As first appeared in TODAY: http://www.todayonline.com/commentary/
Public transport plays a pivotal role in the daily lives of Singaporeans. The vast majority of citizens depend on buses and the MRT to get them to work and home again, and to ensure they can move around the island efficiently and inexpensively throughout the day.
The government is faced with a constant dilemma—how to square the circle of a growing economy and population, citizen aspirations for car ownership, and extremely constrained land area. The policy answer, rightly, has been to expand and improve public transport, in ways that minimize land use and provide travellers with convenient, reliable, comfortable public transport options, available everywhere. The Ministry of Transport’s aim is for commuters to make use of public transport for 75% of morning peak hour journeys by 2030.
The challenge is in balancing supply against demand. Considerable growth in utilization and demand for the public transportation networks—fuelled by a growing economy and population, and the success of measures to reduce private transport—is happening right now. On the other hand, the completion of new MRT lines, both under construction and on the drawing board, is still some years in the future.
This situation is creating a social and economic problem today. Singaporeans are demanding better service, fewer breakdowns and ways to cope with the overcrowding during peak periods. The local authorities and service providers are struggling to optimize services, fleets, and manpower as well as manage contingencies.
The government has broadly shown itself to be tech-savvy, and open to the solutions to multiple issues offered by big data. The transport sector is no exception. In a speech at the Committee of Supply debate, Second Minister for Transport Ng Chee Meng said that big data and analytics will be used to improve train reliability as well as help public bus operators to track the location of their buses.
Ultimately, the objective is to integrate private transport data as well, leading to aggregated, comprehensive, and real-time data on road traffic.
Data analytics is clearly key to resolving Singapore’s transport woes; how can the science be applied?
A project at MIT’s Department of Urban Studies & Planning points the way. A number of papers published under this project show the need for every element of the public transport eco-system to be interconnected, to provide critical real-time data. Analysis of this data can serve to augment intelligence and manage anomalies in real-time.
Predictive maintenance, for example, can be scheduled to minimize vehicle breakdowns, the great bugbear of commuters. Data feeds on the areas and timings of regular traffic congestion can allow for the planning of more efficient bus routes as well as managing peak-period congestion at bus stops with more frequent services for popular routes.
This may sound esoteric but it is really not rocket science, and other countries are already using data analysis to help manage their public transport issues. What can we here in Singapore learn from best practices around the world that are alleviating these challenges for transport authorities, service providers, and consumers?
According to a report by McKinsey & Company, collection and strategic use of information can improve forecasting and help to nudge behavior in ways that improve the reliability of transport infrastructure and increase its efficiency and utilization.
The report cites as an example the fact that Israel has introduced a 13-mile fast lane on Highway 1 between Tel Aviv and Ben Gurion Airport. The lane uses a toll system that calculates fees based on traffic at the time of travel. To make it work, the system counts the cars on the road; it can also evaluate the space between cars to measure congestion. This is real-time pattern recognition of a very high order. The information is then put to use in a way that increases “throughput,” or the amount of traffic the road can bear. If traffic density is high, tolls are high; if there are few cars on the road, charges are cheap. This not only keeps toll revenues flowing, but also reduces congestion by “steering” demand.
Holland, too, is benefitting from the application of big data analysis. Dutch Railways is the principal passenger railway operator in the Netherlands, providing rail services on the Dutch main-rail network and international services to other European destinations. Running these vast networks gives Dutch Railways access to huge amounts of data, collected through intelligent train technology, ticketing systems, travel information, real-time monitoring, and services for maintenance and control unit staff.
Until now, train suppliers delivered all this IT, so each type of train had its own IT environment—making it difficult to work together and maintain each system. Dutch Railways had a vision to integrate all these information to deliver more reliable and better serves to customers. Using streaming analytics, in-memory computing, integration, and messaging software, Dutch Railways is now able to provide real-time information about train services and maintenance scheduling. Commuters are also able to use a travel planner application to ensure a seamless and prompt commute.
The clear conclusion is that digitizing infrastructure networks can improve forecasting, promote reliability, and increase efficiency.
So, what are the next steps?
The Singapore government has already taken the first step to open up and share the data being gathered on transportation with start-ups and entrepreneurs, allowing them to explore and use it for the kind of innovation that the private sector excels at. The sharing of transport data among all the stakeholders—transport operators, system providers, and citizens alike—will, in our opinion, speed up the development of practical solutions to reduce congestion, improve waiting times, and overcome commuter inconvenience. Embracing technology in this area will not only improve our daily lives, but serve as an important step in our journey toward actualizing the Singapore Smart Nation Vision.