OVERCROWDING ON RAILWAY STATION IN MUMBAI
AUTHORS:
SHRUTI BANSODE
GAURAV CHOPADE
NISHA KHARAT
INTRODUCTION:
Mumbai’s railway stations are always packed with people, making Stations really crowded. This means there are too many passengers trying to use the trains and platforms at the same time. It can be tough for everyone to move around safely, and sometimes trains get so full that people can’t even get on them. This overcrowding is a big problem that needs to be solved to make traveling easier and safer for everyone in Mumbai.
OBJECTIVE:
To understand the underlying issue of Overcrowding On Railway Station in Mumbai.
LITERATURE REVIEW:
- A real-time train routing and platforming problem in complex railway stations.
Bai, L. etal. (2021). this article discusses the real-time trains routing and platforming problem (RT-TRPP) in railway stations due to factors like unreliable freight train arrival times, flexible shunting operations, and dynamic station layouts caused by equipment failures. It proposes an Integer Linear Program (ILP) to minimize conflicting trains and ensure a feasible station timetable. The method is tested on a real-world complex station and can handle an overload of train activities efficiently, providing an optimal solution for 249 trains within 2 seconds, meeting the time-critical nature of RT-TRPP.
- Routing trains through railway stations: complexity issues.
Kroon, L.G. etal this article discusses the routing of trains through railway stations, which is a sub problem in the DONS project supervised by Railed and Netherlands Railways. It focuses on the computational complexity of
routing trains and shows that the problem is NP-complete when each train has three routing options but can be solved efficiently when each train has only two options. Additionally, it addresses related issues such as safety considerations and timetable constraints.
DATA COLLECTION:
For the above problem, 5 questions were framed to be answered on Likert Scale with 1 to 5 points. 100 students from Kohinoor Business School were surveyed and for each questions which was coded as 1 to 5, Mean, Standard Deviation, Standard Error and T-stat was calculated.
DATA ANALYSIS:
|
|
Q1 |
Q2 |
Q3 |
Q4 |
Q5 |
|
Mean |
3.16 |
3.66 |
2.68 |
3.78 |
4.3 |
|
Standard Deviation |
1.32 |
1.32 |
1.30 |
1.22 |
1.22 |
|
Standard Error |
0.13 |
0.13 |
0.13 |
0.12 |
0.12 |
|
t-stat |
1.22 |
5.00 |
-2.46 |
6.40 |
10.67 |
|
Result |
Neutral |
Positive |
Negative |
Positive |
Positive |
Q1. At 95% confidence level, t-stat is less than 1.96, are neutral.
Q2. At 95% confidence level, t-stat is more than 1.96, are positive.
Q3. At 95% confidence level, t-stat is less than 1.96, are negative.
Q4. At 95% confidence level, t-stat is more than 1.96, are positive.
Q5. At 95% confidence level, t-stat is more than 1.96, are positive.
CONCLUSION:
1- Students felt Neutral towards Intentional touches on Railway Station.
2- Students have to Stand in Long Queues for Railway Tickets.
3- Students Wallet/ Mobile was not Robbed.
4- Students Have Faced Ugly Fights and Arguments at Railway station.
5- Students skip trains because of crowd.
REFERENCE:
Bai, L. etal. (2021). A real-time train routing and platforming problem in complex railway stations. Journal of Intelligent & Fuzzy Systems, 1–9.
Kroon, L.G.etal. (1997). Routing trains through railway stations: complexity issues. European Journal of Operational Research, 98(3), 485–498.