GER Shitty paper

Congestion on MRT trains

The topic I have chosen for this essay is congestion on MRT trains in Singapore. Congestion can refer to clogging or overcrowding of trains, extending to train platforms as well. This usually happens during peak periods, such as on weekends or when most people are commuting to or from work. This also occurs at places where there tends to be large human traffic, such as in the Central Business District and areas where there is a high tourist population, such as near Vivocity and Chinatown. 

One of the causes of congestion on trains is related to Singapore’s population demographics in general. For instance, there has been a shrinking population of car owners in Singapore for the last 3 years (Tan, 2017). Concurrently, the number of MRT users has risen consistently, but more so since 2009 (Public Transport Utilisation - Average Daily Public Transport Ridership, 2018), indicating that the MRT structures built before then may not have been built to be equipped to handle today’s commuter levels. Another cause is that there have been frequent MRT breakdowns, and subsequent maintenance works that have been happening in the last few months, which have been greatly affecting commuter travel. Many of the maintenance works involve earlier closing times was well as later starting times for the trains (Changes to operating hours for rail renewal and maintenance works- August and September, 2018). This implies that fewer people will be able to enter the MRT at hours before and after peak period, which increases the chance of congestion on train platforms and carriages. 

With regards to the extent of impact, the people affected by congestion are first and foremost, the commuters who may not be able to get to school or work in time due to an inability to properly gauge the time needed to travel. Train companies such as SBS Transit will also be affected, as they may need to input more measures or manpower to cope with the influx of passengers at peak periods, such as around 7.45am (Tan, 2017). 

I am currently considering pursuing Psychology as a major, as I am in FASS. From the psychological perspective, there are many factors that can be explored. Using quantitative analysis, it would be possible to choose a random, representative sample of the commuter population to retrieve statistics on the daily, hourly commuter demographic for every MRT station. Qualitatively, they could also be surveyed on their ridership, asking questions such as why they choose to use the MRT at that particular time, and whether or not they would be willing to change their habits given specific government incentives or institutional changes. 

Some aspects of this problem could be addressed by computing. For example, we would need to distinguish the perceived problem from the right or real problem. A perceived problem could be that there are simply not enough trains to handle commuter levels at peak periods or crowded areas, so the no brainer solution is to buy more trains. However, this is costly and inefficient, as the number of train riders might steadily increase again, accounting for similar problems to the ones we face today. The real or right problem might be that we simply need to streamline the number of commuters so that they are more evenly spread out through the day and through the country, perhaps by increasing bus route efficiency. We can measure congestion computationally by looking for the number of passengers per hour and/or per station. This makes the term “congestion” in the problem formulation less subjective. A constraint might be that there must be enough space allocated not only to commuters but also those who have additional items such as bags or strollers. Optimization might involve minimizing the amount of empty space between commuters while maintaining a civil and appropriate distance between each commuter. So an example of a problem definition would be: given a list of commuters, find a ratio of trains to commuters, with a list of the appropriate train timings, commuters and train stations across Singapore such that there is enough space for commuters’ needs and empty space is maximized appropriately.

However, there might be some issues with solving this problem of congestion computationally as there are some non-computational factors. Commuters may not be willing to change their habits, and measures may include changing of government policy, which is outside the scope of computational thinking. As such, congestion on MRTs is only partially solvable using computational thinking. 

References

Changes to operating hours for rail renewal and maintenance works- August and September. (2018). Retrieved from https://www.lta.gov.sg/content/ltaweb/en/public-transport/changes-to-operating-hours-for-rail-renewal-works.html 

Tan, C. (2017). Private car numbers fall to eight-year low. Retrieved from https://www.straitstimes.com/singapore/transport/private-car-numbers-fall-to-eight-year-low

Tan, S. (2017). Cheaper MRT rides for pre-peak weekday travel. Retrieved from https://www.straitstimes.com/singapore/transport/cheaper-mrt-rides-for-pre-peak-weekday-travel

Public Transport Utilisation - Average Daily Public Transport Ridership. (2018). Retrieved from https://data.gov.sg/dataset/public-transport-utilisation-average-public-transport-ridership