ADDIS ABABA UNIVERSITY
SCHOOL OF MECHANICAL AND INDUSTRIAL ENGINEERING
INDUSTRIAL ENGINEERING CHAIR
POST GRADUATE PROGRAM THESIS
BY: DOBOSHA ABBELTI
ID No: GSR/7437/09
Capacity analysis and optimization of public passenger road transportation service delay in Addis Ababa city
Advisor: Dr. Ing. Eshete B.
Co-advisor Mr. Fitsum G.
Capacity analysis and optimization of public passenger road transport service delay in Addis Ababa city.
A thesis submitted to
The School of Mechanical and Industrial Engineering
Presented in Partial Fulfilment of the Requirements for the Degree of Masters of Science (Industrial Engineering)
Addis Ababa University
Addis Ababa, Ethiopia
Addis Ababa University
School of Graduates Studies
This is to certify that the thesis prepared by dobosha abbelti, entitled: capacity analysis and optimization of passenger transportation service delay in Addis Ababa city and submitted in partial fulfilment of the requirements for the Degree of Masters of Science (Industrial Engineering) complies with the regulations of the University and meets the accepted standards with respect to originality and quality.
Signed by the Examining Committee:
M ______________ ______________
Internal Examiner Signature Date
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External Examiner Signature Date
Dr. Ing Eshete Birhan ______________ ______________
Advisor Signature Date
Mr. Fitsum Getachew ______________ ______________
Co-Advisor Signature Date
M ______________ ______________
School Dean Signature Date
I hereby declare that the work which is being presented in this thesis entitle “Capacity analysis and optimization of passenger transportation service delay in Addis Ababa city” is original work of my own, has not been presented for a degree of any other University and all the resources of materials used for the thesis have been duly acknowledged.
This is to certify that the above declaration made by the candidate is correct to best of my knowledge
Dr. Ing Eshete Birhan ____________ ______________
Advisor Signature Date
Mr. Fitsum Getachew ______________ ______________
Co-Advisor Signature Date
List of Figures
List of Table
BACKGROUND AND JUSTIFICATION OF THE STUDY
Peoples move from one place to another area for different activities. They may move for education, business, office work, daily work, relative visit, tours, medical treatment and etc. Some of these passengers prefers their own foot while others select animals, vehicles, air plane and water transport based on their destination. The number of passengers require for travel are not always balanced with the capacity of transport required for service.
If the supply of the transport is less than the passenger demand the passengers are obligated to wait for the transport service for a long period of time which resulted in delay. Delays are the result of a great difference between demand for a service and the capacity available to meet that demand. Usually this failure to correspond is temporary and due to natural liable to vary in the timing of demands and in the duration of time needed to provide service. This delay, in turn, is resulted in the creation of the passenger queue. According to (The federal democratic republic of Ethiopia Ministry of transport, 2011) as the world population increases, life requires competition which needs increased mobility. Ability of moving from place to place with comfort, reasonable cost and desired time is one of the major factors affecting the competency of individuals. Human beings use different modes of transport for mobility. The growth of modes of transport varies based on the level of development of countries.
As Ethiopia is a developing country, the transport service accessibility is low. According to (Tilahun Meshesha Fenta, 2014,) the increase of population of Addis Ababa is a mixture of three basic processes: rural-urban migration; natural increase, and re-classification of land from rural to urban categories. This population growth leads to the change to another social group of the residents and consequently the demand for public transport for the movement. Compared to the developed countries the change to another social group rate and service standard observed in the city of Addis Ababa is low. In the cities of developed countries average mobility rate per person or trip/day is 2.5. According to (The federal democratic republic of Ethiopia Ministry of transport, 2005) transport study the Addis Ababa mobility rate or average trip/day/person is 1.08. Old neighborhoods far from the main roads and expansion areas of the city are not well served by public transport. The city’s growth in economy, geographical area and population, brings urgent attention and needs additional mass transport service provision supported by capacity and technology.
The mobility rate and low service standards of transport accessibility leads the passenger for delays and the passenger wait the service for more than, at least, one hour at morning up to 11:00 am and afternoon after 3:00 pm. This variability and the interaction between the arrival and service processes make the dynamics of service systems very complex. As a result, it’s too difficult to predict levels of waiting line or to determine how much capacity is needed to achieve some wished level of performance without the help of a queueing model.
In transportation planning it is important to optimize the transport service with the passenger transportation service demand to reduce the passenger waiting time for the transport. To minimize the passenger delay time it requires to distribute the available transport capacity proportionally according to the number of passengers demand for transport service. Before distributing/assigning the available capacity proportionally some analysis method is required. This method is one of the methods of queueing theory model which is called multi-channel multi server queuing model, in which two or more servers or channels are available to handle arriving passengers.
Bus transport is the main type of public transport service in Addis Ababa city. According (Eshetie Berhan, 2013) and (Dejene Mengistu, 2013) the performance of Anbessa City Bus Service is low when compared with the bus service standard. They analyzed and design the optimum route of bus service based on the previous bus service trend. (Micheal Getachew, 2017) analyzed the Performance of Bus service and Addis Ababa Light Rail Transit based on the previous bus service trend. Then he modeled the Coordination Schedule on Anbessa City Bus Service Enterprise and Addis Ababa Light Rail Transit. But, these researchers have not considered the arrival rate of the passenger and the servers as well as the server’s service rate. Therefore this will be my research gap to analyze their performance and optimize using queuing theory model.
In urban passenger transportation the transport service may be govrnmental or private transport which is used by passengers for transport service. According to (Jiangfeng Xi et al, 2015) (H. Kim, J.-S. Oh, and R. Jayakrishnan, 2005) Transit buses and taxis are an integral part of the urban public transport system. Bus transport is characterized by its high passenger capacity, high efficiency, low per-passenger road use, and low environmental impact and is seen as an important measure for alleviating urban traffic congestions. Taxis convey passengers between locations of their choice, offering convenience, speed, and more flexible services. This differs from other modes of public transport where the pickup and drop-off locations are determined by the service provider and is favored by short-distance passengers. In other wards (Jorgen Aarhaug, 2016) defines that taxes as the parts of public transport. Therefore in this thesis while I refer the public transport service I mean the integration of buses and taxes as a public transport service.
Based on the deferent factors passengers prefer public transport or private public transport. These factors are the parameters which hinder the service rate and leads the passengers to waiting for a transportation service. By considering the possible causes of passenger waiting time being in queue for transportation service the queue modeling theory is used to know the capacity of the transportation whether public or private in general. Then the capacity will be evaluated, the transportation service rate will be analyzed, passenger arrival and inter arrival rate be measured and, to reduce the passenger waiting time the constrained based L.P will be used. Therefore the passenger waiting time for the transport service will be optimized in Addis Ababa city.
According to (The World Bank, 2016) report the city’s approach to address urban transport problems over the past twenty years— predominantly by expanding the transport infrastructure – but this has not made the desired improvements in accessibility for pedestrians and many public transport users. Daily time spent traveling in the city has increased, and the city is facing high levels of road traffic accidents, frequent congestion, and high levels of air pollution. These challenges are manifest even though motorization in Addis is quite low by world standards; investments in expansion of the road network has not been accompanied by improvements in traffic management or the development of public transport services. Mobility for the poor is effected primarily through walking and bus services provided by Anbessa City Bus Service Enterprise (ACBE), the city’s public bus operator.
In Addis Ababa city there are a lot of passengers waiting transportation services on the sides of the road. This passengers are waiting for a car service being in queue or without being in queue. Those passengers who are waiting for the car in the queue wait for the car transportation service for a long period of time until they get the car service. Those passengers who are not in the queue are waiting for undetermined or estimated period of time. When the car comes all passengers, who are waiting the transportation without the queue, those comes early or lately, are running to the car to get the transportation service. In the competition of getting the car transportation service those who have a force will get the car transportation. But those who are elder, sick or unhealthy, children and has no force are under question of getting service in this competition. The problem is those passengers who are in queue or waiting in dispersed comes from different areas and goes to different areas. Almost this problem is occurred morning and afternoon rush hours when the passengers goes to the work and comes from the work respectively.
Deferent factors may be caused to the passenger to wait for a transportation service based on the passenger’s interests. These factors may be the cost of transport, the safety of transport, the speed of transport, the direction of transport, imbalance of transport available and passenger demand, congestion or traffic jamming, duration of traffic signal, the volume of the car per passenger, and etc. not only this but also being governmental public transport and private public transport is another factors when it is seen based on their purpose.
The purpose of governmental public transport is basically to provide the scheduled service for the passengers transport with the low transport cost by taking, the level of population life standard, into consideration. But the purpose of private public transport is business oriented. Life standard is not their business. Their daily effort is only to make money regardless of the cost of transport and the schedule of passenger transport services. Taxis provide a publicly available service and are therefore part of public transport. However, the lack of regular schedules, routes and set station –all features characteristics of public transport-gives it a semi private character. Fixed public transport services cannot support all travel demand.
Taxis are an important feature of urban mobility, but they may be the cause to a challenge in many cities due to Safety issues (related to vehicle quality and driver behavior), Quality issues(low quality of vehicles and service, inability of customers to assess quality), Competition with public transport (city space limited), Quantity issue (over supply or under supply), Social issues (long working hours and low , irregular wages), Illicit behavior (competition for passengers, criminal activities), Overpricing (weak negotiation position of customers) etc.
The general objective of the study is to analysis the available capacity of transport supply and to optimize the passenger transportation service delay to reduce the passenger’s delay time in transportation service process in Addis Ababa city of Ethiopia.
To measure and analyses the service rate and the existing capacity of passenger transport servers of Addis Ababa city.
To identify the factors that causes to the passengers queue/delay of Addis Ababa city.
To measure and analyses passenger arrival rate and, transportation service rate to respond the passenger demand for transport in Addis Ababa city.
To identify the capacity planning of Addis Ababa road authority to respond to the demand of passenger transportation service.
To develop the method of optimizing the passenger transportation service of Addis Ababa city.
1.4 The research question
What is the service rate and the available capacity of passenger transport servers Addis Ababa city ?
What are the factors causesed to the passengers queue/delay of Addis Ababa city at every taxi, minibus and bus station.?
What are the passenger arrival and transportation service rate to respond to the passenger demand for transport in Addis Ababa city?
What are deviation of passenger transportation demand and the available transportation capacity of Addis Ababa city ?
How the passenger transportation service will be improved to reduce passenger delays in Addis Ababa city?
Significance of the study
This study helps the Planners and policy makers of the city to forecast the transport required as well as the demand of the passenger transport service based on the number of population growth rate and rural to urban population mobility rate.it helps Not only Planners and policy makers but also it enables the Passenger and Drivers to use their time efficiently. Passenger get access easily to go to their destination without delaying. As a result, the cost of waiting time would be minimized. The Drivers transport the passengers more frequently than the before. The more trips they prove service they receive more benefited from the speed of service provided. In general the Addis Ababa road authority and any passenger who uses the Addis Ababa road passenger transport would benefited from this research.
Scope of the study
The thesis focuses on the analysis of the present or on hand transport capacity using queuing theory model and, develop the method of minimizing the cost of passenger delays or the cost of passenger waiting time for transport service. To minimize the cost of passengers waiting time or delay time, constrained based L-P was developed.
1.7 Organization of the Thesis
“From the beginning of history, human sensitivity has revealed an urge for mobility leading to a measure of Society’s progress. The history of this mobility or transport is the history of civilization. For any country to develop with right momentum modern and efficient Transport as a basic infrastructure is a must. It has been seen throughout the history of any nation that a proper, extensive and efficient Road Transport has played a major role. ‘Transporters’ perform one of the most important activities, at every stage of advanced civilization. Where roads are considered as veins and arteries of a nation, passenger and goods transported are likened to blood in circulation. Passenger Road Transport Service (PRTS) is an essential connected to the economic development. Transport is the essential convenience with which people not just connect but progress. Throughout history, people’s progress has been sustained on the convenience, speed and safety of the modes of transport. Road transport occupies a primary place in to-day’s world as it provides a reach unparalleled by any other contemporary mode of transport.” (CITATION)
The Importance of Public transport
(Ar Anuj Jaiswal, Dr. Ashutosh Sharma, 2012)In enabling the economic efficiency, social cohesion ; the physical integration of an urban area, transport has a very important and a key role. (Rakesh Belwal and Shweta Belwal, 2010)To ensure the state of being strong and active of activities of its citizen’s life, industry, and government, effective public transportation services are a must in every country. According to (American public transportation association, 2007) Public transportation is critical to this nation’s future for A stronger economy, conservation of energy and resources, reduced congestion, less global warming and improved air quality and health, critical support during emergencies and disasters, increased real estate values and development, mobility for small urban and rural communities, increased access for groups of all ages and circumstances, lower health-care costs which all contribute to a better quality of life.
The use of public transport is increasing in developed and developing countries in a similar way.
Even though, the interests of the use of public transportation services is increasing in both developed and developing countries, there are many challenges which affects the performance and serviceability of the transport service with regard to meet the customer requirement. According (Michael D.Meyer, 2005) the main challenge of public transportation which pushed it to limit, and increase the demand of transport service are the trends in population growth, technological change, and the increased globalization of the economy. With these considerations in mind the most critical transportation issues facing the nation in the new (21st) century:
• Congestion: increasingly congested facilities across all modes;
• Emergencies: vulnerability to terrorist strikes and natural disasters;
• Energy and Environment: extraordinary challenges;
• Equity: burdens on the disadvantaged;
• Finance: inadequate revenues;
• Human and Intellectual Capital: inadequate investment in innovation;
• Infrastructure: enormous, aging capital stock to maintain;
• Institutions: 20th century institutions mismatched to 21st century missions; and
• Safety: lost leadership in road safety.
Deferent scholars used deferent method to overcome the challenges of public transportation service to increase the customer satisfaction and efficiency of the transport service. According to (MUKTI ADVANI AND GEETAM TIWARI*, 2006) public Bus transport systems have evolved from single route operations in small to medium size cities to high capacity systems in large urban agglomerations. Improvement in capacity utilization and operating costs have come from incremental changes in bus stop locations, scheduling, route operations, route planning, fleet management, special infrastructure designs, and institutional structures. This shows possible capacity improvement because of incremental changes in various aspects. Bus transportation is a predominant mode of urban transit. As cities grow the bus system is required to cater to a spatially and temporally diverse demand.
(Theo H. J. Muller and Peter G. Furth, 2009) suggesting the importance of Transfer Scheduling and Control system to reduce Passenger Waiting Time. According to this researcher holding connecting vehicles prevents missed connections because of early departures and holding just until the connection is made prevents unnecessary delays after passengers have transferred.
Optimization of public transport
(Martin Anokye et al, 2013) build a basic model of vehicular traffic based on queuing theory. The result suggests that the government could introduce a public transport system so that people do not travel with private cars to their places of work to reduce congestion on the roads, which in turn boosts productivity.
(Jiangfeng Xi et al, 2015) introduced a model-based approach to study the feasibility of having an integrated design to reduce delays to buses from taxi transport by determining whether an integrated single stop design is plausible to serve both buses and taxis at the same time and used vehicle arrival, probability distributions, and queuing theory to look into the traffic characteristics at bus stops.
(Mithun Mohan and Satish Chandra, 2017) estimated passenger car equivalents at signalized intersections using Queue clearance rate method. According to their estimation the result shows that the deviation associated with equivalent flow deduced from estimated PCE values were within 10% of approach’s capacity for different cases of simulation. This indicates that QCR method is suitable for PCE estimation at signalized intersections.
(Orazio Giuffrè et al, 2015) Developed passenger car equivalents for freeways by Microsimulation using various methodologies to calculate the passenger car equivalents for heavy vehicles for different types of facilities based on flow rate and density, queue discharge flow, headways, speed, delays, volume/capacity ratio, platoon formation and travel time. The result shows that PCE estimations are small at low flow rates and increase with increased flow rates due to at low volumes there are few passenger cars that can be influenced by heavy vehicles
(Bayan Bevrani et al, 2017)Used linear programming model (LP) to assess a capacity for multi-modal transportation systems. The result of the assessment Indicates that quantitative techniques are worthwhile and may help transportation planners build better MMTS. Quantitative approaches can in theory be integrated into existing information technology platforms and their data requirements are no longer unrealistic in this day and age. Our approach can facilitate a variety of capacity planning and querying activities and provides a mechanism to quickly analyze the effect of structural and parametric changes within MMTS.
(Xiangming Yao et al, 2017) simulated-based dynamic passenger flow assignment modeling – based transit network dynamic traffic assignment (DTA) models. The result Indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.
(Makrand Wagale et al, 2013) analyzed Real-Time Optimal Bus Scheduling for a City using a Demand and Travel time Responsive (DTR) Model. The result shows that it was found that the optimal cost for entire route per hour and optimal service frequency of per hour against the maximum traffic cost per hour and minimum traffic cost per hour with average frequency of buses per hour. It is also found that the capacity of buses is not fully utilized for single trip, because of that In-vehicle congestion cost was zero.
(Ahmed M. El-Geneidy et al, 2006) analyzed the Effects of Bus Stop Consolidation on Passenger Activity and Transit Operations with mathematical simulation. The result Indicated that bus stop consolidation had no significant effects on passenger activity, whereas bus running times improved by nearly 6%. Running time improvements may have been limited by insufficient schedule adjustments.
(Lars Briema et al, 2017) Integrating public transport into mobiTopp by using agent-based travel demand model mobiTopp and they implemented a time table, which is used for two purposes. First, it serves as input for the Connection Scan Algorithm, which is used by the agents to find the routes with earliest arrival time at their destinations. Second, it is used for the movement of the public transport vehicles. The model also contains capacity constraints for vehicles, which, when activated, result in a noticeable increase in travel time
(JIAO Peng-peng, et al, 2015) Bus scheduling is widely adopted in urban public transportation management organization. Bus operation and organization projects are the basis of bus scheduling and the operation time table is the core of bus operation organization, the critical work to enhance bus operation efficiency and service level is to achieve the reasonable headway
(Esteve Codina et al, 2017) Setting services in public transit lines in short time periods under time-varying demand using Mathematical programming based model Benders decomposition for discrete networks; and, for partially continuous networks, a combination of both the Benders decomposition and the projected gradient heuristics. For small networks with a moderate number of services and time horizons hours, the algorithmic alternatives find a good solution in fractions of a minute, and the faster algorithmic approach has proven to be the projected gradient heuristic for discrete networks. When the number of services is larger or in a larger railway network over a period of 12 hours, the best alternative was using the Benders decomposition while controlling the number of cuts or simply limiting the size of the Master Problem. Although the computational viability of the model is good, it could probably be enhanced by testing other methods for accelerating the Benders algorithm.
(Chenfeng Xiong et al, 2017) predict the travel behavioral response using an AgBM-DTALite: An integrated modelling system of agent-based travel behavior and transportation network dynamics (travel behavior models and traffic simulation). The integration demonstration showcases the capability of the integrated AgBM-DTALite model system. The model can predict rich behavioral responses using agent-based simulation. Departure time, mode, and route adjustments are included in the dimensions of the model. Without assuming perfect rationality, the model instead captures agent-based information search, learning, and knowledge updating. These individual-level modelling components guide search starting, search stopping, and search directions for each agent. When all agents stop their search, the system reaches BUE.
(Haitao He et al, 2017) used mathematical framework to evaluate analytically a flexible sharing strategies on multi-modal arterials. The analytical evaluation result Show that arterials with properly installed pre-signals could improve the person-throughput during rush hours, compared to implementing an inter-mittent bus lane or a dedicated bus lane. Therefore, bus priority could be provided without significant damage to car operations. This makes it more feasible for different stakeholders to agree on the implementation of bus priority strategies, which could lead to a more sustainable transportation system in the long run, with more passengers using the bus mode.
(Mouna Mnif, Sadok Bouamama, 2017) used Firework Algorithm to Optimize Multi-Objective of a Multimodal Transportation Network Problem based on the Pareto-dominance. The approach is applicable to be successfully applied in the large cities. Also, their ability of simultaneously determining for travel demands and satisfying multiple objectives. In addition, we show that the efficient algorithms find solutions included in the Front Pareto. The MFWA approach aims to identify good-quality feasible solutions and also, aims to improve them by giving a balanced optimistic solution between the set of objectives.
(Ties Brands et al, 2014) optimization of multimodal Passenger transportation networks coping with demand uncertainty using multi-objective optimization techniques. The result Indicate that a different transportation demand has a strong influence on the Pareto optimal performance of solutions in the set: 70% of the solutions do not perform Pareto optimal any more if assessed using a different transportation demand. However, the loss in objective function values is small (a 2% decrease in hyper volume value), so although performance is not optimal any more in most cases, loss in performance is limited. In addition, the resulting decision variables are relatively insensitive for transportation demand.
(Heimir Thorisson, James H. Lambert, 2017) analyzed Multi-scale identification of emergent and future conditions along corridors of transportation networks using big- data integration. The result demonstrations suggest the efficacy of the approach to sustain the efficient, reliable, and safe movement of passengers and freight.
(Saadia Tabassum et al, 2017) tried to design feeder network for mass transit system in developing countries by using gravity model. The results shows that not only the population density but the distribution of population within an area must be pre considered and evaluated. An area/town with non-uniform population distribution will result in longer feeder cycle length and vice versa
Multi modal Integration
(Xin Sun et al, 2017) evaluated the dynamic of tether transportation system using absolute nodal coordinate system in different configurations which are illustrated using numerical simulations. The deflection of the tether and the trajectory of the crawler during the transportation is investigated. Finally, the effect on the orbit of the system due to the crawler is revealed.
(Jianguo Qi et al, 2018) Integrated train operation zone and stop plan to optimize with passenger distributions using Mixed-integer linear programming model. The result shows that the proposed method can generate jointly optimized train operation zones, stop plans and passenger distribution plans. In addition, the generated passenger distribution plans can serve as a useful reference for the distribution of tickets for each train in real-world operations.
(Ali Gholami*, Maysam Ziaee, 2017) Development of a performance measurement system to choose the most efficient programs of the transportation system Using Performance measurement frameworks. The analysis shows that modification of the current Taxi Khattee (equivalent to jitney) and introducing the bus rapid transit (BRT) system are the most efficient programs. The very expensive interchange or light rail transit (LRT) system are not as efficient as a modification of the current bus system.
(Tierra S. Billsa, Joan L. Walker, 2017) Examined distributional impacts of transportation improvements looking beyond the mean for equity analysis using activity-based travel demand models. The result Show that distributional comparisons are capable of clearly revealing the winners and losers that result from transportation improvements, in comparison with average measures.
(Magnus Frestad Nygaard and Trude Tørset, 2016) planned the strategy for public transport passengers waiting time using transportation model with field registrations and surveys, passengers’ actual waiting time and their waiting time strategies. The result shows that passengers plan their arrival to bus stops, which implies a lower waiting time than assumed in the transport models. Though random arrivals probably represents a realistic arrival pattern in frequent public transport services, the arrival pattern is quite different in low-frequency services. This could partly be defended by saying we include the hidden as well as the registered waiting time. However, it seems unlikely that the current assumptions in transport model is representing waiting time strategy in a meaningful way.
Research Design and Methodology
In This chapter the research design framework and methodologies followed would be presented as a road map of this study. Different qualitative and quantitative data sources are utilized in the methodology.
3.1 Research Design
3.2 Conceptual framework
Passenger go to their destination
No passenger delay
Mixed integer programming
Adjust multipliers in the model
First come first served (FCFS)
Queue … n
Transport service is available
Passenger arrival rate
Passenger service rate
Figure SEQ Figure * ARABIC 1 research conceptual framework
3.3 Research Methodologies
Draft interview questionnaires
The purpose of this survey is to analysis the Capacity and optimization of passenger public transportation service delay in Addis Ababa city for getting people to and from work.
Interview Questionnaire for the enterprize
what are the objective of your organizations?
To achieve your objective what are the level of your capacity (number of buses)?
How do you assign this buses to each routes?
What are the basic criteria to assign the buses to each route?
Do you think your customers are satisfied with your current bus assignment?
If your answer question no. 1.5a is no what are the main challenges that face your enterprise in order not to satisfy your customers?
How do you control the transportation system of your organization whether they are fulfilling or not their responsibility?
What is the arrival rate of buses at their destination area?
What is the arrival rate of passenger at their boarding/allighting busstoping area?
What are the service rate of each bus per route daily?
What is the target of your service rate of each bus per route daily?
What is your achievement service rate of each bus per route daily?
Where is the origon, destination, travel distance, number of stops and number of trips of each bus?
What the target time set for each bus per route to reach its destination?
What is the avarage real time it takes for each bus per route to reach its destination?
What is the costs of your enterprises?
What is the revenue ofyour enterprises?
Interview Questionairs for passengers
Which type of transport is your favorite transport?
Why have you preferd bus transport sevice?
How often do you use the bus service?
How long do you have waited for the bus service?
Are you satisfied with this service rate?