Role of drivers’ personal characteristics in understanding traffic sign symbols

Al-Madani, H. M. N.; Al-Janahi, Abdul Rahman

doi:10.1016/s0001-4575(01)00012-4

Cited by 82 publications

(42 citation statements)

References 13 publications

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“…Hashim Al-Madani built the letter height model of the alphabet (3). Japan conducted research on the letter height of Japanese letters (4), but the results could not be utilized because of the difference in traffic environment, drivers' characters and the configuration of letters.…”

Section: Fig 1 Inadequate Height Of Letters In Guide Signsmentioning

confidence: 99%

Research on Chinese Character Height Model of Guide Signs Based on 3D Technology and Information Processing Characteristics of Chinese Drivers

Huang

Wang

Tang

2010

2010 International Conference on Computational Intelligence and Software Engineering

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Abstract-drivers are often not able to recognize the letter in time and sometimes it is a waste of money with too large letters in guide signs. In order to solve this problem, a new Chinese character height model for guide signs has been developed based on 3D technology and the apperceive characteristics of Chinese drivers. The model was built according to the visual and kinematic theory based on the legibility process of drivers. Then the key parameters of the model were validated by some special designed simulation experiments. The experiment was designed to determine the minimum visual angle needed. The relationship between the information units and the reaction time was studied based on 3D technology. The disappearing distance was computed according to the geometric relationship concerning about road width, the height of the sign and the disappearing angle. In the end, the letter height for various design speed was computed and compared with the value specified in the standard. The results revealed that the height value of Chinese characters in guide signs which was computed in the model has a relatively good consistence with the current value in national standard, but the value in the standard is a bit small for high speeds and high for low speed. The model of Chinese letter height was built at the first time and it is projected to play a big role in the traffic safety.

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Section: Fig 1 Inadequate Height Of Letters In Guide Signsmentioning

confidence: 99%

Research on Chinese Character Height Model of Guide Signs Based on 3D Technology and Information Processing Characteristics of Chinese Drivers

Huang

Wang

Tang

2010

2010 International Conference on Computational Intelligence and Software Engineering

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“…For example, according to a crash causation survey released by the US National Highway Traffic Safety Administration (NHTSA) in 2015 [2,3], drivers are to be criticised for 94% of crash cases. Apparently, the 94% of such accidents are also related to other causes from common experience, such as road alignment [4][5][6], traffic sign [7][8][9], and weather condition [10][11][12]. Therefore, the existing road accident statistics cannot fully reveal the causes, and traffic…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica

Zou

Yue

2017

Journal of Advanced Transportation

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Based on an overall consideration of factors affecting road safety evaluations, the Bayesian network theory based on probability risk analysis was applied to the causation analysis of road accidents. By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts' knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. Then Netica was used to carry out posterior probability reasoning, the most probable explanation, and inferential analysis. The results showed that the Bayesian network model could effectively explore the complex logical relation in road accidents and express the uncertain relation among related variables. The model not only can quantitatively predict the probability of an accident in certain road traffic condition but also can find the key reasons and the most unfavorable state combination which leads to the occurrence of an accident. The results of the study can provide theoretical support for urban road management authorities to thoroughly analyse the induction factors of road accidents and then establish basis in improving the safety performance of the urban road traffic system.

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“…In so doing, generally traffic signs may function effectively because of the effects arising from non-design and design factors [7]. The non-design factors refer to factors associated with humans who see the warning signs, such as drivers' comprehension of the traffic signs [8]- [9]- [6]- [5]- [11]- [13]. In addition to the design and non-design factors, effectiveness of traffic signs also depends on the driving ability or skill and experience.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the design and non-design factors, effectiveness of traffic signs also depends on the driving ability or skill and experience. It is influenced by a number of factors such as the age of a driver [14], the type of driver's license owned, the length of time a driver has obtained driver's license, the type of vehicle usually used, the range and frequency of driving a vehicle, as well as the average mileage per day [8]- [9]- [13]- [10]- [11].…”

Section: Introductionmentioning

confidence: 99%

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Drivers

2016

IJSR

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Effectiveness of a traffic sign is greatly influenced by design and non-design factors. The non-design factors are influenced, among other things, by drivers' driving skills and comprehension of the meaning of such signs. Questionnaires distributed to a total of 202 respondents who have obtained driver's license and are domiciled in Soloraya region. These questionnaires examine these respondents' comprehension of the existing 15 traffic signs. Based on the response provided by the respondents, it is revealed that 67% of the respondents has the correct comprehension of the traffic signs meaning. The F-test indicates that the variables of age, sex, education, occupation, type of driver's license owned and the length of time driver's license simultaneously bring a significant effect on the obtained score for the respondents' comprehension, but only the variable of the type of driver's license owned which partially has a significant effect on the respondents' comprehension of the traffic signs.

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Role of drivers’ personal characteristics in understanding traffic sign symbols

Cited by 82 publications

References 13 publications

Research on Chinese Character Height Model of Guide Signs Based on 3D Technology and Information Processing Characteristics of Chinese Drivers

Research on Chinese Character Height Model of Guide Signs Based on 3D Technology and Information Processing Characteristics of Chinese Drivers

A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica

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