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http://210.212.227.212:8080/xmlui/handle/123456789/432| Title: | PERCEPTION OF PEDESTRIANS TOWARDS THE USE OF FOOTBRIDGE |
| Authors: | Anaswara, R Adarsh, S |
| Keywords: | Machine learning techniques Footbridge |
| Issue Date: | 30-Jul-2023 |
| Series/Report no.: | ;TKM21CETE01 |
| Abstract: | Pedestrians are the most vulnerable group of road users. In order to protect the pedestrians from fatalities while crossing through at grade crosswalks, grade separated crossing facilities are provided. But they are sparsely used by the pedestrians. Using zebra crossing has become part of their habitual action. Pedestrians are not willing to use footbridge even though they are safe. The study aims to identify factors influencing the non-usage of footbridge using perception survey. Machine learning techniques was used to analyze the data. Different algorithms such as random forest, decision tree, support vector machine, k-nearest neighbor and logistic regression were compared to get best model. Random forest outperformed all other model with an accuracy of 83%. The weightage of factors was computed using random forest. It was found that frequency of using footbridge has a high weightage among other factors. It was followed by easiness, stressful, weather, tiresome, night, bad infrastructure, heavy traffic, height fear, unfamiliar location, accessibility, hurry, good illumination, education, age, pedestrian accident history and occupation. Some counter measures such as escalator, alerting poster, fine for illegal crossing, seating arrangement, security staff are suggested in the study to identify the change in usage of footbridge among non-users. Most of the pedestrians are willing to use footbridge if escalator or elevator is provided. To promote footbridge utilization, a usercentered strategy is necessary. |
| URI: | http://210.212.227.212:8080/xmlui/handle/123456789/432 |
| Appears in Collections: | 2023 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Anaswara.pdf | 1.64 MB | Adobe PDF | View/Open |
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