A Summary Reader Response

In the case study, “Preventing ‘Bus Bunching’ with Smart Phone Application Implementation,” Sprogis (n.d.) addressed the problem of ‘bus bunching’ in Watertown, MA (US), through the use of a smartphone application. In the article, the author inferred that public buses lost substantial productivity when they bunched together. To tackle the issue, Sprogis utilized AnyLogic's Geographic Information System (GIS) alongside data published by the Massachusetts Bay Transportation Authority (MBTA) to run various simulations for possible solutions. He discovered that the solution named “equilibrium policy” showed the best results. The equilibrium policy emphasizes that busses keep a constant distance between themselves. Sprogis further stated that the equilibrium policy caused the wait time to be of a “more predictable distribution,” which removed unnecessarily long buffer times and “[dampened] overcrowding of buses.” He later proposed the MBTA to implement “’uber-fication’ of buses” via a phone application. The application would “[advise] drivers when to wait based on network metrics” to impose the equilibrium policy. In my opinion, while the implementation of the equilibrium policy via a phone application would bring about positive results, the author did not mention other methods used to tackle the problem of bus bunching.

 

There are a few other ways proposed to handle the bus bunching problem. One such example would be in Erath’s (2013) proposal to Singapore’s Land Transport Authority (LTA) to shorten long bus routes in half. Akin to Sprogis’s proposal, LTA utilizes onboard displays to remind drivers of their bus schedule, ensuring that they arrive at their stops on time. LTA also provided commuters with a phone application to allow commuters to plan their commutes better. Erath reported that based on simulations ran by Future Cities Laboratory, Singapore, the dependability of busses could theoretically increase by 35 percent when they shorten long bus routes in half. This has a higher chance of decreasing bus bunching because shorter routes require fewer bus stops, and busses will also be proportionately utilized. Erath further stated that cutting bus routes could show to be “efficient in improving service quality and in increasing commuter satisfaction.” I prefer Erath’s approach towards bus bunching over Sprogis’s proposal as the former’s proposal does not require the drivers to divide their attention. Drivers need to give their utmost attention to driving to ensure the safety of the passengers.

 

Similar to Sprogis’s equilibrium system, there also other proposed systems that calculate headways between busses. In a news article, Jaffe (2012) reported that John Bartholdi III and Donald Eisenstein proposed and live-tested a similar operating system. Their “self-equalizing system” calculates departure times from control points based on traffic conditions and route distances. Bus drivers would drive without being mindful of a schedule and stop at control points to allow the “self-equalizing equation” to calculate the bus’s next departure time, which resulted in better distributions of headways between busses. Similar to the equilibrium policy, the self-equalizing system reacts to live traffic conditions. However, unlike Sprogis’s proposal, the self-equalizing system does not require a fixed schedule. Jaffe inferred that commuters would find this system more reliable than fixed schedules and that it “simplifies the job of the drivers, who can focus purely on flowing with the traffic.” In my opinion, Jaffe’s proposal works better than Sporgis’s approach as the former does not require drivers to divide their attention while driving. 

 

In conclusion, though I agree that Sprogis’s approach to deal with bus bunching is useful, I argue that the other methods could potentially bring about the same (or even greater) results. The main reason Sprogis’s proposal is not as desirable compared to the other methods is that it takes away too much of the driver’s attention. Bus drivers have to be as vigilant as they possibly can be while driving, to maintain the safety of the passengers.

 

References

Sprogis, D. (n.d.). Preventing ‘Bus Bunching’ with Smart Phone Application Implementation. AnyLogic. https://www.anylogic.com/preventing-bus-bunching-with-smart-phone-application-implementation/

Erath, A. (2013, March 24). How to solve the problem of bus bunching. The Straits Times. https://www.straitstimes.com/singapore/how-to-solve-the-problem-of-bus-bunching

Jaffe, E. (2012, March 12). How to keep buses from bunching. Bloomberg CityLab. https://www.bloomberg.com/news/articles/2012-03-12/how-to-keep-buses-from-bunching

 

(Revised 2 December 2020)