# Urban Traffic State Sensing and Analysis Based on ETC Data: A Survey
## 4 Traffic State Analysis and Assessment Using ETC Data
### Road Segment Traffic State Analysis  
Road segments serve as fundamental units connecting cross-sections, and their traffic state analysis complexity far exceeds single-point cross-section analysis. Segment analysis requires the comprehensive consideration of multiple-dimensional factors, including spatial continuity, temporal dynamics, and flow variability, placing higher demands on the systematicity and precision of analytical methods. ETC data-based road segment traffic state analysis technology achieves the comprehensive sensing and precise assessment of segment traffic states through fully utilizing the spatiotemporal continuity characteristics of the data.  
The construction of road segment operational reliability assessment systems reflects an important shift in traffic management from focusing on the average levels to emphasizing service quality. Traditional traffic analysis often concentrates on indicators such as average speed and average delay, while reliability assessment focuses more on service stability and predictability.  
Calculating these indicators based on ETC data possesses advantages, including large data volumes, extended temporal spans, and high precision. Compared with traditional floating car surveys, ETC data can provide larger sample sizes of travel time data, making reliability indicator calculations more accurate and stable. Simultaneously, the long-term continuity characteristics of ETC data enable the analysis of reliability variation patterns under different time periods, weather conditions, and traffic situations, providing more scientific foundations for traffic management strategy formulation.  
The precision of bottleneck segment identification technology constitutes a crucial component of traffic optimization management. By analyzing the spatial distribution and temporal evolution of segment speeds to identify bottleneck locations causing congestion, the effectiveness of this technical method depends on the spatiotemporal resolution of the data and the scientific validity of the analytical algorithms. Bottlenecks typically manifest as the locations of sharp speed decreases, but accurate bottleneck identification requires the consideration of comprehensive influences from multiple factors. The advantage of ETC data in bottleneck identification lies in providing precise vehicle trajectory information. By analyzing numerous vehicle driving trajectories, the specific locations and times of speed decreases can be accurately pinpointed. Compared with traditional fixed detectors, ETC data can provide more continuous and complete speed variation processes, making bottleneck identification more accurate and reliable. The practical application significance of bottleneck identification lies in providing scientific foundations for traffic organization optimization. By identifying characteristics such as bottleneck locations, occurrence times, duration, and impact scope, targeted improvement measures can be formulated, including signal optimization, lane management, and traffic guidance, thereby improving overall segment traffic efficiency.