is essential; however, most models primarily focus on normal conditions, with limited research addressing incident situations. There are several intrinsic challenges associated with prediction during incidents, such as a lack of interpretability and data scarcity. To address these challenges, we propose a two-stage method that separates predictions under normal conditions and the causal effects of incidents. First, a normal prediction model is trained using data from normal situations. Next, the synthetic control method is employed to identify the causal effects of incidents, combined with placebo tests to determine significant levels of these effects. The significant effects are then utilized to train a causal effect prediction model, which can forecast the impact of incidents based on features of the incidents and passenger flows. During the prediction phase, the results from both the normal situation model and the causal effect prediction model are integrated to generate final passenger flow predictions during incidents. Our approach is validated using real-world data, demonstrating improved accuracy. Furthermore, the two-stage methodology enhances interpretability. By analyzing the causal effect prediction model, we can identify key influencing factors related to the effects of incidents and gain insights into their underlying mechanisms. Our work can assist subway system managers in estimating passenger flow affected by incidents and enable them to take proactive measures. Additionally, it can deepen researchers' understanding of the impact of incidents on subway passenger flows.

New York City officials announced a pilot program on Thursday to deploy portable gun scanners in the subway system, part of an effort to deter violence underground and to make the system feel safer. The scanners will be introduced in certain stations after a legally mandated 90-day waiting period, the mayor, Eric Adams, said. "Keeping New Yorkers safe on the subway and maintaining confidence in the system is key to ensuring that New York remains the safest big city in America," said Adams, who also announced a plan to send additional outreach workers into subway stations to try to get people with mental health issues who are living in the system into treatment. Adams said officials would work to identify companies with expertise in weapons-detection technology and that after the waiting period, the scanners would be instituted in some subway stations "where the NYPD will be able to further evaluate the equipment's effectiveness". The scanner that Adams and police officials introduced during Thursday's news conference in a lower Manhattan station came from Evolv, a publicly traded company that has been accused of doctoring the results of software testing to make its scanners appear more effective than they are.

New York City's police department has added K5, a crime-fighting machine that is supposed to make the subway safer. Riders on the subway in New York City might have noticed a new addition to the transit system: a robot named K5. K5 is a crime-fighting machine that is supposed to make the subway safer and more secure. But is it really a good idea to have a robot watching over us? CLICK TO GET KURT'S FREE CYBERGUY NEWSLETTER WITH SECURITY ALERTS, QUICK VIDEO TIPS, TECH REVIEWS, AND EASY HOW-TO'S TO MAKE YOU SMARTER K5 is 64.5" tall and weighs in at 420 pounds.

WARNING--Graphic footage: Fox News correspondent Bryan Llenas has the latest on the investigation from Brooklyn, New York, on'Special Report.' New York City may be rolling out new technology and periodic bag checks to prevent future terrorist attacks, according to the mayor. New York City Mayor Eric Adams spoke with MSNBC's "Morning Joe" on Wednesday about the previous day's terror attack on the city's subway system. The mayor touched on the possibility of new technology on public transportation to prevent similar acts in the future. "With the gun detection devices – oftentimes when people hear of'metal detectors,' they immediately think of the airport model," Adams said.