Created by W.Langdon from gp-bibliography.bib Revision:1.8081
The perceived comfort levels of on-street bicyclists are affected by both road characteristics and environmental healthiness. A thorough knowledge of these factors helps to encourage bicycle use and improve human health. This study thus aims to incorporate the parameters describing environmental healthiness in the evaluation of urban street performance.
Methods
For analysis purpose, extensive data are collected from sixty street segments of three Indian mid-sized cities. Variables having significant influences on bicycling comfort are identified using Spearman's correlation technique and a {"}Bicycle Comfort Level Rating{"} (BCLR) model is developed using the step-wise regression technique. A service scale is also defined using the Genetic Programming (GP) cluster technique to convert model outputs to letter-graded bicycling comfort levels A-F (excellent-worst).
Results
As observed, the bicycling comfort is influenced by total eight attributes. Of all, air quality index (AQI) is the most significant one (Spearman's correlation coefficient = 0.645). The BCLR model developed using all identified parameters has produced a high coefficient of determination (R2) value of 0.87 with overall observations. Results have also shown that around 97percent segments are offering average-worst levels of bicycling comfort (C-F) at their present scenario.
Conclusion
An unhealthy environment largely discourages the use of bicycles as a choice mode of transport (as the users are more likely to be exposed to environmental hazards). Hence, the improvement in factors like air quality is essential to encourage the bicycling activity. The roadway parameters like traffic volume, road width and roadside commercial activities, etc. should also be prioritized in the planning process to provide better bicycling comfort. The developed BCLR model is highly reliable for its applications in mid-sized cities of India and other developing countries. This model along with other outcomes of this study would be helpful to enhance the quality of bicycling and public health.",
Genetic Programming entries for Sambit Kumar Beura Haritha Chellapilla Mahabir Panda Prasanta Kumar Bhuyan