| dc.description.abstract | Metropolitan area consists of huge population density, one or more urban areas, satellite cities,
rural areas and towns. It highly concentrates economic activities to attract people from rural areas
and is a complex spatial structures and reached a milestone in the development of road infrastructure
to support transportation systems. Due to increase in the number of vehicles, many traffic
related problems have arised, such as increase in delays, wastage of resources, high traffic accidents,
economic losses, environmental pollution, security, privacy, etc. These problems are solved
by using Intelligent Public Transportation System (IPTS), which consists of advanced technologies
for transportation engineering including information technology (IT), computational intelligence,
system control technology and system engineering. These advanced technologies play significant
role in reducing traffic congestion, traffic accidents, traffic pollution, energy consumption and improving
road traffic safety.
In this thesis, we have designed IPTS for public transport in a metropolitan area. It consists
of 5 major functional units, such as commuters’ arrival prediction, transport resource allocation,
privacy preservation, context-based service management and transport management. We have used
Emergent Intelligence (EI) technique with agents, as it is efficiently used, in several applications
for collecting, analyzing, monitoring, and sharing information. Also, it takes dynamic decisions to
give independence to each agent to take a decision. Some of these features are essential for public
transport system.
First, we have designed Commuters’ Arrival Prediction (CAP) scheme, which analyzes and
predicts commuters’ patterns in the bus station using commuters’ arrival density, resource availability,
history, and dynamic arrivals of commuters and vehicles. The proposed scheme provides
an accurate analysis and prediction of commuters’ arrival density pattern at each bus station in the
vicinity of transport depot. The predicted commuters’ density will be used to choose an optimal
route to reach the desired destination in a metropolitan area.
We have designed a Transport Resource Allocation (TRA) scheme using EI technique. The
proposed scheme efficiently manages and provides resource over space and time based on predicted
commuters’ arrival pattern, availability of resources, history, deficit resources and surplus
resources of neighborhood transport depots. The EI technique is used to collect, analyze and share
resources, reliability of resources, reliability of neighborhood depots, resource gathering time delay
reliability and travel time reliability. We have built an analytical model for TRA scheme using
discrete time Markov chain to analyse the system at steady state. The proposed scheme optimally
allocates reliable resources and provides reliable public transport services to the commuters.
In the metropolitan area, there will be privacy breach during communication among transport
depot’s staff and agents, which results in anomalies like impersonation, malicious activities
and greedy behavior and they lead to issues, such as traffic accidents, wastage of resources, delays,
etc. For this, we have designed Public Transport Depot Privacy Preservation Scheme (PTDPPS)
using EI technique in a metropolitan area. The proposed scheme consists of two phases: First,
policy based privacy preservation for depot staff and Second, pseudonymous authentication based
privacy preservation for communicating agents. The proposed scheme preserves privacy of resources,
vehicle dispatch, allocation, private and public information of transport depot staff during
communication inside and outside the transport depot.
In a metropolitan area, managing and providing suitable services are difficult or impossible
due to the non-linear and complex nature of transportation system. Thus, we have designed
Context based Public Transportation Service Management (CPTSM). The EI technique is used for
collecting, analyzing and sharing context information of vehicles, staff, commuters, routes, bus
station units and environmental. The collected and analyzed context information are used to develop
the policies to provide relevant services to commuters. The proposed system makes public
transportation system most reliable and efficient for the commuters.
We have designed an efficient public transportation management system in a metropolitan
area by combining CAP, TRA, PTDPPS, and CPTSM, and made as a single entity at a transport
depot in a metropolitan area. We have presented management of public transportation during
normal conditions and disaster situations in one of the zone in the vicinity of transport depot
using EI technique in a metropolitan area. During normal conditions, we have estimated and
predicted the commuters’ arrival pattern and their density, and also estimated and allocated the
resources at every bus stations. Using these information public transportation management is done
at every bus stations in the vicinity of transport depot. During the disaster situations, proposed
evacuation management system estimates boundary of disaster, evacuation exit points, victims
density, severity of victims and resources required. The evacuation management system assigns
fraction of victims to the desired destination through multiple evacuation exit points, and avoids
the occurrence of secondary disaster in the same disaster zone in the metropolitan area.
In summary, we have used EI technique with agents to design: 1) commuters’ arrival prediction,
which efficiently analyzes and predicts the commuters arrival density; 2) transport resource
allocation scheme, which dynamically allocates optimal resources; 3) privacy preservation
schemes, which preserves the privacy of transport depot staff and agents; 4) context based service
management, which efficiently makes use of context information of various transportation entities
to provide accurate services; and 5) transport management for evacuation of victims, which effectively
manages the disaster victims. We have simulated above mentioned schemes in different
scenarios with various performance parameters. The results obtained in simulation and analysis
show the importance of the approaches and effectiveness of the proposed system | en_US |
