Measuring Collision Risk in Mixed Traffic Flow Under the Car-Following and Lane-Changing Behavior
This study proposes a risk measurement approach to assess collision risks in mixed traffic flow, focusing on the integrated behavior of car-following and lane-changing. A new surrogate safety measure (SSM), denoted as <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/23/11400 |
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| Summary: | This study proposes a risk measurement approach to assess collision risks in mixed traffic flow, focusing on the integrated behavior of car-following and lane-changing. A new surrogate safety measure (SSM), denoted as <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>R</mi></mrow><mrow><mrow><mi>total</mi></mrow></mrow></msub></mrow></semantics></math></inline-formula>, is developed to provide a comprehensive risk assessment. Numerical analysis is used to determine the weights of parameters within <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>R</mi></mrow><mrow><mrow><mi>total</mi></mrow></mrow></msub></mrow></semantics></math></inline-formula>, and its validity is substantiated using an empirical dataset, with a risk threshold of 0.49 established when the time to collision (TTC) is set to 2 s. The study incorporates scenarios of connected and automated vehicle (CAV) degradation and evaluates the influence of penetration rates, perception–reaction time (PRT), and lane-changing modes on risk levels. Simulation results reveal that a CAV penetration rate between 0.4 and 0.6 represents a critical range where collision risks significantly increase, reflecting safety dynamics under CAV degradation. Furthermore, in scenarios involving lane-changing, the degradation of the following vehicle in the target lane poses the highest risk. At lower PRTs, the penetration rate exerts a more significant influence on collision risks. <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>R</mi></mrow><mrow><mi>total</mi></mrow></msub></mrow></semantics></math></inline-formula> has been validated across various scenarios, showing strong applicability and more sensitive trends than other SSMs, making it well-suited for assessing long-term comprehensive traffic flow risks. These findings offer practical guidance for traffic management to establish real-time risk prediction and warning systems for identifying high-risk car-following and lane-changing behaviors. Future research can explore the applicability of the proposed risk index in more complex traffic scenarios and its effectiveness across different levels of vehicle automation and connectivity. |
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| ISSN: | 2076-3417 |