The First User-FlockSourced Bus Intelligence System in the World
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A User-Flocksourced Bus Intelligence System in Dhaka
the first
the world ----------
---
By Albert Ching MCP 2012 April 13, 2012
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Collaborators Stephen Kennedy, MIT DUSP Muntasir Mamun, Kewkradong Tonmoy Saad Bin Hussain, Kewkradong Xitu Masuk Ahmed, Kewkradong Swapon, Kewkradong Chonchol Morshed Alam, Kewkradong Raian Md. Shakhawat Chowdhury, Kewkradong Mamun Bhai, Kewkradong Share My Bus Dhaka & Boston Volunteers Principal Advisors Chris Zegras, MIT Asst. Prof. of Urban Studies and Planning Zia Wadud, BUET Prof of Civil Engineering Paul Barter, NUS Asst. Prof. at LKY School of Public Policy Entrepreneurs Navdeep Asija, Fazilka Eco-Cabs Ravee Aahluwalia, Patiala Eco-Cabs Sundara Raman, Ideophone Anenth Guru, Ideophone Sandeep Bhaskar, Ideophone Sanjeev Garg, Delhi Cycles Atul Jain, Delhi Cycle HR Murali, Namma Cycle Anthony Tan, My Teksi Hooi Ling Tan, My Teksi Nadiem Makarim, GO-Jek Arup Chakti, NITS
Acknowledgements Leading Thinkers Apiwat Ratanwahara, Chulalongkorn University Sorawit Narupiti, Chulalongkorn University Charisma Chowdhury, BUET Moshahida Sultana, University of Dhaka Geetam Tewari, IIT-Delhi Anvita Arora, IIT-Delhi Rajinder Ravi, cycle rickshaw expert Tri Tjahjono, Univesiti Indonesia Jamillah Mohamad, University of Malaya Advocates Debra Efroymson, Work for a Better Bangladesh Maruf Rahman, Work for a Better Bangladesh Akshay Mani, EMBARQ Madhav Pai, EMBARQ Chhavi Dhingra, GTZ-India Eric Zusman, IGES Yoga Adiwinarto, ITDP Indonesia Restiti Sekartini, ITDP Indonesia Government Anisur Rahman, Dhaka Transport and Coordination Board Rajendar Kumar, Indian Dept of Information Technology Anil Sethi, Mayor of Fazilka Prodyut Dutt, ADB India Penny Lukito, BAPPENAS Indonesia Firdaus Ali, Jakarta Water Provision Industry RD Sharma, HI-BIRD Bicycles Comfort Cab Malaysia Jacob Yeoh, Yes! 4G Mobile Internet Malaysia Pornthip Konghun, Googlers Thailand James McClure, Google Singapore Kapil Goswami, Google India
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4 pm Traffic in Jakarta, August 2011
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Mobile rickshaw wallah in India
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Cheap data + promoting sustainable transport
Marketing 1 Real-Time User Services 2
Monitor, Evaluate, Iterate 3
Users
Cars = aspiration Information can improve
accessibility to, comfort and efficiency of shared vehicles
The rise of the first iterative city?
Bus Operators & Regulators
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QR Coded Patiala GreenCabs in Punjab, July 2011
Marketing 1
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GO-Jek Dial-a-Motorcycle Transport in Jakarta, August 2011
Real-Time user services 2
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Makes existing shared modes more efficient and on-demand
Safety / Payments
1! 2!1 2 3 4
SINGAPORE
DELHI/MUMBAI/ BANGALORE/
FAZILKA
DID NOT VISIT
KUALA LUMPUR
JAKARTA
BANGKOK
DHAKA
Bus Arrival
C Makes driving
a car easier
5 Private vehicle-sharing
Vehicle Security
Car Pooling
Mobile Productivity
Shared Transport Social Fun
Navigation
Congestion Tracking
Rail Arrival
On-Demand Auto Taxi
On-Demand Auto Taxi
On-Demand
Cycle Rickshaw
On-Demand
Auto Rickshaw
Bus Arrival
Bicycle Sharing
Car Sharing
Fare-Tracking / Safety Alerts
Fare-Tracking
Constellation of Experiments | August 2011
On-Demand Motor-cycle
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Monitor, Evaluate, Iterate 3
How Fucked is the T in Boston, April 2012
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Urban data collection techniques
Ubiquitous, Sensing
All the data, all the time Some data for lots of disparate times and places
Lots of data for a specific time and place
Sensors Crowds + Sensors Flocks + Sensors
Privacy Closed
Expensive Data processing
Only objective metrics
Gathering sufficient and relevant data
Organizing the flock Flock bias
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Urban data collection techniques
CrowdSourcing
All the data, all the time Some data for lots of disparate times and places
Lots of data for a specific time and place
Sensors Crowds + Sensors Flocks + Sensors
Privacy Expensive
Data processing Only objective metrics
Gathering sufficient and relevant data
Organizing the flock Flock bias
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Urban data collection techniques
FlockSourcing
All the data, all the time Some data for lots of disparate times and places
Lots of data for a specific time and place
Sensors Crowds + Sensors Flocks + Sensors
Privacy Cost
Data processing Only objective metrics
Gathering sufficient and relevant data
Organizing the flock Flock bias
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Mini bus on outskirts of Dhaka, January 2012
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Flock
Hardware
Software
Mobile data network
Cloud
Data processing
Visualization
Distribution
Cost
Free
$175 per phone
$10-15 per person per day
Free $4 per GB
Flocksourcing Workflow
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Target Bus Lines, January 2012
13 km
20 km
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100 onboard surveys
10 flock
members
team target
$800 120 one-way rides
resources
1 week
Week before Spring break 2012
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Kb16
Kb10 Kb20 Kb7 Kb14
Kb13
Kb2
Kb8
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100 onboard surveys
10 flock
members
team target
$800 270
----- 120 one-way rides
resources
1 week
----- 1,000
+10,000 passenger counts, bus
location points
*In Boston, a simultaneous crowdsourcing effort with the same apps has produced 3 surveys and less than 20 rides, most by me
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Cheap data + promoting sustainable transport
Marketing 1 Real-Time User Services 2
Monitor, Evaluate, Iterate 3
Cars = aspiration The rise of the first iterative city? Information can improve
accessibility to, comfort and efficiency of shared vehicles
Users Bus Operators & Regulators
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Bus Survey
Marketing 1 Transport survey on the pedestrian bridge in Mirpur 1, Jan 2012
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Bus Speed Map
http://web.mit.edu/mrching/Public/crowdsourcedbuslivedhaka.html
Real-Time User Services 2
Live Bus Location Map
Almost
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Bus Travel Times
#27
Azimpur
Uttara
20 km
1:25 Average
1:47
1:04
*Data based on 42 Rides in March 2012
Bad day 2:07
0:43 Good day
8 am 10 am 6 pm
1:50
Real-Time User Services 2 Almost
Weekend Weekday
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Real-Time User Services 2
Wait Time Live Bus Map Estimated Bus Wait Time* Live Wait Times Bus Delays Travel Time Bus Route Map* Estimated Bus Travel Times* Fastest Route Bus Speed Map* Comfort/Safety Live Crowd Data Estimated Crowd Data* Prepaid Seats Cashless Payments Accident Notification
--------
---------
*Potentially provided with flocksourced data
Almost
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Monitor, Evaluate, Iterate 3
March 2012 Dhaka Bus Update
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Bus health Indicators
Rider Happiness
Current Ridership
crowding
marketing slowness
operator profitability
Future Ridership
Affordability of alternatives
1
2
Accessibility
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Current Riders
Young, Male, Captive, Mobile, Hates Crowding
85% surveyed btwn 24-34 years
16% female (of those counted)
57% ride at least 5 times a week
100% with a mobile phone (18% with smartphone, 50% with internet-enabled multimedia phone)
Most common complaint about buses (23%)
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1.3 hours Average one-way
commute time
Azimpur
Uttara
Banani
Dhanmondi
#27 Gazipur 2.5hours
Accessibility
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Happiness
2.7
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Happiness by bus company
#27 #36
BRTC 3.6
Suchona 2.8
2.3 VIP 2.3 2.5 Bikolpa
Safety
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crowding 3.6
2.8
2.3
BRTC 52 seats per bus
Suchona 48 seats per bus
VIP 39 seats per bus
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New Market
Uttara
Dhanmondi
Pallabi
http://web.mit.edu/mrching/Public/speeddhaka.html
Slowness
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Rider Happiness Trends, Changes* Determinants* By Segment, Line, Company* Accessibility Home and Work Origin by Line* Commute Time* Equity Female Share of Riders* >50 Share of Riders
--------
--------- *Potentially provided with flocksourced data
Monitor, Evaluate, Iterate 3
Operator Performance Est. Ridership* Est. Profitability Est. Poor Performance Rate* City Performance Avg Road Speed* Est. Carbon Emissions per Capita
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An Iterative approach to cities
Masterplan Simulation 1 2 Iteration 3
Low-Cost Measurement Low-Cost Computing
1960s 2010-
Processors Computer hardware
Smartphone sensors Mobile data networks
Clouds Machine learning
Measuring results Calibrating and integrating models to reality
(1) Cost effective and appropriate data collection
(2) Data analysis, visualization, and
distribution
key
chal
lenge
s
Top-Down Top-Down Top-Down + Bottoms-Up
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Mahalo!