Theme 2 Automated data collection - a new foundation for analysis and management

AUTOMATIC DATA COLLECTION: A New Foundation for Analysis and Management

Nigel H.M. Wilson

Professor of Civil & Environmental Engineering

MIT

email: [email protected]

Nigel Wilson, BRT Workshop: Experiences and Challenges

September 2013 1

OUTLINE

• Automated Data Collection Systems (ADCS)

• Key Transit Agency/Operator Functions

• Impact of ADCS on Functions

• Traditional Relationships Between Functions

• State of Research/Knowledge

2 Nigel Wilson, BRT Workshop: Experiences and Challenges

September 2013

Automated Data Collection Systems

• Automatic Fare Collection Systems (AFC)

• increasingly based on contactless smart cards with unique ID

• provides entry (exit) information (spatially and temporally) for individual passengers

• traditionally not available in real-time

• Automatic Vehicle Location Systems (AVL)

• bus location based on GPS

• train tracking based on track circuit occupancy

• available in real time

• Automatic Passenger Counting Systems (APC)

• bus systems based on sensors in doors with channelized passenger movements

• passenger boarding (alighting) counts for stops/stations with fare barriers

• train weighing systems can be used to estimate number of passengers on board

• traditionally not available in real-time


September 2013

Manual

• low capital cost

• high marginal cost

• small sample sizes

• "hard and soft"

• unreliable

• limited spatially and temporally

• not available immediately

Automatic

• high capital cost

• low marginal cost

• large sample sizes

• "hard"

• errors and biases can be estimated and corrected

• ubiquitous

• available in real-time or quasi real-time

Transit Agencies are at a Critical Transition in Data Collection Technology

4


September 2013

ADCS - Potential

• Integrated ADCS database

• Models and software to support many agency decisions using ADCS database

• Monitoring and insight into normal operations, special events, unusual weather, etc.

• Large, long-time series disaggregate panel data for better understanding of customer experience and travel behavior


September 2013

ADCS - Reality

• Most ADCS systems are implemented independently

• Data collection is ancillary to primary function

• AVL - emergency notification, stop announcements

• AFC - fare collection and revenue protection

• Many problems to overcome:

• not easy to integrate data

• requires resources and expertise


September 2013

Key Transit Agency/Operator Functions

Off-Line Functions

• Service and Operations Planning (SOP)

• Network and route design

• Frequency setting and timetable development

• Vehicle and crew scheduling

• Performance Measurement (PM)

• Measures of operator performance against SOP

• Measures of service from customer viewpoint


September 2013

Key Transit Agency/Operator Functions

Real-Time Functions

• Service and Operations Control and Management (SOCM)

• Dealing with deviations from SOP, both minor and major

• Dealing with unexpected changes in demand

• Customer Information (CI)

• Information on routes, trip times, vehicle arrival times, etc.

• Both static (based on SOP) and dynamic (based on SOP and SOCM)


September 2013

Impact of ADCS on Functions

IMPACT ON Service Planning

• AVL: detailed characterization of route segment running times

• APC: detailed characterization of stop activity (boardings, alightings, and dwell time at each stop)

• AFC: detailed characterization of fare transactions for individuals over time, supports better characterization of traveler behavior

IMPACT ON Performance Monitoring

• AVL: supports on-time performance assessment

• AFC: supports passenger-oriented measures of travel time and reliability


September 2013

Impact of ADCS on Functions

IMPACT ON Management and Control

• AVL: identifies current position of all vehicles, deviations from SOP

IMPACT ON Customer Information

• AVL: supports dynamic CI

• AFC: permits characterization of normal trip-making at the individual level, supports active dynamic CI function


September 2013

Opportunities

• ADCS • monitoring status at various levels of resolution

• measuring reliability

• understanding customer behavior

• Data + Computing • simulation-based performance models

• Communications • real time information (demand)

• operations management (supply)

• Systematic approaches for planning, operations, real-time control


September 2013

Relationships Between Functions

• Real-time functions (SOCM and CI) based on

• SOP

• AVL data

• Reasonable as long as SOP is sound and deviations from it are not very large

• Fundamentally a static model in an increasingly dynamic world


September 2013

State of Research/Knowledge in SOCM

• Advances in train control systems help minimize impacts of routine events

• Major disruptions still handled in individual manner based on judgment and experience of the controller

• Little effective decision support for controllers

• Models are often deterministic formulations of highly stochastic systems

• Simplistic view of objectives and constraints in model formulation

• Substantial opportunities remain for better decision support


September 2013

Key Functions

Off-line Functions

Real-time Functions

Supply Demand

Customer

Information (CI)

Service

Management

(SOCM)

Service and Operations

Planning (SOP)

ADCS ADCS

Performance

Measurement (PM)

System Monitoring, Analysis, and Prediction


September 2013

Real-Time Functions

15

Vehicle Locations Loads

Monitoring

Information

- travel times

- paths

Dynamic

rescheduling Demand

CONTROL CENTER

Prediction

Estimation of current

conditions Supply

ADCS

Incidents/Events


September 2013

Theme 2 Automated data collection - a new foundation for analysis and management

Technology

nigel wilson

adcs systems

brt workshop

automatic data collection

management nigel

data collection technology

systems apc bus systems

panel data