Transcript Development of a Transit Passenger Information System using GIS

A multi-objective transit trip itinerary
planning system using gis for bangalore
city
By
Dr. Ashish Verma
Assistant Professor (Dept. of Civil Engg.) and
Associate Faculty (CiSTUP)
Indian Institute of Science (IISc) Bangalore – 560012,
India
E-mail: [email protected]
Presentation at
Geo-Infra 2012, Gurgaon
9th Feb. 2012
OVERVIEW
Introduction

Problem Definition

System Architecture and Design

Case Study

Conclusion
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Low Volume
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High Volume
NMT
High Priority




Low priority
People-oriented approach (proposed)
INTRODUCTION

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Public transport modes are considered as
efficient modes of transport because they carry
more number of passengers per unit of space
occupied.
Due to spatial and temporal variations in transit
services, roadway, traffic and weather conditions,
travelers within cities are not generally
conversant with the prevailing public transport
schedules, routes and traffic conditions.
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PASSENGER INFORMATION SYSTEMS

Passenger Information Systems aim at bridging
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the information gap by providing the pre-trip
and/or en-route information to the travelers
about their travel options, so that they can take
well informed travel decisions.
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PASSENGER INFORMATION
SYSTEMS

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Passenger Information System (PIS)
 Assist travelers by providing them timely,
accurate, reliable and relevant information
 Influence their travel behavior about mode
choice, time of travel, cost of travel, route
choice or trip making.
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Good Passenger Information System
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Good Passenger Information System
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PASSENGER INFORMATION
SYSTEMS

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Trip Planning System
 Assist in pre-trip planning through a standalone kiosk or a web-site.
 Assist in identifying the shortest path along
the public transport network, to perform a
trip from user’s origin to destination.
 Displays the complete graphical and textual
directions to perform the trip.
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GEOGRAPHICAL INFORMATION SYSTEMS

Because of the spatial nature of transportation
data, GIS is the perfect match. Using a base map
and layered, geographically coded data, GIS
provide a variety of spatial views and broad
query capability.
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
Geographical Information Systems (GIS) are a
powerful tool for visualization, planning,
operations, analysis, and maintenance across
many areas and functions.
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Trip Planning System
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Successful examples
 Multi-modal
transit system in Berlin,
Germany (Operator-BVG).
 Bay
Area Rapid Transit (BART), San
Francisco, USA.
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Components of a Trip
Origin
Travel
Waiting
Transfer
Travel
Walking
Destination
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Walking
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GENERALIZED COST AS A PARAMETER
An assumption that users are simply aiming to
minimize their money costs, when in fact they
attach great significance to time saving or vice
versa, may lead to errors in trip planning.
 For this reason, most of the urban transport
models use some form of GC (as a impedance
parameter) rather than simple "out of pocket"
money outlays.
 Hence, it is felt that this concept of GC can be
potentially adopted in Passenger Information
Systems also.
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GENERALIZED COST AS A PARAMETER


Also, many Indian cities follow experience or thumb rules more
than some scientific approach, to decide routes and schedules of
their public transport systems. This may lead to higher and
uncomfortable walking and waiting times for the user.
Besides all these, a major share of public transport users in India
are captive riders, for whom the fare paid for making a trip is also
an important criteria for choosing any transit route for trip
making.
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
This consideration is especially important in the Indian scenario,
where the various modes of transport are generally not
integrated, and the transfer time from one mode to another may
be very large.
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Complexities of Transit Network
Transit service is time dependant. The availability and the level of
transit service vary by time of day and day of week.
 For the same route, not every segment of the route has the same
amount of services all the time. Some stops lack service during
some times of the day and some days of the week. (peak/off-peak,
express/limited, weekday/weekend services). (Figure)
 Hence, integration of transit routes and temporal transit services
is necessary.

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Complexities of Transit Network
One bus stop may serve multiple routes, and more than one transit
route may share the same street links. Hence, trip planning system
requires a relational database linking bus stops, transit route, and
street network.
 Not every bus stop has a scheduled arrival and departure time
(time point). Hence, for trip planning the location of buses at
specific times has to be estimated.
 These unique features make the minimal path finding
application for transit networks much more challenging.
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PROBLEM DEFINITION
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Develop a web-based Transit Passenger
Information System, which takes into account:
Time of arrival and departure
 Maximum number of modal transfers
 Maximum walking distance
Along with one of the basic choices:
 Optimum path based on generalized cost
 Minimum time
 Minimum cost

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Generalized Cost approach
 Multi-objective user queries

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SYSTEM ARCHITECTURE AND
DESIGN
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SYSTEM ARCHITECTURE AND DESIGN
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USER INTERFACE
User
Query
Enter the Origin, Destination(s), Day and time of
travel
General
Information
•Bus time table
•Metro time table
Enter the maximum number of modal
transfer
User Query for trip based on
•Shortest distance
•optimum time
•optimum cost
•optimum generalized cost
Display of
Results
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Itinerary planning
Module for finding optimum path based on user
query
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NETWORK ANALYSIS
Steps followed:

All transit nodes that are within walking
distance of the user’s trip origin and destination
are found and flagged.
Travel time calculation:
In-vehicle time
 Walking time
 Waiting time
 Transfer time
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NETWORK ANALYSIS

Generalized Cost Calculation
Cost-per-unit-time’s for the four time segments are
calculated on the basis of the weightages input by the user.
 Algebraic sum of fare and monetary equivalents of the time
segments is assigned to each possible path.

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MATHEMATICAL FORMULATION
( i , j )  Ar , r  M is used,
= {0} otherwise
Objective Function:
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xij  
1 if arc
Min Z = w1twko,d + w2twto,d +  (w3ttri,j.r + ci,j.r)xi,j + w4 ttti,jxi,j
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CASE STUDY AND IMPLEMENTATION
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City of Bangalore
Public transport
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
BUS
Metro
Bus – BMTC
3.75 Crores
5901
6140
12.57 Lakhs
79001
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48
32680
4.5 million
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A quick overview of BMTC
Every Day Traffic Revenue Rs.
No of Schedules
No of Vehicles
Daily Service Kms
No of trips
No of buses under PPP
Depots
Bus Stations
Staff employed
Daily Passengers Carried
Metro – BMRCL


The first stretch between Baiyyappanahalli and M.G. Road was inaugurated on
October 20, 2011.
During the first month, since the opening of Reach I, about 13.25 lakh people have
taken ride on the metro. The BMRCL has earned a revenue of Rs 2.1 crore
(US$462,000) in its first month of operation
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CASE STUDY AND IMPLEMENTATION
The proposed system architecture for the Transit
PIS is implemented in a commercially available
GIS software TransCAD and its associated
programming language GISDK.
 The objective is to test the methodological
framework on the real city network of the study
area, Bangalore city.
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DATA REQUIREMENT
•
•
•
•
•
•
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Road network of Bangalore – digitized
Bus stops in Bangalore – digitized and field collection
Bus routes – digitized
Stage information for fare calculation – Form 4 BMTC /
Metro document
Schedule information for planning – Form 3 BMTC /
Metro document
Dwell time at bus stops – modeled
Travel time of buses for arrival time prediction –
modeled
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FIELD SURVEY

Road information
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Divided/undivided Carriageway, road width, shoulder width,
footpath width, road name, no. of lanes, one-way/two-way
Bus stops information

Latitude, longitude, name
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DIGITIZATION
Road digitization using Google maps and TransCAD
 Stops digitization based on field data
 Routes based on information from BMTC
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ROADS DIGITIZATION
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BUS STOPS DIGITIZATION
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ROUTES MAP
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DATA ENTRY TO BUILD DATABASE
Form 4 data (stages information)
 Form 3 data (schedule information)
 BMTC website for fare structure
 Road information (field data)
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Table: Transit/non-transit modes
Description
Mode ID
1
Metro
2
Walk access/egress/transfer
3
Vayu Vajra Airport service
4
Vajra
5
Big 10
6
Suvarna
7
Pushpak
8
Special services
9
Ordinary services
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Other services
Table: Snapshot of Mode table
Mode_Name
Mode_ID
Mode_used
Impedence_field
Fare_type
Fare_matrix
Metro
1
1
Metro_TT
2
Fare_Metro
Walk
2
1
Walk_TT
1
Vayu Vajra Airport service
3
1
BMTC_TT
1
Fare_BIAL
Vajra
4
1
BMTC_TT
1
Fare_Vajra
Big 10
5
1
BMTC_TT
1
Fare_Big_10
Suvarna
6
0
BMTC_TT
1
Fare_Suvarna
Pushpak
7
0
BMTC_TT
1
Fare_Pushpak
Special services
8
0
BMTC_TT
1
Fare_Special
Ordinary services
9
0
BMTC_TT
1
Fare_Ordinary
TRAVEL TIME MODELLING
Need to know the arrival time of the bus at each bus stop
 Due to the bus sharing space with other traffic, travel
time variability is greater
 Travel time depends upon: traffic flow, passenger
demand, intersections, frequency of stops, etc.
 Travel time = dwell time + link travel time

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DWELL TIME MODELLING
Definition:
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time the bus stops at a
loading area to serve the passengers
Factors affecting dwell time: passengers
alighting, passengers boarding, total
number of passengers, payment type.
Possible other factors: day of week,
time of day, type of route.
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TRAVEL TIME MODEL - MLR
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TRAVEL TIME MODELING
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An attempt was made to develop travel time
model considering

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


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distance between stops,
number of intersections between stops,
passengers boarding/alighting at stops,
dwell time at each stop,
total number of passengers on board,
type of bus,
time of day,
day of week.
1200 observations were considered
 The obtained model had a poor r square value of
0.007

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TRAVEL TIME MODELING

Since the obtained model was poor, in the current work
weighted averages of speeds were calculated for different
category of buses and the same were used in the model.
Big 10
Weighted averages of
speeds in kmph
22.48
Volvo
21.62
Normal
15.82
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Category Of buses
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Trip Planner - Walkthrough
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Trip Planner - Walkthrough
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Trip Planner - Walkthrough
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Trip Planner - Walkthrough
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Trip Planner - Walkthrough
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Trip Planner - Walkthrough
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WALK THROUGH
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CONCLUSIONS
Most of the approaches for transit PIS design direct cost / the in-vehicle travel time - optimum
path for making a trip.
 The GC based PIS design for trip itinerary
planning is suitable for the Indian scenario.
 In the present work, a unique PIS design suitable
for Indian conditions, for multimodal transit
system is proposed.
 The same has been applied on commercially
available GIS software TransCAD. It will answer
user queries taking into account a multi-objective
GC based approach.

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CONCLUSIONS
A system architecture is developed and proposed
to obtain optimum path, on a multimodal transit
network, based on GC.
 The developed model of transit PIS, is
demonstrated on a real world transit network of
Bangalore City, India.

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FUTURE SCOPE

If a continuous GPS data on arrival of buses is
used to obtain the real time data which in turn is
used in the travel time modeling then the
accuracy of the proposed system will enhance
Dr. Ashish Verma, IISc Bangalore

The travel time model developed was statistically
poor. A thorough research is required to analyze
the travel pattern in Bangalore and a good model
could be developed.
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Paper based on this work:
Kasturia S. and Verma A., (2010). “Multiobjective Transit Passenger
Information System Design Using GIS” Journal of Urban Planning and
Development, ASCE, Vol. 136, No. 1
Dr. Ashish Verma, IISc Bangalore
Thank you
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