Research on Safety Lane Change Warning Method Based on Potential Angle Collision Point

Ding, Tongqiang; Li, Xiaorong; Zheng, Longxi; Hao, Zhiguo

doi:10.1155/2019/1281425

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…The proposed combined AHP-BWM approach could help decision-makers to focus on highlighted significant factors affecting frequent lane-changing to improve road safety. Previous studies recommended the application of lane-change assisting systems to improve active safety and reduce traffic accidents due to frequent lane-changing [72].…”

Section: Discussionmentioning

confidence: 99%

Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model

Farooq

Moslem

Jamal

et al. 2021

IJERPH

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Frequent lane changes cause serious traffic safety concerns for road users. The detection and categorization of significant factors affecting frequent lane changing could help to reduce frequent lane-changing risk. The main objective of this research study is to assess and prioritize the significant factors and sub-factors affecting frequent lane changing designed in a three-level hierarchical structure. As a multi-criteria decision-making methodology (MCDM), this study utilizes the analytic hierarchy process (AHP) combined with the best–worst method (BWM) to compare and quantify the specified factors. To illustrate the applicability of the proposed model, a real-life decision-making problem is considered, prioritizing the most significant factors affecting lane changing based on the driver’s responses on a designated questionnaire survey. The proposed model observed fewer pairwise comparisons (PCs) with more consistent and reliable results than the conventional AHP. For level 1 of the three-level hierarchical structure, the AHP–BWM model results show “traffic characteristics” (0.5148) as the most significant factor affecting frequent lane changing, followed by “human” (0.2134), as second-ranked factor. For level 2, “traffic volume” (0.1771) was observed as the most significant factor, followed by “speed” (0.1521). For level 3, the model results show “average speed” (0.0783) as first-rank factor, followed by the factor “rural” (0.0764), as compared to other specified factors. The proposed integrated approach could help decision-makers to focus on highlighted significant factors affecting frequent lane-changing to improve road safety.

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Section: Discussionmentioning

confidence: 99%

Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model

Farooq

Moslem

Jamal

et al. 2021

IJERPH

View full text Add to dashboard Cite

show abstract

“…However, this performance metric is adopted primarily in simple test scenarios, for example, car‐following manoeuvres. In this study, the minimum relative distances between the HV and SVs [32] and corresponding relative velocities, which represent the likelihood of impending collision between the HV and SVs, are taken as the performance metrics. Smaller minimum relative distances and larger relative velocities between the HV and SVs will increase the risk of driving.…”

Section: Methodsmentioning

confidence: 99%

Risk analysis of autonomous vehicle test scenarios using a novel analytic hierarchy process method

Zhang,

Tak

2023

IET Intelligent Trans Sys

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Scenario‐based test methods are employed to assess the safety and performance of autonomous vehicles. The analytic hierarchy process (AHP) method is a common assessment method for determining the criticality of test scenarios. However, the AHP method is subjective and less reproducible when performed by different persons, as the elements of pairwise comparison values that are directly linked to the outcome must be assigned by the person involved. This paper proposes a novel AHP method that automatically generates pairwise comparison values by optimizing the correlation between performance metrics and risk of test scenarios by simulation. Performance metrics are defined as the minimum relative distances and corresponding relative velocities between vehicles, and the risk of the test scenario is determined by the pairwise comparison values of AHP. The novel AHP method was evaluated using a cut‐in scenario. The results showed that the minimum relative distance and the risk determined by the novel AHP method achieved a better correlation coefficient of −0.96, which is better than the conventional AHP of −0.828 and Fuzzy AHP of −0.824. These results suggest that the criticality of the test scenarios determined by the novel AHP method can more accurately reflect real‐world driving environments.

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Vehicle Collision Warning Method Based on Trajectory Prediction

Wang

Yang

2021

Application of Intelligent Systems in Multi-Modal Information Analytics

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Research on Safety Lane Change Warning Method Based on Potential Angle Collision Point

Cited by 6 publications

References 22 publications

Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model

Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model

Risk analysis of autonomous vehicle test scenarios using a novel analytic hierarchy process method

Vehicle Collision Warning Method Based on Trajectory Prediction

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