Abstract: In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.
Abstract: There are various modes of transport in metro cities in India, auto-rickshaws being one of them. Auto-rickshaws provide connectivity to all the places in the city offering last mile connectivity. Among all the modes of transport the auto-rickshaw industry is the most unorganized and inefficient. Although unions exist in different cities they aren’t good enough to cope up with the upcoming advancements in the field of technology. An introduction of simple technology in this field may do wonders and help increase the revenues. This paper aims to organize this segment under a single umbrella using GPS devices and mobile phones. The paper includes surveys of about 300 auto-rickshaw drivers and 1000 plus commuters across 6 metro cities in India. Carrying out research and analysis provides a base for the development of this model and implementation of this innovative technique, which is discussed in this paper in detail with ample emphasis given on the implementation of this model.
Abstract: The purpose of this research is to develop and apply the
RSCMAC to enhance the dynamic accuracy of Global Positioning
System (GPS). GPS devices provide services of accurate positioning,
speed detection and highly precise time standard for over 98% area on
the earth. The overall operation of Global Positioning System includes
24 GPS satellites in space; signal transmission that includes 2
frequency carrier waves (Link 1 and Link 2) and 2 sets random
telegraphic codes (C/A code and P code), on-earth monitoring stations
or client GPS receivers. Only 4 satellites utilization, the client position
and its elevation can be detected rapidly. The more receivable
satellites, the more accurate position can be decoded. Currently, the
standard positioning accuracy of the simplified GPS receiver is greatly
increased, but due to affected by the error of satellite clock, the
troposphere delay and the ionosphere delay, current measurement
accuracy is in the level of 5~15m. In increasing the dynamic GPS
positioning accuracy, most researchers mainly use inertial navigation
system (INS) and installation of other sensors or maps for the
assistance. This research utilizes the RSCMAC advantages of fast
learning, learning convergence assurance, solving capability of
time-related dynamic system problems with the static positioning
calibration structure to improve and increase the GPS dynamic
accuracy. The increasing of GPS dynamic positioning accuracy can be
achieved by using RSCMAC system with GPS receivers collecting
dynamic error data for the error prediction and follows by using the
predicted error to correct the GPS dynamic positioning data. The
ultimate purpose of this research is to improve the dynamic positioning
error of cheap GPS receivers and the economic benefits will be
enhanced while the accuracy is increased.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.