Eye in the Sky: Harnessing AI to Monitor Police Response to Illegal Parking Complaints

Abstract

Illegal parking poses significant challenges in urban environments, obstructing travel lanes, increasing gridlock, and blocking access to critical infrastructure. This study aims to examine how the police respond to illegal parking complaints in New York City, offering a first-of-its-kind, systematic, large-scale analysis of law enforcement patterns, with significant policy implications. We used artificial intelligence and a network of publicly available camera feeds operated by the New York City Department of Transportation (DOT) to monitor and file complaints and subsequently track and assess enforcement efficacy. Over five days, 558 illegal parking complaints were generated across 21 cameras, with at least one in each of the city’s five boroughs. The New York Police Department (NYPD) closed 291 complaints (52.15%) while vehicles were still parked illegally, and reported issuing only 16 tickets (2.87%) during the observation period. Certain areas exhibited chronic illegal parking issues that persisted despite repeated complaints. Official resolutions often contradicted ground truth captured by DOT cameras, highlighting discrepancies in enforcement reporting. These findings empirically validate a phenomenon widely recognized anecdotally in New York City and strengthen the case for increased automated ticketing systems, greater police oversight and street designs that inherently discourage illegal parking.

Keywords: Illegal Parking, Automated Enforcement, Police Response to Parking Violations, Parking Detection, Computer Vision, 311 Request Response, Urban Management