Reading Passage
Paragraph A
In 2008, the Metropolitan Traffic Analytics Centre (MTAC), located at 112 Mobility Avenue, Singapore, began investigating the use of big data to address chronic traffic congestion. At the time, average vehicle speeds during peak hours had fallen to 18 kilometres per hour in central districts. Early research between 2009 and 2011 focused on collecting data from GPS devices, traffic cameras, and electronic toll systems. Initial simulations suggested that real-time data analysis could reduce congestion delays by up to 22%, prompting authorities to invest in data-driven traffic control systems.
Paragraph B
Citywide implementation began in 2012, when MTAC integrated data from over 9,600 sensors installed at major intersections and expressways. These systems processed approximately 1.3 billion data points daily. By 2015, adaptive traffic signals reduced average commute times from 54 minutes to 41 minutes. The infrastructure upgrade cost SGD 410 million and was funded through national transport budgets approved in December 2011.
Paragraph C
Despite efficiency improvements, several challenges emerged. A 2014 internal review reported that data privacy concerns were raised by 36% of surveyed residents. Technical issues also occurred, including software incompatibility between older signal systems and new analytics platforms. Smaller municipalities lacked the expertise to manage complex datasets. In response, MTAC introduced stricter data governance policies in 2015 and established a central analytics training centre at Jurong East.
Paragraph D
Government commitment intensified after 2016, when Singapores Ministry of Transport allocated SGD 680 million to expand intelligent traffic systems nationwide. By 2019, 67% of urban roads were managed using real-time data analytics. National transport statistics showed that fuel consumption from idling vehicles declined by 14% between 2016 and 2020, reflecting improved traffic flow.
Paragraph E
Economic and environmental benefits followed. A 2021 study conducted by the National University of Singapore estimated annual savings of SGD 290 million due to reduced travel delays and fuel costs. Carbon emissions from urban traffic fell by 9% between 2017 and 2021. Businesses operating in logistics hubs also reported productivity gains as delivery times became more predictable.
Paragraph F
Future plans involve incorporating artificial intelligence into traffic management systems. MTAC aims to deploy predictive congestion modelling by 2032 to anticipate traffic surges up to 30 minutes in advance. As of January 2024, 53% of Singapores road network used advanced analytics platforms. Pilot projects scheduled for 2027 will test fully autonomous signal coordination across the central business district.
Questions 1-4: Matching Headings
Instructions: Choose the correct heading for each paragraph from the list below. Write the correct Roman numeral.
List of Headings
i. Financial and environmental impacts
ii. Early research into data-driven traffic solutions
iii. Privacy concerns and technical limitations
iv. Large-scale rollout supported by public funding
v. Operational improvements from system deployment
vi. Future integration of artificial intelligence
Question 1: Paragraph B
Question 2: Paragraph C
Question 3: Paragraph D
Question 4: Paragraph E
Questions 5-8: True/False/Not Given
Instructions: Write TRUE if the statement agrees with the information, FALSE if it contradicts, or NOT GIVEN if there is no information.
Question 5
Traffic data were collected exclusively from mobile phones.
Question 6
Average commuting times decreased after adaptive signals were introduced.
Question 7
Most residents opposed the use of traffic data analytics.
Question 8
Fuel consumption from stationary vehicles declined after 2016.
Questions 9-12: Table Completion
Instructions: Complete the table below. Write NO MORE THAN TWO WORDS AND/OR A NUMBER for each answer.
| Category | Measurement | Value |
|---|---|---|
| Sensor deployment | Intersections equipped | |
| Data processing | Daily data points | billion |
| Infrastructure cost | Total investment | SGD million |
| Coverage (2019) | Roads under management | percent |
Questions 13-16: Sentence Completion
Instructions: Complete the sentences below. Write NO MORE THAN TWO WORDS AND/OR A NUMBER for each answer.
Question 13
Initial simulations predicted congestion delays could fall by percent.
Question 14
Average commute times dropped to minutes by 2015.
Question 15
Data governance policies were introduced in .
Question 16
Carbon emissions declined by percent between 2017 and 2021.
Questions 17-19: Summary Completion
Instructions: Complete the summary below. Write NO MORE THAN TWO WORDS AND/OR A NUMBER for each answer.
Big data was deployed in urban traffic management to reduce congestion and improve journey times. Initial concerns about and data security were addressed through governance policies. System deployment led to reduced fuel from idling vehicles and improved traffic flow. Future developments will integrate predictive modelling to anticipate surges in advance.
Questions 9-13: Short Answer Questions
Instructions: Answer the questions below. Write NO MORE THAN THREE WORDS AND/OR A NUMBER for each answer.
Question 9
Where is the Metropolitan Traffic Analytics Centre located?
Question 10
How many sensors were installed citywide?
Question 11
Which university conducted the 2021 economic study?
Question 12
What percentage of roads used advanced analytics in 2024?
Question 13
In which year will autonomous signal coordination pilots begin?