Efficient road traffic anti-collision warning system based on fuzzy nonlinear programming

Author(s):  
Fei Peng ◽  
Yanmei Wang ◽  
Haiyang Xuan ◽  
Tien V. T. Nguyen
2020 ◽  
Author(s):  
Sizhuo Wang ◽  
Wei Li ◽  
Chunyu Kong

Abstract With the increase of per capita car ownership, traffic accidents frequently occur, in which rear-end collision accounts for 30% to 40% of the total accidents; thus, rear-end collision has become the primary factor of traffic environment deterioration. Therefore, how to improve road traffic safety and reduce the probability of rear-end collision has become a major social concern. In this study, based on the safety pre-warning algorithm, a vehicle collision model was built, and a vehicle anti-collision warning system was established. The calculation was performed based on the sample data to obtain the prediction value of vehicle collision time under different driving speeds, so as to provide drivers with effective response time and reduce the casualties and property losses caused by a vehicle collision. The experimental results showed that the accuracy rate of the pre-warning reached 80% when the speed was regarded as a variable, and the simulation results showed that the early pre-warning or delayed pre-warning rate was very low, and the timeliness rate reached 89%, which enables drivers to react quickly in the appropriate time and effectively reduces the risk of vehicle rear-end collision.


2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Chao Ma ◽  
Wei Dong Liu ◽  
Zhi Ying Tu ◽  
Zhong Jie Wang ◽  
Xiao Fei Xu

The “transboundary”, an emerging phenomenon in the Internet service ecosystem, is leading to the flourishing of innovative services. A transboundary service incorporates services, resources, and technologies from multiple domains into its business to create a particular competitive advantage and unique user experiences. It is difficult to comprehensively consider all the constraints from multiple domains to precisely design the nonfunctional characteristics of transboundary services, such as quality attributes and capability attributes. We propose a two-phase quality design method for transboundary services called value quality deployment-quality capability deployment (VQD-QCD) based on quality function deployment (QFD). Given the restrictions of transboundary services, VQD-QCD translates the value expectations of multiple stakeholders into an optimal configuration for global quality parameters (GQPs), local quality parameters, and capability parameters. Details of VQD are illustrated. Considering the inherent vagueness and uncertainty of relationships between value expectations and GQPs, and among GQPs, fuzzy least absolute regression and fuzzy nonlinear programming methods are incorporated into QFD to identify the quantitative relations between value indicators and GQPs, and among GQPs, and obtain an optimal configuration scheme for GQPs. Usability of the proposed method is validated through a case study on the “DiDi mobile transportation service”, which is a representative transboundary service in China. Compared with the current method, which is inaccurate and inefficient because its translation between value expectations and relevant quality and capability parameters is artificial and subjective, the proposed method integrates fuzzy least absolute regression and fuzzy nonlinear programming methods into QFD, which facilitate transboundary service designers to precisely and efficiently design the quality and capability characteristics of innovative services in the manner of semiautomatisation, which promotes the innovative design of transboundary services.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yongqing Guo ◽  
Xiaoyuan Wang ◽  
Qing Xu ◽  
Quan Yuan ◽  
Chenglin Bai ◽  
...  

Anxiety is a complex emotion characterized by an unpleasant feeling of tension when people anticipate a threat or negative consequence. It is regarded as a comprehensive reflection of human thought processes, physiological arousal, and external stimuli. The actual state of emotion can be represented objectively by human physiological signals. This study aims to analyze the differences of ECG (electrocardiogram) characteristics for various types of drivers under anxiety. We used several methods to induce drivers’ mood states (calm and anxiety) and then conducted the real and virtual driving experiments to collect driver’s ECG signal data. Physiological changes in ECG during the experiments were recorded using the PSYLAB software. The independent sample t-test analysis was conducted to determine if there are significant differences in ECG characteristics for different types of drivers in anxious state during driving. The results show that there are significant differences in ECG signal characteristics of drivers by gender, age, and driving experience, in time domain, frequency domain, and waveform under anxiety. Our findings of this study contribute to the development of more intelligent and personalized driver warning system, which could improve road traffic safety.


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