Reader response draft 3

In the article “Preventing ‘Bus Bunching’ with Smart Phone Application Implementation”, Dave Sprogis (n.d.) used AnyLogic’s software simulator to prove his claim that limiting “Bus Bunching” would boost the experience of public bus transport commuters. Sprogis surveyed that the long waiting time at the bus stop could be eradicated and congestion could be reduced by improving minor setbacks to the bus before a cluster is formed. Sprogis proposed to install the SaaS system knowing that the Massachusetts Bay Transportation Authority (MBTA) had presented an API with real-time bus data that could be retrieved for scrutiny. Sprogis shaped an actual route using Geographic Information System software which allows him to replicate the situation with his ideal results he called “equilibrium”. Adopting this protocol, transport buses have to maintain distances between each other, as a result, the number of users is spread uniformly, reducing long waiting time and inundate of buses. Sprogis suggested that MBTA implement “uber-fication” of their buses using application software to advise drivers while imposing the protocol. This could further aid decision-makers in anticipating the issues and would improve the services for the commuters. I agree with Sprogis in the implementation of the SaaS system in the transport operation. Real-time data could be retrieved to assist bus drivers and operators in data analysis, headway calculations, and app developments for the commuter’s benefits.

Firstly, passenger count and headway analysis could be attained to assist bus operators with the help of different types of sensors such as GPS, APC, odometers, etc. in the bus operating system. According to Erath (2013), cities like London and Zurich have adopted an identical approach. Also illustrated by Wang (2018), systems like “AVL (Automatic Vehicle Location) and APC (Automatic Passenger Count)” have been utilized widely in bus operating systems. This could help establish the precision of the bus location even in tunnels or downtown areas. These units are on board buses that continue to record real-time data and feed it over to assist bus control operators in data analysis.

Secondly, bus drivers could also benefit from this system as proposed by Bartholdi (2011), with the use of AVL and GPS. With these two data, we could achieve mean headway and alteration among headways. With the help of these data it is possible to update and correct headways of buses departing from the control points. Bus drivers will also be alerted to accommodate their speed in real-time and relies on the estimation of commuter demand in order to achieve the target speed in which they called “self-equalizing”.

Lastly, commuters could benefit from this system by relying on real-time data updated on the bus application. According to Moreira-Matias (2016), a real-time data collection application using historical and real-time AVL data were proposed to predict and prevent bus bunching from occurring. The outputs predicted could be correctively adjusted by the system. This system has shown improvement and a “reduction of 68%” in the statistics of bus bunching incidents, as demonstrated by country like Portugal. As a result, has shown improvement in bus bunching and commuter’s experience.

In conclusion, the proposal made by Sprogis (n.d.) is feasible and with the advancement in technologies and resources. Drivers and bus control operators could benefit from data analysis. Also, data could be easily attained for the benefits of commuters in terms of mobile applications.

References

Bartholdi, J., Eisenstein, D. (2011). A self-coördinating bus route to resist bus bunching. Transportation Research Part B: Methodological, 46(4), 481-491. https://doi.org/10.1016/j.trb.2011.11.001

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

Moreira-Matias, L. (2016). An online learning approach to eliminate Bus Bunching in real-time. Applied soft computing, 47, 460-482. https://doi.org/10.1016/j.asoc.2016.06.031

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

Wang, P., Chen X., Chen W. (2018). Provision of Bus Real-Time Information: Turning Passengers from Being Contributors of Headway Irregularity to Controllers. Sage Journals. https://doi.org/10.1177/0361198118798722