A multi-objective transit trip itinerary planning system using gis for

bangalore city

By

Dr. Ashish VermaDr. Ashish VermaAssistant Professor (Dept. of Civil Engg.) and Assistant Professor (Dept. of Civil Engg.) and

Associate Faculty (CAssociate Faculty (CiiSTUP)STUP)Indian Institute of Science (IISc) Bangalore – 560012, Indian Institute of Science (IISc) Bangalore – 560012,

IndiaIndiaE-mail: E-mail: ashishv@civil.iisc.ernet.in

Presentation at

Geo-Infra 2012, Gurgaon9th Feb. 2012

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OVERVIEW

Introduction

Problem Definition

System Architecture and Design

Case Study

Conclusion

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People-oriented approach (proposed) Lo

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Hig

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NMT

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INTRODUCTION

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 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

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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PASSENGER INFORMATION SYSTEMS

Trip Planning System Assist in pre-trip planning through a stand-alone 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

Geographical Information Systems (GIS) are a powerful tool for visualization, planning, operations, analysis, and maintenance across many areas and functions.

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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Trip Planning System

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

Destination

Walking

Waiting

Travel

Travel

Transfer

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 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.

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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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

Develop a web-based Transit Passenger Information System, which takes into account:

Generalized Cost approach Multi-objective user queries

Time of arrival and departure Maximum number of modal transfers Maximum walking distanceAlong with one of the basic choices: Optimum path based on generalized cost Minimum time Minimum cost

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SYSTEM ARCHITECTURE AND DESIGN

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SYSTEM ARCHITECTURE AND DESIGN

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USER INTERFACE

Enter the Origin, Destination(s), Day and time of travel •Bus time table

•Metro time table

User Query

Itinerary planning General Information

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

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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Objective Function:

Min Z = w1twko,d + w2twt

o,d + (w3ttri,j.r + ci,j.r)xi,j + w4 ttt

i,jxi,j

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MATHEMATICAL FORMULATION

if arc is used, = {0} otherwise

1ijx MrAji r ,),(

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CASE STUDY AND IMPLEMENTATION City of Bangalore Public transport

BUS Metro

Bus – BMTC

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

A quick overview of BMTCEvery Day Traffic Revenue Rs. 3.75 Crores

No of Schedules 5901No of Vehicles 6140

Daily Service Kms 12.57 LakhsNo of trips 79001

No of buses under PPP 17Depots 37

Bus Stations 48Staff employed 32680

Daily Passengers Carried 4.5 million

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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

• 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 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

Mode IDDescription

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

10 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

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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: 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

An attempt was made to develop travel time model considering 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.

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Category Of buses Weighted averages of speeds in kmph

Big 10 22.48

Volvo 21.62

Normal 15.82

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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. 53

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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

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.

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

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Thank you

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