Automatic Freeway Bottleneck Identification and Visualization using Image Processing Techniques

TL;DR

This paper presents an innovative image processing-based algorithm for automatic freeway bottleneck detection and visualization, capable of utilizing diverse traffic sensing data to improve accuracy and provide detailed bottleneck characteristics.

Contribution

The study introduces a novel multi-step algorithm that combines image processing with traffic flow theory, enhancing bottleneck identification beyond traditional loop detector methods.

Findings

Outperforms existing methods in congestion detection accuracy

Successfully extracts detailed bottleneck characteristics

Effective with various traffic sensing technologies

Abstract

This paper develops an automatic freeway bottleneck identification and visualization algorithm using a combination of image processing techniques and traffic flow theory. Unlike previous studies that are based solely on loop detector data, the proposed method can use traffic measurements from various sensing technologies. Four steps are included in the proposed algorithm. First, the raw spatiotemporal speed data are transformed into binary matrices using image binarization techniques. Second, two post-processer filters are developed to clean the binary matrices by filtering scattered noise cells and localized congested regions. Subsequently, the roadway geometry information is used to remove the impact of acceleration zones downstream of bottlenecks and thus locate bottlenecks more precisely. Finally, the major characteristics of bottlenecks including activation and deactivation points, shockwave speeds and traffic delay caused by bottleneck are automatically extracted and visualized. The proposed algorithm is tested using loop detector data from I-5 demonstrating that the proposed method outperforms the state-of-the-art methods for congestion identification. The second test using INRIX data from I-66 demonstrates ability of the proposed algorithm to accurately extract and visualize bottleneck characteristics.