Analysis of vessel traffic flow characteristics in inland restricted waterways using multi-source data

TL;DR

This paper investigates inland waterway vessel traffic flow characteristics using multi-source data, proposing models and classifications to improve traffic management and navigation services.

Contribution

It introduces a comprehensive analysis combining vessel-following experiments, fixed-point video monitoring, and novel models for traffic flow and state classification.

Findings

Identified the economic speed range for vessels.

Established the logarithmic model as the best fit for vessel speed-gap relationships.

Proposed a piecewise fundamental diagram model for macroscopic traffic analysis.

Abstract

To effectively manage vessel traffic and alleviate congestion on busy inland waterways, a comprehensive understanding of vessel traffic flow characteristics is crucial. However, limited data availability has resulted in minimal research on the traffic flow characteristics of inland waterway vessels. This study addresses this gap by conducting vessel-following experiments and fixed-point video monitoring in inland waterways, collecting multi-source data to analyze vessel traffic flow characteristics. First, the analysis of vessel speed distribution identifies the economic speed for vessels operating in these environments. Next, the relationship between microscopic vessel speed and gap distance is examined, with the logarithmic model emerging as the most accurate among various tested models. Additionally, the study explores the relationships among macroscopic speed, density, and flow rate, proposing a novel piecewise fundamental diagram model to describe these relationships. Lastly, the inland vessel traffic states are categorized using K-means clustering algorithm and applied to vessel navigation services. These findings provide valuable insights for enhancing inland waterway transportation and advancing the development of an integrated waterway transportation system.