原文传递
Data-Driven Freeway Performance Evaluation Framework for Project Prioritization and Decision Making.
| 题名： | Data-Driven Freeway Performance Evaluation Framework for Project Prioritization and Decision Making. |
| 作者： | Liu, X. C.; Chen, Z. |
| 关键词： | Freeway performance monitoring, Reliability analysis, Decision making, Hot spots, Realiability, incident induced delay, Impact analysis, Data driven applications, Reduced roadway volume |
| 摘要： | This report describes methods that potentially can be incorporated into the performance monitoring and planning processes for freeway performance evaluation and decision making. Reliability analysis is conducted on the selected I-15 corridor by employing congestion frequency as the performance measure and hot spots during peak hours are identified through sensitivity analysis. A data-driven algorithm combining spatiotemporal analysis and shockwave theory is developed and applied to historical traffic data and incident records to determine the secondary incidents. The results show that the occurrence of secondary incidents is highly related to weather and roadway conditions. Incident-induced delay is further quantified through spatiotemporal pattern recognition. The average delay induced by incidents aligns well with the incidents’ severity and impact. There were several hot spots suffering from higher delays and are explored in further details. A statistical mechanism is developed to determine the adverse weather impact on travel. Using the weather records in 2013 and mapping with the PeMS traffic database, the volume and delay under normal condition are estimated and compared with the condition under adverse weather. The analysis of different roadway conditions reveals that the general parabolic pattern of speed and volume disappear under severe adverse weather condition. The mechanism is able to identify the causes for reduced volume under a variety of scenarios through empirical data, either due to roadway capacity reduction or travel demand reduction. |
| 总页数： | Liu, X. C.; Chen, Z. |
| 报告类型： | 科技报告 |
相关文献
- Development of a Computational Framework for Big Data-Driven Prediction of Long-Term Bridge Performance and Traffic Flow.
- Aeronautical Decision Making - Cockpit Resource Management
- Application of a Project Prioritization Framework to the 2016 SHOPP.
- Synthesis of the "State-of-the-Practice for Advancing Planning and Operations Integration Opportunities within Transportation Agencies", Summary.
- Synthesis of the "State-of-the-Practice for Advancing Planning and Operations Integration Opportunities within Transportation Agencies".
- Performance Measurement Framework for Highway Capacity Decison Making.
检索历史
应用推荐
