A User-Flocksourced Bus Intelligence System in Dhaka

the first

the world ----------

---

By Albert Ching MCP 2012 April 13, 2012

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

4 pm Traffic in Jakarta, August 2011

Mobile rickshaw wallah in India

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

QR Coded Patiala GreenCabs in Punjab, July 2011

Marketing 1

GO-Jek Dial-a-Motorcycle Transport in Jakarta, August 2011

Real-Time user services 2

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

Monitor, Evaluate, Iterate 3

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

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

Target Bus Lines, January 2012

13 km

20 km

100 onboard surveys

10 flock

members

team target

$800 120 one-way rides

resources

1 week

Week before Spring break 2012

Kb16

Kb10 Kb20 Kb7 Kb14

Kb13

Kb2

Kb8

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

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

Bus Survey

Marketing 1 Transport survey on the pedestrian bridge in Mirpur 1, Jan 2012

Bus Speed Map

http://web.mit.edu/mrching/Public/crowdsourcedbuslivedhaka.html

Real-Time User Services 2

Live Bus Location Map

Almost

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

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

Monitor, Evaluate, Iterate 3

March 2012 Dhaka Bus Update

Bus health Indicators

Rider Happiness

Current Ridership

crowding

marketing slowness

operator profitability

Future Ridership

Affordability of alternatives

1

2

Accessibility

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%)

1.3 hours Average one-way

commute time

Azimpur

Uttara

Banani

Dhanmondi

#27 Gazipur 2.5hours

Accessibility

Happiness

2.7

Happiness by bus company

#27 #36

BRTC 3.6

Suchona 2.8

2.3 VIP 2.3 2.5 Bikolpa

Safety

crowding 3.6

2.8

2.3

BRTC 52 seats per bus

Suchona 48 seats per bus

VIP 39 seats per bus

New Market

Uttara

Dhanmondi

Pallabi

http://web.mit.edu/mrching/Public/speeddhaka.html

Slowness

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

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

Mahalo!