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Malang (ID) --:--Privacy PolicyTerms of Service

December 20, 20192 min read

Planning a Mikrolet Trip With a REST ServicePlanning a Mikrolet Trip With a REST Service

A prototype service generates paratransit trip plans for a city where route information is hard to find.

  • Journal
  • Publications

Written by

  • SRShirasaka RenIT & Infrastructure · Student Member

In this article

  1. 01How the planner works
  2. 02Where it strains

Malang has long been served by mikrolet, a form of paratransit that runs like a shared minibus on fixed routes. It was once a default way to get around the city. Ridership fell as newer, app based transport arrived, and one reason is unglamorous. Passengers often cannot find out which mikrolet goes where.

An angkot in Malang traffic. Image: Annidafattiya, CC0, via Wikimedia Commons.
Fig. 01An angkot in Malang traffic. Image: Annidafattiya, CC0, via Wikimedia Commons.

A study from Universitas Brawijaya describes a prototype that tries to close that information gap. It generates trip plans for mikrolet journeys and serves them through a REST web service, so any client, whether a phone or a web page, can request a route over standard HTTP.

01/02

How the planner works

The service follows a location-based style. A request carries a starting point and a destination, and the system returns candidate journeys through the mikrolet network. The search is built on depth-first search, chosen for a practical reason rather than a theoretical one.

  • Depth-first search is simple to modify, which matters while the routing rules are still being worked out.
  • The output is a web service, so it stays independent of any single app.
  • Each plan lists the sequence of routes a passenger would take.
A route unit parked at Mulyorejo terminal. Image: Mujiono Ma'ruf, CC BY-SA 4.0, via Wikimedia Commons.
Fig. 02A route unit parked at Mulyorejo terminal. Image: Mujiono Ma'ruf, CC BY-SA 4.0, via Wikimedia Commons.

Functional testing gave the team the result they wanted. The system produced all the trip plans expected from the test cases, with none missing.

02/02

Where it strains

Performance is the weak point, and the authors say so plainly. As the number of routes and possible plans grows, the system slows down. Depth-first search explores aggressively, and a denser network multiplies the paths it has to consider.

The paper presents the prototype as a working foundation rather than a finished product, and points to optimization as the next task. For a city trying to improve information about a legacy transport system, a prototype that generates correct plans is already a useful step.

Source

  1. Kharisma and Pinandito (2019). Prototype of REST Location-based Service for Trip Planning by Paratransit (Mikrolet) in Malang City. Journal of Information Technology and Computer Science.

    DOI10.25126/jitecs.201943131 (opens in a new tab)

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