Book Review by Dr. Ong Kian Ming, Member of Parliament for Serdang and Assistant National Director for Political Education for the DAP, on the 18th of March 2018
Most of my colleagues in the DAP who were elected into office for the first time in the 2008 and 2013 general elections did not grow up thinking that they would be state assembly representatives or Members of Parliament. None of my friends grew up thinking that they wanted to be the next Prime Minister of Malaysia. But since the tsunami elections of 2008, many more people in the younger generation can imagine themselves being elected representatives. More of them are interning and working for elected officials both in the Barisan Nasional as well as Pakatan Harapan. Public policy is being discussed and debated more rigorously among students via events such as the Model United Nations and public policy competitions such as the Malaysian Public Policy Competition (MPPC).
RECENT announcements heralding Alibaba’s move to roll out its City Brain Artificial Intelligence (AI)-driven smart city solution in Kuala Lumpur (the first city outside China to implement this system) had me initially excited, for two reasons.
Firstly, I hope that the system would help alleviate some of the horrendous traffic jams at critical junctions in downtown KL. Secondly, that this initiative would spur further initiatives using AI and other ‘smart’ systems to tackle transportation issues in the Klang Valley.
But, as with most policy matters, the devil lies in the details. No matter how ‘smart’ a system is, it cannot solve traffic problems caused by human driving patterns and infrastructure bottlenecks. And sometimes, overly ‘smart’ systems may not be as useful as other simpler, non-AI driven information provision systems.
For example, one of City Brain’s earliest initiatives aimed to analyse livestream data from 500 of DBKL’s CCTV cameras and integrate the information with 300 of DBKL’s traffic lights. Presumably, this data would be used to optimise traffic light changes in order to improve traffic flow. But this kind of optimisation will do little to solve the massive congestion that occurs at major traffic intersections during rush hour, when drivers tend to routinely ignore traffic signals, creating ‘bottlenecks’ in traffic.
Information is power, and sometimes, keeping it simpler may be more effective. Instead of centralising traffic flow information at the top to drive data analytics, a better alternative is to cascade the data down to consumers and empower them to use that information to optimise their own travel schedules.
If RAPID KL were to create an app providing real time information on the RAPID bus, LRT and MRT services, this would give public transport users the ability to anticipate bus and train delays, and to adjust their journey schedules accordingly. This kind of app may not sound as sexy as the City Brain initiative, but the likelihood of having a greater impact on time savings is much higher.
RAPID KL already collects real time data for its buses as well as the LRT and MRT trains. The former information is probably of more value to public transport users. Waiting times for the LRT and MRT are much shorter and are already displayed at the LRT and MRT stations, but with the exception of a few public bus stops that have electronic displays, there is typically no information on when the next bus will be arriving at most other bus stops.
We know that real time data for the location of each RAPID KL bus exists. I’ve visited the state of the art control room of the RAPID KL bus depot in Balakong, where the exact location of each bus on the road was shown on a gigantic screen. At some larger bus stops, such as the one at the Bangsar LRT station, RAPID KL also provides real time data for bus arrivals.
The Malaysian Administration Modernisation and Management Planning Unit, better known as MAMPU, is one of the key government agencies which is pushing for greater data sharing, open data and data transparency. To MAMPU’s credit, it has been encouraging various government agencies and ministries to share their data via its open data website (data.gov.my). Last May, an open data day event held on the premises of the University of Malaya, saw PRASARANA sharing RAPID KL’s real time data for Bus No.789 (the bus’s route crosses into the university).
The real time data for Bus No.789 was then shared on an app created by WRZIT Sdn Bhd (according to the company’s Facebook post).
MAMPU then published the GPS location mapping information of Bus No.789’s route on its website. The map of the bus route as indicated by the GPS locations is shown below together with the regular Bus No.789 route.
Blue line: The bus route for T789 (Bukit Angkasa – Universiti Malaya);
Green line: Bus stops along the T789 bus route;
Red line: Location of bus from MAMPU bus tracking data
*Map prepared by Penang Institute intern, Atticus Seong.
Instead of relying on a private company to show real-time data for RAPID KL buses, wouldn’t it be better for RAPID KL to create its own app to provide this information to the user for ALL its buses?
The Petaling Jaya Municipal Council (MBPJ), for example, has an easy to use PJ City Bus app which shows the real-time location of all of its free buses that are currently on the road.
The Selangor state government has also launched a real-time bus tracking app called the Selangor Intelligent Transport System (SITS). This app tracks the real time location of all the Selangorku buses plying the free bus routes in Shah Alam, Petaling Jaya, Subang Jaya, Ampang Jaya, Klang, Kajang, Selayang, Sepang, Hulu Selangor, Kuala Langat, Sabak Bernam and Kuala Selangor. It shows the plate number of the bus, the bus stops along the route and notifies the user on the estimated arrival time (including possible delays).
To sum up, before getting overly excited about brand new innovations in the marketplace, we might be better off investing in less “sexy” (yet more practical) efforts to make both public and private transportation in Malaysia ‘smarter’, more efficient and more user-friendly.