An Autonomous Intelligent Liability Determination Method for Minor Accidents Based on Collision Detection and Large Language Models
Abstract
:1. Introduction
2. Methodology
2.1. YOLOv8 Network
2.2. “Minimum Output Sum of Squared Error” Tracking Algorithm
2.3. Horn and Schunck Algorithm
2.4. Multimodal Large Language Model
3. Fully Intelligent Accident Liability Determination Method Based on Collision Detection
3.1. Vehicle Recognition and Tracking
3.2. Vehicle Target Tracking Based on Minimum Error Square Filter
3.3. Accident Identification Based on Collision Detection
3.3.1. Calculation of the Amplitude Change in the Optical Flow Vector
3.3.2. Collision Detection Classification Based on SVM
3.4. Responsibility Determination Method Based on Multimodal Large Language Model
3.4.1. Key Frames Extraction Based on K-Means Algorithm
3.4.2. GPT4-V API Access
4. Experimental Analysis
4.1. Experimental Parameter Settings
4.2. Vehicle Recognition Accuracy
4.3. Tracking Performance
4.4. Collision Detection Efficacy
4.4.1. Effectiveness of the Improved HS Algorithm
4.4.2. Performance of SVM Collision Detection
4.5. Accident Liability Assessment
4.5.1. Key Frame Extraction Evaluation
4.5.2. Accident Liability Determination Results
4.6. Analysis of the Impact of Image and Text Information on Liability Determination Results
4.6.1. Experiment 1
4.6.2. Experiment 2
5. Discussion
5.1. Limitations of the Algorithm
5.2. Challenges in Real-World Implementation
5.3. Legal and Ethical Considerations
5.4. Future Work
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Tracking Algorithm | FPS |
---|---|
MOSSE | 615 |
TLD | 28 |
Struck | 20 |
MIL | 38 |
ORIA | 9 |
CT | 64 |
Configuration Item | Configuration Information |
---|---|
Operating system | Windows 10 |
Development language | Python 3.7.16 |
CPU | 11th Gen Intel(R) Core (TM) i5-11400H @ 2.70GHz 2.69 GHz |
GPU | Intel(R) UHD Graphics/NVIDIA GeForce RTX 3050 Ti Laptop GPU |
Memory | 16GB |
Parameter | Description | Value |
---|---|---|
Pre-trained weights | Path to the pre-trained YOLOv8 weights file | YOLOv8s.pt |
Epochs | Number of training cycles | 15 |
Batch size | Number of images processed per batch | 4 |
Image size | Dimensions of the images used in training (pixels) | 640 × 640 |
Worker processes | Number of worker processes for data loading | 4 |
Weather | Recall (%) | Precision (%) | F1-Score (%) | AP (%) |
---|---|---|---|---|
Cloudy | 50.42 | 98.74 | 67.55 | 92.77 |
Night | 48.55 | 97.89 | 65.92 | 89.97 |
Rainy | 50.68 | 98.92 | 67.76 | 93.18 |
Sunny | 52.11 | 98.99 | 67.88 | 94.56 |
Algorithm | AEE | Angle Error | FPS |
---|---|---|---|
Improved HS algorithm | 12.02 | 66.09° | 5.26 |
Classic HS algorithm | 13.32 | 66.88° | 6.25 |
Traffic Accident Liability Determination |
---|
I. Basic Situation:
|
On a highway without traffic lights, an elderly person suddenly crossed the road. To avoid the elderly person, the driver of the white car braked urgently, and the black car behind failed to brake in time due to excessive speed, and collided with the white car. At the same time, a truck was also present, but it only rotated and did not collide with other vehicles. |
II. Accident Evidence and Analysis:
|
III. Fault and responsibility analysis:
|
Supplementary Text Information | Text Information Qualitative | Responsibility Determination Result |
---|---|---|
The driver of the white car claimed that he stopped so suddenly to avoid the old man, so he was not responsible; the driver of the black car claimed that the driver of the white car stopped suddenly and did not have time to brake, so the responsibility should be on the driver of the white car. | In this scenario, the model needs to fairly analyze the relevance of these conflicting statements with other evidence to make a balanced judgment of responsibility. | Article 43 of the “Road Traffic Safety Law of the People’s Republic of China” stipulates that the rear car should maintain a safe distance from the front car sufficient to take emergency braking measures. The driver of the black car failed to maintain a sufficient safe distance and failed to brake in time, so should bear all the responsibility for this accident. During the emergency braking process, the driver of the white car avoided pedestrians who suddenly crossed the road. His behavior was reasonable defense and complied with relevant road traffic safety regulations. He did not violate Article 47 of the “Road Traffic Safety Law of the People’s Republic of China” regarding stopping to let pedestrians pass. Therefore, the driver of the white car was not responsible. In summary, the driver of the black car was fully responsible and the driver of the white car was not responsible. |
\ | In such cases, the model must rely entirely on objective data and laws to make an independent and unbiased judgment. | According to the relevant provisions of the Road Traffic Safety Law of the People’s Republic of China, the white car did not ensure safety when turning, which violated the provisions that motor vehicles should slow down or stop to give way when encountering vehicles turning left in front (Article 44), and was primarily responsible. The black car failed to control its speed, which violated the provisions that motor vehicles should maintain a safe speed according to road, traffic, weather and other conditions (Article 42), and was secondarily responsible. Responsibility ratio: The white car was responsible for 70% of the accident, and the black car was responsible for 30%. |
It did not rain today. There were two people sitting in the white car and the white truck was full of eggs. | The model needs to filter out such irrelevant information to maintain focus on the pertinent facts and ensure the accuracy of the liability determination. | Article 43 of the Road Traffic Safety Law of the People’s Republic of China: It is stipulated that the rear vehicle should maintain a safe distance from the front vehicle sufficient to take emergency braking measures. Liability determination: The driver of the black car failed to maintain a sufficient safety distance and failed to brake in time, so should bear all the responsibility for this accident. Article 47 of the Road Traffic Safety Law of the People’s Republic of China: It is stipulated that motor vehicles should slow down when passing through crosswalks; when pedestrians are crossing the sidewalk, they should stop and give way. Liability determination: The driver of the white car was in reasonable defense during emergency braking to avoid pedestrians who suddenly crossed the road. He complied with the relevant laws and regulations on road traffic safety and did not violate the above regulations. Therefore, the driver of the white car was not responsible. |
The white car deliberately braked urgently, leaving the black car no time to react, resulting in a tragedy. | The model must identify and exclude any misleading or incorrect information to preserve the fairness and integrity of the judgment. | The driver of the white car violated Article 42 of the Road Traffic Safety Law of the People’s Republic of China, which stipulates that drivers should pay attention to driving safety and avoid emergency braking without reason. According to the accident form and evidence, the sudden deceleration of the white car was the main cause of the accident. Although the driver of the black car maintained the necessary distance between vehicles, he failed to take effective evasive measures, violating the safe driving requirements of taking emergency avoidance measures in response to emergencies. According to the provisions of the Road Traffic Safety Law and relevant regulations, the driver of the white car bears the main responsibility for the accident, and the driver of the black car bears secondary responsibility. The responsibility ratio is 70% for the white car and 30% for the black car. |
There was a young couple in the white car. The weather was good today. The driver of the white car suddenly stopped to avoid the elderly. The black car was about 20 m away from the white car when driving. | The model needs to filter out irrelevant details while extracting key information to ensure an accurate responsibility determination. | The white car braked to avoid pedestrians, which is a normal driving behavior. The black car failed to maintain a safe distance and failed to react to the sudden stop of the vehicle behind, which violated the safe distance requirements stipulated in Article 43 of the Road Traffic Safety Law of the People’s Republic of China. Responsibility determination: The driver of the black car is fully responsible. The driver of the white car is not responsible. |
The white car was forced to brake suddenly because the vehicle in front braked. The black car followed closely behind and failed to stop in time, hitting the white car. At the same time, another car behind the black car also failed to brake and hit the black car. | Here, the model must navigate through a multi-vehicle accident scenario, assessing each vehicle’s actions and making a comprehensive judgment on liability. | How the accident happened: According to surveillance video and on-site photos, the black car failed to maintain a safe distance during driving and collided with the white car in front. When the accident occurred, the white car was driving normally in the right lane of the road, and the black car followed closely behind. The white car braked normally due to an emergency in front, and the black car failed to respond in time, resulting in a rear-end collision. Fault and responsibility analysis: The driver of the black car failed to maintain a safe distance, violating Article 43 of the Road Traffic Safety Law that vehicles should maintain a safe distance sufficient to take emergency braking measures. The driver of the white car drove normally and did not have obvious violations. Responsibility determination: The driver of the black car bears the main responsibility for this accident, and the driver of the white car is not responsible. |
The road was snowy and very slippery. The white car skidded and lost control when turning. The black car behind it was unable to brake in time because the road was too slippery and hit the white car. | This scenario reflects the model’s performance when faced with traffic accidents caused by bad road conditions (such as snow, slippery, etc.), especially how to distinguish the responsibility for accidents caused by external conditions. | How the accident happened: According to the surveillance video and photos taken at the scene, the white car lost control and skidded at the turn due to the slippery snow on the road. The black car following closely behind failed to brake in time due to the same slippery road conditions, resulting in a collision with the white car in front. Fault and responsibility analysis: When driving on the slippery road, the driver of the white car failed to effectively control the speed and stability of the vehicle, violating Article 42 of the Road Traffic Safety Law on appropriately reducing the speed according to road conditions. The driver of the black car followed the car too closely under the same road conditions and failed to maintain a safe distance, which also violated Article 43 of the Road Traffic Safety Law. Responsibility determination: The driver of the white car bears the main responsibility, and the driver of the black car bears secondary responsibility. |
The driver of the white car suddenly became ill, causing the vehicle to lose control and stop suddenly. The black car behind it had no time to react and rear-ended it. | In this scenario, the model needs to account for the sudden health issue as a contributing factor, balancing it against the actions of the other driver to determine liability. | How the accident happened: According to the surveillance video and photos taken at the scene, the driver of the white car suddenly stopped due to illness, and the black car followed closely behind and failed to react in time, causing a rear-end collision with the white car in front. Fault and liability analysis: The driver of the white car lost control of the vehicle due to a sudden illness, which is a force majeure. According to Article 63 of the Road Traffic Safety Law, he shall not be liable in case of emergency avoidance. The driver of the black car failed to maintain a safe distance from the car in front and failed to take timely measures to avoid the accident, which violated Article 43 of the Road Traffic Safety Law that the rear car should maintain a safe distance. The driver of the black car bears the main responsibility for this accident. |
Changes in Image Input | Input Explanation | Responsibility Determination Result |
---|---|---|
Figure 14 | The frame at the moment of collision was removed from the eight key frames. | Fault and liability of the parties causing the road traffic accident or accidental cause Elderly woman: According to Article 62 of the Road Traffic Safety Law of the People’s Republic of China, “Pedestrians shall use crosswalks or pedestrian crossing facilities when passing through intersections or crossing roads”. The elderly woman did not comply with this provision, which directly led to the white car taking emergency measures. Therefore, she bears primary responsibility for the accident. Driver of the white car: His behavior was an emergency avoidance, but he did not consider the risks that emergency braking might bring to the rear vehicle, so he bears secondary responsibility. Driver of the black car: He failed to maintain a safe distance, which violated Article 43 of the Road Traffic Safety Law of the People’s Republic of China, “For motor vehicles traveling in the same lane, the rear vehicle shall maintain a safe distance from the front vehicle sufficient to take emergency braking measures”. Therefore, he bears secondary responsibility for the accident. |
Figure 15 | Key information at the moment of collision is obscured | How the accident happened: A was driving a white car along the main road. Because an old man suddenly crossed the road in front of him, he stopped suddenly to avoid him. B was driving a black car about 20 m behind. Due to the high speed, he failed to react in time and rear-ended the white car. Responsibility determination: According to the “Road Traffic Safety Law of the People’s Republic of China”: A’s behavior was a normal risk avoidance behavior and he was not at fault. B failed to maintain a safe distance and drove at a high speed, which violated Article 43 of the “Road Traffic Safety Law” and should bear the main responsibility. |
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Share and Cite
Chen, J.; Lu, S.; Zhong, L. An Autonomous Intelligent Liability Determination Method for Minor Accidents Based on Collision Detection and Large Language Models. Appl. Sci. 2024, 14, 7716. https://doi.org/10.3390/app14177716
Chen J, Lu S, Zhong L. An Autonomous Intelligent Liability Determination Method for Minor Accidents Based on Collision Detection and Large Language Models. Applied Sciences. 2024; 14(17):7716. https://doi.org/10.3390/app14177716
Chicago/Turabian StyleChen, Junbo, Shunlai Lu, and Lei Zhong. 2024. "An Autonomous Intelligent Liability Determination Method for Minor Accidents Based on Collision Detection and Large Language Models" Applied Sciences 14, no. 17: 7716. https://doi.org/10.3390/app14177716