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TRAFFIC MANAGEMENT 65 Real time information  P robably anyone reading this has been in this situation more times than they can count. e traffic on the motorway has already slowed to a crawl and the VMS sign ahead flashes: CONGESTION NEXT 20km. Brilliant! At this point you are committed to stay in the jam with the most viable alternate routes well behind you and the ones ahead now filling up as drivers bail out at the first opportunity, quickly tying up the secondary roads. You are on a modern, well-managed highway in a major city with a good current generation ITS infrastructure. e traffic management centre is fully aware of the situation. Roadside cameras and loop detectors in the system are all working perfectly generating a stream of images and probe data in real-time as they were designed and (procured at great expense) to do. So why didn’t all this technology prevent the traffic jam that you and about 30,000 others are sitting in right now or that the one that millions around the world experience on a daily basis? e simple answer is that real-time transport management, no matter how much data is available or how quickly and effectively it can be processed, simply isn’t good enough. For decision-makers from city managers to operations centre supervisors to individual drivers to have the means to avoid delays caused by any number of events, they must be able to anticipate, forecast and take action well ahead of what’s happening at that moment. MORE THAN AN EDUCATED GUESS is is exactly the situation that predictive analytics are designed to address – for virtually all transport modes whether highway, bus, ferry, rail, or any combination or sub-category thereof. As it has in other areas of both artificial intelligence and ‘big data’ management technology, IBM and other members of the global ICT David E Pickeral on when real time isn’t good enough Predictive text >>>
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Thinking Highways - Real Time 10-11

Apr 16, 2017

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Page 1: Thinking Highways -  Real Time 10-11

TRAFFIC MANAGEMENT

65

Real time information

 Probably anyone reading this

has been in this situation more

times than they can count.

"e tra#c on the motorway

has already slowed to a

crawl and the VMS sign ahead $ashes:

CONGESTION NEXT 20km.

Brilliant! At this point you are

committed to stay in the jam with the

most viable alternate routes well behind

you and the ones ahead now &lling up as

drivers bail out at the &rst opportunity,

quickly tying up the secondary roads.

You are on a modern, well-managed

highway in a major city with a good

current generation ITS infrastructure. "e

tra#c management centre is fully aware of

the situation. Roadside cameras and loop

detectors in the system are all working

perfectly generating a stream of images

and probe data in real-time as they were

designed and (procured at great expense)

to do. So why didn’t all this technology

prevent the tra#c jam that you and about

30,000 others are sitting in right now

or that the one that millions around the

world experience on a daily basis?

"e simple answer is that real-time

transport management, no matter how

much data is available or how quickly and

e*ectively it can be processed, simply isn’t

good enough.

For decision-makers from city managers

to operations centre supervisors to

individual drivers to have the means to

avoid delays caused by any number of

events, they must be able to anticipate,

forecast and take action well ahead of

what’s happening at that moment.

MORE THAN AN EDUCATED GUESS"is is exactly the situation that

predictive analytics are designed to

address – for virtually all transport

modes whether highway, bus, ferry, rail,

or any combination or sub-category

thereof. As it has in other areas of both

arti&cial intelligence and ‘big data’

management technology, IBM and

other members of the global ICT

David E Pickeral on when real time isn’t good enough

Predictive text

>>>

Page 2: Thinking Highways -  Real Time 10-11

66

TRAFFIC MANAGEMENT

66

community are developing predictive analytics as the essential

next step in ITS evolution.

Recognising the substantial investment in transport

monitoring technology to date, predictive analytics is about

enhancement not replacement. Enhanced assets such as

analytical tools, trackers, dashboards, ATMS and TIS become

an order of magnitude more e*ective by integrating multiple

sources of data – in far larger volumes than ever before possible

– to look ahead of real-time with a high degree of accuracy.

A SENSE OF HISTORYIBM’s Tra#c Prediction Tool (TPT), which has been piloted

in Singapore, is in the process of being selectively deployed

elsewhere around the world. "rough its synthesis of both

real time and historical data, TPT is able to provide extremely

accurate predictions about how and to what extent speci&c

incidents or events will a*ect all modes within the transport

ecosystem collectively and individually. As a result, all

stakeholders are empowered with accurate information

accompanied by actionable recommendations far earlier than

ever before possible. "is gives transport operators the ability

to mitigate or even eliminate problems in the transport system,

not merely react to them.

"e result is that predictive analytics, when used in concert

with advanced tra#c management, ensures the reliable

and unhindered $ow of goods and people through existing

Tra!c in Singapore which piloted IBM’s Tra!c Prediction Tool

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Page 3: Thinking Highways -  Real Time 10-11

67

Real time information

David Pickeral is Global Development Executive for Smarter Transportation at IBM, based in Washington, DC

[email protected]

www.linkedin.com/in/pickeral

Read more in our ARCHIVES at thinkinghighways.com/archives.aspx

fyi

transport channels without the need to expand physical

infrastructure or replace existing ITS systems. Additionally,

there are socio-economic and environmental bene&ts. In any

geography or economy, that translates to a win-win situation.

Today there are more than a billion cars worldwide and that

number will double by 2020. Tra#c increased 236 per cent

as the population grew 20 per cent between 1982 and 2001 in

the US. Clearly the situation demands a di*erent paradigm

so we can get more throughput out of existing road, rail,

runway and waterway infrastructure. By starting the process

of deploying analytical tools across all modes as budgets and

schedules allow, transportation planner will take positive

steps to ensure that as the years progress transport modes

of the world stay ahead of this growth both collectively and

individually, ensuring the $ow of goods and people as the

century progresses.