Dataset Information

Quantifying the Effects of Visual Road Information on Drivers' Speed Choices to Promote Self-Explaining Roads.

ABSTRACT: Roads should deliver appropriate information to drivers and thus induce safer driving behavior. This concept is also known as "self-explaining roads" (SERs). Previous studies have demonstrated that understanding how road characteristics affect drivers' speed choices is the key to SERs. Thus, in order to reduce traffic casualties via engineering methods, this study aimed to establish a speed decision model based on visual road information and to propose an innovative method of SER design. It was assumed that driving speed is determined by road geometry and modified by the environment. Lane fitting and image semantic segmentation techniques were used to extract road features. Field experiments were conducted in Tibet, China, and 1375 typical road scenarios were picked out. By controlling variables, the driving speed stimulated by each piece of information was evaluated. Prediction models for geometry-determined speed and environment-modified speed were built using the random forest algorithm and convolutional neural network. Results showed that the curvature of the right boundary in "near scene" and "middle scene", and the density of roadside greenery and residences play an important role in regulating driving speed. The findings of this research could provide qualitative and quantitative suggestions for the optimization of road design that would guide drivers to choose more reasonable driving speeds.

SUBMITTER: Qin Y

PROVIDER: S-EPMC7177682 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Publications

Quantifying the Effects of Visual Road Information on Drivers' Speed Choices to Promote Self-Explaining Roads.

Qin Yuting Y Chen Yuren Y Lin Kunhui K

International journal of environmental research and public health 20200403 7

Roads should deliver appropriate information to drivers and thus induce safer driving behavior. This concept is also known as "self-explaining roads" (SERs). Previous studies have demonstrated that understanding how road characteristics affect drivers' speed choices is the key to SERs. Thus, in order to reduce traffic casualties via engineering methods, this study aimed to establish a speed decision model based on visual road information and to propose an innovative method of SER design. It was ...[more]

PMID: 32260129

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Project description:Road development is occurring at an unprecedented rate in important conservation areas in tropical countries with limited understanding of how local people will adjust their livelihood activities in response. We use a discrete choice experiment to explore the effect of road development on respondents ex-ante preferences for changes in livelihood activities-crop and livestock production, hunting and trading bushmeat, and business and wage employment-under different incentives-provision of loans, livestock and crop extension services-in scenarios with reduced travel time to nearest district town in the Greater Serengeti Ecosystem in Tanzania. We test four hypotheses about the effects of roads with opposing implication for conservation. Hypothesis 1 predicts that increased market access will lead to intensification of crop and livestock production activities (achieved through extension services and loans), and Hypothesis 2 that market access will facilitate the development of non-farm Micro, Small and Medium Enterprises (MSME) providing new livelihood opportunities (e.g. business income and wage employment)-both reducing environmental pressure. Hypotheis 3 on the other hand predicts that improved market access will lead to extensification and expansion of crop and livestock production activities, while Hypotheis 4 suggests that it will encourage exploitation of environmental goods (here in the form of hunting and trading bushmeat and illegal grazing inside protected areas)-both increasing environmental pressure. We find increasing preferences for more cropland and more cattle as travel time to market is reduced but no preference for increased allocation of household members to hunting and trading bushmeat supporting hypothesis 3 while contradicting hypothesis 4. However, second-order effects might support hypothesis 4 as we find aversion towards decreasing effort invested in hunting and trading bushmeat. Preferences for increased cropland and livestock may furthermore interact to increase land use change and illegal grazing inside protected areas. Crop extension services had a negative modifying effect on preferences for more cropland (supporting hypothesis 1) while livestock extension services had a positive modifying effect on preferences for more cattle (contradicting hypothesis 1). Providing loans had a negative modifying effect on preferences for increasing cropland and number of cattle. Marginal rates of substitution suggest that 950,000 TSH borrowed at a 10% interest rate will reduce preferences for more cropland and cattle by 11.8 and 38.4% respectively. Crop extension services reduce preferences for more cropland by 27% whereas livestock extension services increase preferences for more cattle by 104%. Contradicting Hypothesis 2, we found no preference for increasing the number of households members engaged in business and wage employment in response to reduced travel time. Targeted efforts to increase the educational level as well as entrepreneurship skills in the GSE could promote engagement in the labour market and development of business enterprises diverting focus from traditional activities such as farming and livestock production and hence reducing pressure on the ecosystem.

Dataset Information

Quantifying the Effects of Visual Road Information on Drivers' Speed Choices to Promote Self-Explaining Roads.

Publications

Quantifying the Effects of Visual Road Information on Drivers' Speed Choices to Promote Self-Explaining Roads.

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