Research on technical model and method of urban road traffic accident and traffic conflict based on artificial intelligence

Yuan, Yun; Yi, Aijiao; Wang, Yongdong; Chen, Xuwei

doi:10.1145/3510858.3511416

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Robert Cervero and Jin Murakami Pataik [2] used the data of Hong Kong subway to divide the stations into 5 categories through cluster analysis and gave the average value of development intensity and mixing degree 24. Domestic research on station classification mainly uses the characteristics of the station itself and the surrounding environment for qualitative analysis [3][4][5] , with complex and redundant variables, and does not consider the impact of passenger flow fluctuations. With the widespread use of AFC (Automatic fare collection) systems, a large amount of AFC data has been generated, which can accurately record passenger transportation activities and reflect the characteristics of stations.…”

Section: Introductionmentioning

confidence: 99%

Research on classification of urban rail transit stations based on AFC data

Chen

2023

3rd International Conference on Internet of Things and Smart City (IoTSC 2023）

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Urban rail transit has received widespread attention due to its advantages such as fast speed, high punctuality, green and low-carbon. To explore the characteristics of passengers in urban rail transit, a station classification method based on data mining is proposed. Using urban rail transit inbound and outbound swiping data, the station is divided into 5 categories using K-means clustering algorithm, with the inbound and outbound passenger flows of each station as variables during the three periods of the day, morning peak, and evening peak. The results show that the inbound and outbound passenger flow data can better reflect the spatiotemporal characteristics of different types of rail stations. Finally, the passenger travel characteristics of different types of stations are analysed, and the identification study of different types of stations can provide reference for the planning, design, and operation management of rail transit stations.

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Section: Introductionmentioning

confidence: 99%

Research on classification of urban rail transit stations based on AFC data

Chen

2023

3rd International Conference on Internet of Things and Smart City (IoTSC 2023）

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“…Advanced computer technologies such as big data, Artificial Intelligence (AI), cloud computing, digital twins, and edge computing have been applied in various fields along with advances in digitalization (Lv & Xie, 2021). AI is essential in many real-world applications (Yuan et al, 2021) with inconsistent and affected data (Tonni et al, 2021). AI can offer emergency situational awareness and increase the efficiency of emergency response operations (Barachi et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Face detection is performed to warn drivers about drowsiness or to avoid road accidents (Kshirsagar et al, 2022). Road accident-prone points are predicted using AI using the spatial grouping and cumulative frequency curve methods (Yuan et al, 2021). AI exploration in facilitating automatic incident detection systems is used to reduce road accidents (Olugbade et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Road Traffic Accident Prediction

Siswanto,

Syaban,

Hariani

2023

JJi

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The rapid development of AI shows its power and great development potential in practical engineering applications. Critical issues and potential solutions can reduce road traffic accidents and application of AI in road accident prediction. The published use of AI for road accident prediction is reviewed, presented, and represented as the main objective. The methods are collecting article data, quotations, presentation, and representation. The article data collection was obtained from 671 conference and journal articles in 2019-2023, but the suitability of articles that can be used is 69. Quotation produces a grouping of approaches, models, predictions, and benefits. The presentation showed that most approaches used were machine learning, the most used model was random forest, the prediction was mostly about severity, and the most benefit was about number reduction. Representation produces road accidents and related factors into factors in road accident predictions using artificial intelligence, so strategies and anticipation can be made to overcome them to improve road safety. AI in road accident prediction plays an important role in building predictive models with the hope that road accidents can be identified early, risk factors can be reduced, and effective preventive measures can be taken to improve road safety.

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Review of the adaptive Swedish traffic conflict technique: Applications and implications for road traffic safety

Pratama,

Mahmudah

2024

J Appl Eng Science

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The Swedish Traffic Conflicts Technique (STCT) is a systematic approach used to examine traffic conflicts, specifically emphasising the correlation between severe conflicts and accidents. It uses safety indicators such as average speed, post-encroachment time, deceleration rate, time to collision, and traffic flow size to evaluate the gravity of interactions between pedestrian and motorised vehicles. The development of the TCT has been significant, with studies highlighting the impact of speeding, inattentiveness, inadequate following distance, signal violations, drowsiness, excessive alcohol consumption, and reckless driving on road safety. The Adaptive STCT for road traffic safety is a significant area of research and development, aiming to enhance understanding of the global implementation and efficacy of the Adaptive Swedish TCT in enhancing road traffic safety. The STCT has been applied in various countries, including Sao Carlos, Nanjing, Ho Chi Minh City, and Qatar, and has shown significant development in identifying hazardous manoeuvres at urban intersections, facilitating the adoption of safer designs and efficient risk management measures. Nevertheless, research on the STCT's implementation on rural roads is limited; it highlights the need for further investigation and implementation in rural environments due to varying road safety issues.

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Research on technical model and method of urban road traffic accident and traffic conflict based on artificial intelligence

Cited by 3 publications

References 5 publications

Research on classification of urban rail transit stations based on AFC data

Research on classification of urban rail transit stations based on AFC data

Artificial Intelligence in Road Traffic Accident Prediction

Review of the adaptive Swedish traffic conflict technique: Applications and implications for road traffic safety

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