Problem faced by the student Due to Traffic.
Authors: Shubham Vishwakarma – 123, Ajaykumar Odyar- 99.
Introduction:
The challenges posed by traffic congestion have become a prevalent issue affecting students in various aspects of their academic lives. From delayed arrivals leading to missed classes and exams to heightened stress levels impacting mental well-being, the repercussions of traffic-related problems are multifaceted. Reduced productivity, increased fatigue, financial strains, and safety concerns further compound the difficulties students face when navigating through congested roadways.
Objective:
To understand the underlying issues of the problem ‘Problem faced by the student Due To Traffic.’
Literature Review:
Solving Traffic Problems in the State of Kerala, India: Forecasting, Regression and Simulation Models.
Bollapragada, R., et al focused on road traffic accidents in South Delhi, highlighting that pedestrians, two-wheeler riders, and bus commuters were the most affected. It emphasized the need for tailored safety measures different from those in high-income countries, such as promoting helmet use to reduce head injuries in two-wheeler accidents. Regression analysis revealed a correlation between the number of vehicles per kilometer and accident rates, while simulation models suggested redesigning road networks to mitigate accidents. Recommendations included allowing fast vehicles to pass and expanding road infrastructure to accommodate the growing number of vehicles, aiming to address and alleviate traffic issues effectively.
Sensitivity analysis for a continuum traffic equilibrium problem.
Wong, S. C., et al presents a study on sensitivity analysis for a continuum traffic equilibrium problem in a city with competing facilities. It explores customer distribution, flow conservation principles, and performance metrics. The problem is addressed using a finite element method and sensitivity analysis, showing how changes in travel costs impact total cost and consumer surplus. The study highlights the importance of understanding traffic equilibrium for urban planning and transportation management, contributing to the broader literature on traffic flow modeling and equilibrium prediction
Data Collection:
For the above problem we framed 5 questions on Likert scale 1 to 5. Data was gathered from kbs students. 100 students were surveyed. From each students Mean, Standard deviation, standard error and T-stat was calculated.
Data analytics:
|
|
Q1 |
Q2 |
Q3 |
Q4 |
Q5 |
|
Mean |
3.10 |
3.24 |
3.52 |
3.36 |
3.83 |
|
STD Deviation |
1.38 |
1.36 |
1.29 |
1.43 |
1.24 |
|
STD Error |
0.14 |
0.14 |
0.13 |
0.14 |
0.12 |
|
T-stat |
-18.61 |
-18.87 |
-19.72 |
-17.59 |
-20.37 |
At 95% confidence level,
If T stat > 1.96, accept positively.
If T stat is between 1.96 and –1.96, accept neutrally.
If T stat < 1.96, accept negatively.
Conclusion:
- Students doesn’t encounter heavy traffic during the hours when college is in session.
- Students doesn’t encounter traffic due to construction work.
- Traffic congestion doesn’t often leave me feeling frustrated and impatient.
- Students are not often late for college.
- Students don’t usually spend around 30 minutes stuck in traffic.
References:
BOLLAPRAGADA, R. et al. Solving Traffic Problems in the State of Kerala, India: Forecasting, Regression and Simulation Models. Vikalpa: The Journal for Decision Makers, [s. l.], v. 41, n. 4, p. 325–343, 2016. DOI 10.1177/0256090916675532. https://research.ebsco.com/linkprocessor/plink?id=341b602b-82cf-35f7-bebd-48d88c091025
Wong, S. C., Sensitivity analysis for a continuum traffic equilibrium problem. Annals of Regional Science, [s. l.], v. 40, n. 3, p. 493–514, 2006. DOI 10.1007/s00168-006-0071-9. https://research.ebsco.com/linkprocessor/plink?id=ddfd79da-5983-3662-9485-9f4662fdb892