Friday, May 18, 2018

PUBLIC TRANSPORTATION OPTIMIZATION IN BUDANILAKANTHA TO GODAVARI VIA INTRODUCTION OF BUS RAPID TRANSIT (BRT)

As final year project we are conducting the research on feasibility of transits and eventually optimizing public transport.With constant guidance of Er. Hmenat tiwari we are heading towards some positive outcome .The following members are involved in project . 

                                                                  Group members:
                                                                  Sandip Acharya
                                                                  Sagar Upreti
                                                                  Anand Marasini
                                                                  Sandeep Jha
                                                                   Suyog Kattel


we are very thankful for  Guidance and co-ordination from Er Hemant Tiwari during the entire project time.Without his supervision the projrct wouldnot have been effective and successful.


                                                                 Er. Hemant Tiwari  (  supervisor  )

                                                             

He also helped us in manpower managment during phase II (volume  studies and  delay survey) . Also various tools and guidelines during whole project.

                                               

                                         Article written by:  Er. SandipAcharya




BACKGROUND

The problem of optimizing the public transport paths of large networks is a complicated issue that cannot be solved by the ordinary optimization methods in mathematics. Various problems in solving public transport optimization include non-linearity, state of being non-convex, multi-target function, and the like one innovative method for solving the optimization problem of public transport paths was presented by Mandl (1979), comprising two steps:

In the first step, a primary possible network is created, and in the second step, a target function in the form of the total time of travelers, including on-means time and waiting time, is minimized. This algorithm does not consider the travel demand in the network construction stage. In Mandl’s algorithm, the emphasis is on the network’s coverage and direct paths (Mandl 1979). Throughout following years, other methods were proposed for solving these problems, such as localizing a path from the rapid transit system with population coverage insight considering interstation distances and source-destination demand.







FEASIBILITY OF BRT

Like many other cities in developing countries Kathmandu is struggling with the problem of how to upgrade and improve existing transit services at a low cost. The ever-increasing chaos and congestion, high rate of accidents and rapidly deteriorating transport operational, management and environmental condition calls for immediate considerations of an alternative transport option that could reduce the transport problem. In the way of searching a fruitful solution to the transport problem, various options are available. The experience of other developing countries (like Columbia, Jakarta) shows that implementation of a bus rapid transit option may come out successful. But, it is still questionable whether the modern space efficient mass transit system particularly introduce of BRT is feasible or not for the present road network system viz. quantity, quality, orientation, functionality as well as land use and transport network structure of this city. This study presents the prevailing transport and traveling scenario and the characteristics of existing mass transit system in Kathmandu Metropolitan city. Particular emphasis has been made to assess the feasibility of BRT options as compared to the physical and infrastructural capacity of the road network of Kathmandu city. Finally, a set of recommendations have been proposed to improve the physical, infrastructural and operational condition of the transportation system aims at introducing modern mass rapid transit system in Kathmandu Metropolitan City to meet the future enormous demand.

The quality of life and economic vitality of the Municipality of Kathmandu are seriously threatened by the rapid growth in polluting two-wheelers, cars, and auto tempos, which have been growing at 10% per annum. Kathmandu’s air pollution level is much higher than the recommended World Health Organization standard for suspended particulate matter, resulting in thousands of pre-mature deaths each year. Traffic flow is nearing capacity, so that any minor incident can bring traffic to a standstill for extended periods of time. The rapid growth in the private vehicle fleet means that if nothing is done, Kathmandu’s traffic condition will deteriorate further and result in severe congestion. Even if congestion causes only 5 minutes of additional travel time per trip in Kathmandu, this means Rs.150 crore per year lost to congestion. Worldwide, cities that have not developed an effective mass transit system have been unable to reduce congestion despite massive expenditures on new infrastructure.



fig:transit system for BRT

LIGHT RAIL TRANSIT:LRT


As the project objective we can also propose rail transit in this route. Being young on rail transits Nepal must focus on light rail concept as light rail is the most right option for the rail transit along Kathmandu. Designwise we can prefer monorail because of its shape and size but practically we have to adopt metro system being beginners in this field 
A monorail system has a slim and light body structure, and so the authority could argue that it would be more feasible for Kathmandu’s narrow roads. However, it is necessary to understand that the capacity of a monorail system is very limited, catering to only 3,000 to 4,000 passengers per direction per hour. For Kathmandu, a densely populated and rapidly growing city, a metro rail system should be provided instead.






fig:station for rail transits

government is massively conductiong the research in this sector on last three years .various studies are on going to build rail system inside kathmandu and outside valley.

govermnment proposed route

BRT over LRT:

Problem with metro-rail is that the distance between stations must be generous: at least 1.5  kilometers or more, in order to maintain higher travel speeds. This might not be possible in a densely aggregated city like Kathmandu where key junctions or possible metro stations are very close; this would materially increase the construction cost since more stations would incur greater cost. With BRT, keeping stations close, even only a few hundred meters apart would be financially feasible. 

SELECTED ROUTE:

Godavati to patan
Patan to Ratnapark
Ratnapark to Budanilkantha










OBJECTIVE OF RESEARCH
  • To detect and overcome the complexity in public transport planning
As we proceed in this project, we encounter many conflicting demands which we need to balance. The public transportation services are expected to be safe, reliable and affordable. Our plan must be efficient and profitable in real scenario. Thus, it is crucial to scrutinize the plan and look for problems to overcome through this research.

  • To handle real-time disturbances with ease

Every route in which a vehicle needs to travel to reach its destination have a certain probability of facing problem like crashes, traffic jam or any other disturbances. Our main objective is to suggest the protocol on the basis of our research to handle such disturbances and provide a smooth movement with ease.

  • To maximize the demand to be served by the bus service

  • To minimize operating cost

Transit planning models adopt this because the real operator cost depends on each particular case. For example, there can be subsidies and revenues based on the tickets effectively sold. Moreover, because our model is not conceived for operational planning, changes of buses among different lines are not considered; that characteristic is usually taken into account in vehicle scheduling models. Our proxy for operators cost is the number of buses required to travel simultaneously in the network.

  • To minimize the total travel time

Its value is computed by the assignment sub-model once the frequencies are determined. Note that frequencies by themselves impact directly over the user waiting time. But because passengers consider all the travel time components to decide the lines to board, a change in the line frequencies also impacts over the whole travel time of each passenger.



The following measuremnts are followed and to be followed while conducting survey of public transport otimizaton.




THE AVAILABILITY AND USABILITY OF MEASUREMENTS AND SERVICES

Planning (acquisition of source data)

•      Traffic surveys

o    Automatic traffic counts

o    Intersection counts

o    Non-motorised traffic counts

o    Traffic functionality audits

o    Destination surveys



•         Road profile measurements

•         Inventory of surfacing damage

•         Noise measurements

Construction

•         Roadside technology construction and maintenance

•         Surfacings sawing services

Surfacing
•         Road profile measurements (quality and condition measurements)
•         Surfacings sawing services
Maintenance
•         Inventory of equipment and machinery
•         Inventories of road signs
•         Inventories of lighting
•         Winter maintenance quality measurements
•         Gravel road inventories
•         Digital photography of the road network

PHASE II : data collection and analysis

data collection

Data collection is categorized in two phases :phase I and phase II. In phase I we got engagged in volume count of the vehicles in the proposed route. we also got assistance from our supervisor Er.Hemant tiwari with extra members for this phase.

phase I data colletion team ( station: lagankhel)

In phase II we collect massive amount of data about delays and capacity .moreover we were focused in journey characteristic study like travel time , delay time,occupancy,journey speed and so on.
More than 60 days we were involved in data collection and field visit during project span. All the resources used were somewhat limited but we tried to get maximun benifit from the source available.
phase II data collection ( station : Gangalal,Maharanjung )


Data Processing and Analysis

Background

All the members were engagged during the analysis of the project. we use wide amount of books,notes and reference during the project.the result obtained are too fruitful for our entire nation to optmize and enforce the intelligent techniques for maximizing outputs.
we also intend to check the feasibility of LRT (light rail transit), ropeway transit,bus rapid transit.

   Alignment and stops of mass rapid transit is the prerequisite for developing an integrated mass rapid transit system. Then mass rapid transit system such as Metro and BRT are integrated on operational, physical and institutional level.
    Least generalized cost concept has been applied using stochastic user equilibrium  approach to select the user oriented BRT corridor. In the backdrop of need of mass rapid transit for major cities and making BRT a viable mass rapid transit mode in terms of ridership and accessibility, integrated BRT approach has been proposed widely all over the world.
   In the light of above studies and to make BRT planning more realistic in terms of transit users behavior and transit demand,my project and research presents GIS based methodology ,integrated approach and combined approach to select the user oriented corridor for horizon year based on stochastic user equilibrium approach.


ANALYSIS:

Primary data collection refers to the field traffic studies and surveys conducted for collecting detailed information of the city transportation system including household interview survey, origin and destination survey, bus passenger survey, bus passengers boarding-alighting survey, classified volume count and vehicle occupancy, speed and delay study, road network inventories and stated preference survey. Whereas secondary data including population, employment, vehicle registration, city bus network and passenger details, emission data, city master plan, municipal ward maps were collected from Government and non Government agencies involved in urban planning.



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