RTChoke: Efficient Real-Time Traffic Chokepoint Detection and Monitoring

TL;DR

RTChoke is a system that efficiently detects and monitors traffic congestion hotspots using adaptive sensing, significantly reducing energy consumption while maintaining accurate congestion estimates for real-time traffic management.

Contribution

The paper introduces a novel adaptive sensing approach for traffic hotspot detection that minimizes resource usage without sacrificing accuracy.

Findings

Consumes 40-80% less energy than periodic sampling

Maintains similar congestion estimation accuracy

Effectively identifies new hotspots with adaptive sampling

Abstract

We present a novel efficient adaptive sensing and monitoring solution for a system of mobile sensing devices that support traffic monitoring applications. We make a key observation that much of the variance in commute times arises at a few congestion hotspots, and a reliable estimate of congestion can be obtained by selectively monitoring congestion just at these hotspots. We design a smartphone application and a backend system that automatically identifies and monitors congestion hotspots. The solution has low resource footprint in terms of both battery usage on the sensing devices and the network bytes used for uploading data. When a user is not inside any hotspot zone, adaptive sampling conserves battery power and reduces network usage, while ensuring that any new hotspots can be effectively identified. Our results show that our application consumes 40- 80% less energy than a periodic sampling system for different routes in our experiments, with similar accuracy of congestion information. The system can be used for a variety of applications such as automatic congestion alerts to users approaching hotspots, reliable end-to-end commute time estimates and effective alternate route suggestions.