the first
A User-Flocksourced Bus Intelligence System in Dhaka
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the world
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By Albert Ching MCP 2012 April 13, 2012
Acknowledgements 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
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
4 pm Traffic in Jakarta, August 2011
Mobile rickshaw wallah in India
Cheap data + promoting sustainable transport
Users
1
Marketing
Cars = aspiration
Bus Operators & Regulators
2
Real-Time User Services
Information can improve accessibility to, comfort and efficiency of shared vehicles
3
Monitor, Evaluate, Iterate
The rise of the first iterative city?
1
Marketing
QR Coded Patiala GreenCabs in Punjab, July 2011
2
Real-Time user services
GO-Jek Dial-a-Motorcycle Transport in Jakarta, August 2011
C
1!
Makes driving a car easier Navigation
1
2!
Private vehiclesharing
Makes existing shared modes more efficient and on-demand OnDemand Auto Taxi
Bus Arrival
2
3
Mobile Productivity
4
Shared Transport Social Fun
5
Safety / Payments
SINGAPORE Car Sharing DID NOT VISIT
KUALA LUMPUR Congestion Tracking Fare-Tracking OnOnDemand Demand Auto Taxi Motorcycle
BANGKOK Bus Arrival JAKARTA DELHI/MUMBAI/ BANGALORE/ FAZILKA
Rail Arrival
OnOnDemand Demand Cycle Auto Rickshaw Rickshaw
Car Pooling
Bicycle Sharing
Fare-Tracking / Safety Alerts
Vehicle Security
DHAKA
Constellation of Experiments | August 2011
3
Monitor, Evaluate, Iterate
How Fucked is the T in Boston, April 2012
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
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
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
Mini bus on outskirts of Dhaka, January 2012
Flocksourcing Workflow Cost Flock
$10-15 per person per day
Hardware
$175 per phone
Software
Mobile data network
Free
$4 per GB
Cloud Data processing Visualization Distribution
Free
20 km
13 km
Target Bus Lines, January 2012
resources
10
flock members
1 week
$800
team target
120
100
one-way rides
onboard surveys
Week before Spring break 2012
Kb16
Kb10
Kb2
Kb14
Kb20
Kb7
Kb8
Kb13
resources
10
flock members
1 week
$800
team target 1,000 270
120
100
one-way rides
onboard surveys
-----
-----
+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
Cheap data + promoting sustainable transport
Users
1
Marketing
Cars = aspiration
Bus Operators & Regulators
2
Real-Time User Services
Information can improve accessibility to, comfort and efficiency of shared vehicles
3
Monitor, Evaluate, Iterate
The rise of the first iterative city?
Bus Survey
1 Transport survey on the pedestrian bridge in Mirpur 1, Jan 2012
Marketing
Bus Speed Map Live Bus Location Map
2
Almost Real-Time User Services
http://web.mit.edu/mrching/Public/crowdsourcedbuslivedhaka.html
Bus Travel Times
Weekday 2:07
Bad day
#27
Weekend
Uttara
1:50
20 km
1:47
1:25
Average
1:04 0:43
8 am 10 am
Good day
*Data based on 42 Rides in March 2012
Azimpur
6 pm
2
Almost Real-Time User Services
Wait Time -------Live Bus Map - Bus Wait Time* Estimated 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
2
Almost Real-Time User Services
3
Monitor, Evaluate, Iterate
Dhaka Bus Update
March 2012
Bus health Indicators
Accessibility
2
Current Ridership
marketing slowness
1
Rider Happiness
Future Ridership
crowding Affordability of alternatives
operator profitability
Current Riders 100% with a mobile phone (18% with smartphone, 50% with internetenabled multimedia phone)
16% female (of those counted)
Young, Male, Captive, Mobile, Hates Crowding 85% surveyed btwn 24-34 years
57% ride at least 5 times a week
Most common complaint about buses (23%)
Gazipur
Accessibility
2.5hours
Uttara
Banani
Dhanmondi
1.3
hours
Average one-way commute time
Azimpur
#27
Happiness
2.7
Happiness by bus company #27
3.6
BRTC
2.8
Suchona
2.3
VIP
#36
2.5 2.3
Bikolpa Safety
crowding 3.6
BRTC
52 seats per bus
2.8
Suchona
48 seats per bus
2.3
VIP
39 seats per bus
Uttara
Slowness
Pallabi
Dhanmondi
http://web.mit.edu/mrching/Public/speeddhaka.html
New Market
Rider Happiness Trends, Changes* Determinants* -------By Segment, Line, Company*
Operator Performance
Accessibility Home and Work Origin by Line* Commute Time*
City Performance Avg Road Speed* Est. Carbon Emissions per Capita
Equity --------Female Share of Riders* >50 Share of Riders
Est. Ridership* Est. Profitability Est. Poor Performance Rate*
*Potentially provided with flocksourced data
3
Monitor, Evaluate, Iterate
An Iterative approach to cities
1
Masterplan
2
Simulation
key challenges
Low-Cost Computing
Measuring results
Top-Down
3
Iteration
Low-Cost Measurement
1960s
2010-
Processors Computer hardware
Smartphone sensors Mobile data networks Clouds Machine learning
Calibrating and integrating models to reality
(1) Cost effective and appropriate data collection (2) Data analysis, visualization, and distribution
Top-Down
Top-Down + Bottoms-Up
Mahalo!