Abstract
The interchange merging area suffers a high crash risk in the freeway system, which is greatly related to the intense mandatory merging maneuvers. Ignoring such correlation may result in limited and biased conclusions and inefficient countermeasures. Recently, the availability of unmanned aerial vehicle (UAV) provides us an opportunity to collect individual vehicle's data to conduct traffic analysis at the microscopic level. Hence, this paper contributes to the literature by proposing a new framework to analyze crash risk at freeway interchange merging areas considering drivers’ merging behavior. The analysis framework is conducted based on individual vehicle data from UAV videos. A multilevel random parameters logistic regression model is proposed to investigate each driver's merging behavior in the acceleration lane. The model could identify the impact of different factors related to traffic and drivers on the merging behavior. Then, the crash risk between the merging vehicle and surrounding vehicles is calculated by incorporating the time-to-collision (TTC) and the output of the estimated merging behavior's model. The results suggest that the proposed method provides more valuable insights about the crash risk at interchange merging areas by simultaneously considering the merging behavior and the safety measure. It is concluded that the merging speed, driving ability (e.g., lane change confidence, lane-keeping instability), and the merging location can affect the crash risk. These results can help traffic engineers propose efficient countermeasures to enhance the safety of the interchange merging area. The results also have implications to the design of merging areas and the advent of connected vehicles’ technology.
| Original language | English |
|---|---|
| Pages (from-to) | 159-169 |
| Number of pages | 11 |
| Journal | Accident Analysis and Prevention |
| Volume | 123 |
| DOIs | |
| State | Published - Feb 2019 |
| Externally published | Yes |
Funding
The study was funded by the Fundamental Research Funds for the Central Universities and Postgraduate Research & Practice Innovation Program of Jiangsu Province ( KYLX16_0274 ), and China’s National Science and Technology Plan of Action for Traffic safety ( 2014BAG01B01 ), the National Natural Science Foundation of China (No. 71871059 ). The authors acknowledge the assistance provided by the graduate research assistants Zhanji Zheng and Fulin Chen, at the School of Transportation, Southeast University, in field data collection. Part of the research was conducted at the University of Central Florida where the first author spent a year as a visiting student funded by China Scholarship Council.
Keywords
- Crash risk
- Interchange
- Merging behavior
- UAV