Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System
Abstract
:1. Introduction
2. Aggressive Driving of Two-Wheeled Vehicles
2.1. Definition of Aggressive Driving
2.2. Aggressive Driving Identification
2.2.1. Image-Based Identification
2.2.2. GIS-Based Identification
2.2.3. Inertial-Sensor-Based Identification
3. Two-Wheeled Vehicle Evaluation System
3.1. Attachment-Type Aggressive Driving Sensing Device for Two-Wheeled Vehicle
3.2. System Overview
3.2.1. Sensing Model
3.2.2. Driving Evaluation
4. Experiments/Applications
5. Conclusions
6. Patents
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
ACC | Advanced Cruise Control |
AHD | Analog High Definition |
AHP | Analytic Hierarchy Process |
ARAS | Advanced Rider Assistance System |
BLE | Bluetooth Low Energy |
CNN | Convolution Neural Network |
COVID-19 | Coronavirus Disease 2019 |
CPU | Central Processing Unit |
DTG | Digital Tachograph |
eTAS | Electronic Traffic Assessment Score |
GNSS | Global Navigation Satellite System |
GPS | Global Positioning System |
HMI | Human–Machine Interface |
HTTPS | Hypertext Transfer Protocol Secure |
IMU | Inertial Measurement Unit |
LED | Light Emitting Diode |
LSTM | Long Short-Term Memory |
OpenAPI | Open Application Programming Interface |
RPM | Revolutions Per Minute |
RTK | Real-Time Kinematic |
TAAS | Traffic Accident Analysis System |
UBI | Usage-Based Insurance |
WFS | Web Feature Service |
WMS | Web Map Service |
XGBoost | Extreme Gradient Boosting |
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Main Criteria | Sub-Criteria | Results of Two-Wheeled Vehicle Traffic Accident Type Analysis | |
---|---|---|---|
1 | Traffic Violations | Signal Violation | Based on 2017–2021 data for motorcycle accidents in Seoul, Incheon, and Gyeonggi, signal violations account for approximately 23.8% of all accidents. In a survey conducted by the Korea Road Traffic Safety Corporation on signal violation among motorcycles on the roads of Seoul, it constitutes about 48.8% of all violation cases. |
2 | Reverse Lane Driving | In a survey conducted by the Korea Road Traffic Safety Corporation on wrong-way driving among motorcycles on the roads of Seoul, it constitutes about 3.1% of all violation cases. | |
3 | Central Line Violation | Based on 2017–2021 data for motorcycle accidents in Seoul, Incheon, and Gyeonggi, crossing the centerline accounts for approximately 5% of all accidents. In a survey conducted by the Korea Road Traffic Safety Corporation on crossing the centerline among motorcycles on the roads of Seoul, it constitutes about 5.8% of all violation cases. | |
4 | Speed Violation | In a study of the fatality rates for different types of motorcycle accidents, including speeding, crossing the centerline, and signal violation, speeding exhibits the highest fatality rate at 22.2%. | |
5 | Helmet Non-Usage | According to the 2017–2021 data from the Korean National Police Agency, failure to wear protective headgear, such as helmets, accounts for approximately 50% (around 800,000 cases) of all violations. Among the causes of motorcycle accident-related fatalities, head injuries rank first at a dominant 67.1%. | |
6 | Pedestrian Threat | Proximity to Pedestrians | Based on 2017–2021 data for motorcycle accidents in Seoul, Incheon, and Gyeonggi, cases involving pedestrians as victims constitute about 18% of all accidents (compared to about 48% for passenger vehicles). |
7 | Riding on Sidewalks | According to the 2017–2021 data from the Korean National Police Agency, cases of motorcycles riding on sidewalks account for approximately 5% of all violations. In a survey conducted by the Korea Road Traffic Safety Corporation on motorcycles riding on sidewalks in Seoul, it constitutes about 11.2% of all violation cases. | |
8 | Reckless Driving | Rapid Acceleration | Motorcycles exhibit significantly higher acceleration per unit weight compared to standard vehicles. |
9 | Rapid Deceleration | Jackknife effect: In cases of motorcycles or vehicles with a short wheelbase, abrupt braking leads to a shift in weight towards the front, causing the rear wheel to lift and skid. | |
10 | Rapid Turns | According to the Traffic Accident Analysis System (TAAS), over half of the 4035 motorcycle accidents in Seoul in 2021 occurred at intersections. | |
11 | Rapid Lane Changes | The Traffic Accident Analysis System (TAAS) defines lane violations, improper lane usage, overtaking violations, and obstructing straight or right turns as motorcycle accident types. |
Main Criteria | Sub-Criteria | Method | References | |
---|---|---|---|---|
1 | Traffic Violations | Signal violation | Based on Images | [12,13,14] |
2 | Reverse lane driving | Based on GIS | [15,16] | |
3 | Central line violation | Based on GIS | [17,18,19] | |
4 | Speed violation | Based on GIS | [20,21,22] | |
5 | Helmet non-usage | Based on Images | [23,24,25,26] | |
6 | Pedestrian Threat | Proximity to pedestrians | Based on Images | [27,28,29,30,31] |
7 | Riding on sidewalks | Based on Images/GIS | [32,33] | |
8 | Reckless Driving | Rapid acceleration | Based on Inertial Sensor | [34,35,36,37,38] |
9 | Rapid deceleration | Based on Inertial Sensor | ||
10 | Rapid turns | Based on Inertial Sensor | ||
11 | Rapid lane changes | Based on Inertial Sensor |
Main Criteria | Sub-Criteria | Weight | |
---|---|---|---|
1 | Traffic Violations | Signal violation | 0.082 |
2 | Reverse lane driving | 0.060 | |
3 | Central line violation | 0.096 | |
4 | Speed violation | 0.124 | |
5 | Helmet non-usage | 0.158 | |
6 | Pedestrian Threat | Proximity to pedestrians | 0.122 |
7 | Riding on sidewalks | 0.078 | |
8 | Reckless Driving | Rapid acceleration | 0.098 |
9 | Rapid deceleration | 0.098 | |
10 | Rapid turns | 0.044 | |
11 | Rapid lane changes | 0.040 |
Cost (Time) 1 | Cost (Distance) | Score | Aggressive Driving Event 2 | ||||
---|---|---|---|---|---|---|---|
Normal | Acc. | Dcc. | Turn. | ||||
Ped. | Sig. | Speed. | Helmet. | ||||
User A | 3 day. 15 h. | 1544.330 km | 83.237 | 79.350% | 0.460% | 0.090% | 0.248% |
0.465% | 0.002% | 19.384% | |||||
User B | 12 day. 7 h. | 4485.452 km | 85.21 | 78.653% | 1.383% | 0.233% | 0.178% |
0.036% | 0.003% | 19.513% | 0.001% | ||||
User C | 2 day. 2 h. | 1008.265 km | 84.44 | 82.141% | 1.245% | 0.244% | 0.356% |
0.002% | 16.013% | ||||||
User D | 6 day. 2 h. | 2215.477 km | 99.985 | 81.269% | 0.603% | 0.103% | 0.083% |
17.953% |
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Kim, D.; Kim, H.; Lee, S.; Lee, Q.; Lee, M.; Lee, J.; Jun, C. Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System. Sensors 2024, 24, 4739. https://doi.org/10.3390/s24144739
Kim D, Kim H, Lee S, Lee Q, Lee M, Lee J, Jun C. Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System. Sensors. 2024; 24(14):4739. https://doi.org/10.3390/s24144739
Chicago/Turabian StyleKim, Dongbeom, Hyemin Kim, Suyun Lee, Qyoung Lee, Minwoo Lee, Jooyoung Lee, and Chulmin Jun. 2024. "Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System" Sensors 24, no. 14: 4739. https://doi.org/10.3390/s24144739
APA StyleKim, D., Kim, H., Lee, S., Lee, Q., Lee, M., Lee, J., & Jun, C. (2024). Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System. Sensors, 24(14), 4739. https://doi.org/10.3390/s24144739