Freight Vehicle Travel Time Analysis: A Case Study of Birgunj Nagdhunga Corridor

2021 ◽  
Vol 08 (02) ◽  
pp. 1-13
Author(s):  
Abhishek Jha ◽  
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
License Plate ◽  
Monitoring Method ◽  
Factors Affecting ◽  
Average Travel Time ◽  
Major Factors ◽  
Vehicle Travel Time ◽  
Freight Vehicles

This study covers the freight vehicle, which clears the custom clearance process for Kathmandu and transports the same goods to Kathmandu from Birgunj. In this study average travel time for freight vehicles from Birgunj to Nagdhunga has been studied, along with the factors affecting the travel time from Birgunj to Nagdhunga. License plate monitoring method of the freight vehicles was done to find the average travel time and a questionnaire survey was done to identify the factors affecting travel time of the freight vehicle. The travel time from Birgunj to Nagdhunga is different for different types of, vehicle and good. The fastest average travel time is of fixed container of 40 feet size with 23.2 hours and longest average time is for fixed container of 20 feet size with 28.95 hours. The average travel time for non-degradable goods is 26.5 hours and for degradable goods is 22.38 hours. Major factors affecting the travel time are traffic congestion along the route, bad road condition along the route and hilly road with sharp bends, turns and grade.

scholarly journals Effect of Traffic Information on Travel Time of Medium-distance Trips: A Case Study in Tehran

2018 ◽  
Vol 30 (3) ◽  
pp. 281-291 ◽  
Author(s):  
Roozbeh Mohammadi ◽  
Amir Golroo ◽  
Mahdieh Hasani
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Information Dissemination ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Trip Distance ◽  
Traffic Information Dissemination ◽  
Time Reduction

In populated cities with high traffic congestion, traffic information may play a key role in choosing the fastest route between origins and destinations, thus saving travel time. Several research studies investigated the effect of traffic information on travel time. However, little attention has been given to the effect of traffic information on travel time according to trip distance. This paper aims to investigate the relation between real-time traffic information dissemination and travel time reduction for medium-distance trips. To examine this relation, a methodology is applied to compare travel times of two types of vehicle, with and without traffic information, travelling between an origin and a destination employing probe vehicles. A real case study in the metropolitan city of Tehran, the capital of Iran, is applied to test the methodology. There is no significant statistical evidence to prove that traffic information would have a significant impact on travel time reduction in a medium-distance trip according to the case study.

scholarly journals Bus Travel Time Reliability Incorporating Stop Waiting Time and In-vehicle Travel Time with AVL Data

2022 ◽  
Author(s):  
Zixu Zhuang ◽  
Zhanhong Cheng ◽  
Jia Yao ◽  
Jian Wang ◽  
Shi An
Keyword(s):  
Travel Time ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Influence Factors ◽  
Future Research ◽  
Travel Time Reliability ◽  
Independent Events ◽  
Harbin City ◽  
Bus Travel Time ◽  
Vehicle Travel Time

Abstract Improving bus operation quality can attract more commuters to use bus transit, and therefore reduces the share of car and alleviates traffic congestion. One important index of bus operation quality is the bus travel time reliability, which in this paper is defined to be the probability when the sum of bus stop waiting time and in-vehicle travel time is less than a certain threshold. We formulate the bus travel time reliability by the convolution of independent events’ probabilities, and elaborate the calculation method using Automatic Vehicle Location (AVL) data. Next, the No.63 Bus Line in Harbin City is used to test the applicability of the proposed method, and analyze the influence factors of the bus travel time reliability. The numerical results show that factors such as weather, workday, departure time, travel distance, and the distance from the boarding stop to the bus departure station will significantly affect the travel time reliability. At last, some general conclusions and future research are summarized.

Factors affecting maintenance cost of public buildings: case study of Tanzania Buildings Agency and National Housing Corporation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kassim Slim Zeni ◽  
Geraldine John Kikwasi
Keyword(s):  
Maintenance Cost ◽  
Public Buildings ◽  
Related Factors ◽  
Maintenance Costs ◽  
Content Type ◽  
Factors Affecting ◽  
Housing Corporation ◽  
Major Factors ◽  
National Housing

PurposeThe state of public buildings in Tanzania exhibits evidence of a lack of maintenance and repair. Despite efforts to raise the performance of public buildings, little emphasis is placed on maintenance works and related factors affecting maintenance costs of public buildings, which are often high. This study aims to examine factors affecting maintenance costs of public buildings.Design/methodology/approachThis was a case study involving two government building agencies – Tanzania Buildings Agency (TBA) and National Housing Corporation (NHC). A total of 387 tenants and 29 experts participated in the study. Data were collected using questionnaires and analyzed using Stata version 16 – descriptive statistics feature reporting absolute numbers and frequencies.FindingsBoth tenants and experts ranked building age, poor quality control, building material used, execution of work when it is urgent and inadequate financial resources as major factors affecting maintenance costs of public buildings. In the distinctive rating, tenants ranked resource management as a major factor, while experts ranked ignorance about the property of materials, misuse of buildings and faulty maintenance as major factors.Research limitations/implicationsThe study has some limitations such as geographical coverage which is limited to Dar es Salaam and Dodoma regions, hence missing information from other regions may have different experiences. Additionally, data were collected in a self-reported manner which could bring about information bias.Practical implicationsFindings of this study provide an insight on recent developments on the factors affecting maintenance cost of buildings using two cases of NHC and TBA which are single entities owning a substantial amount of housing units in Tanzania. Factors affecting the maintenance cost of public buildings identified in this study is a threshold for experts to devise strategies for minimizing maintenance costs.Originality/valueTo the best of the authors’ knowledge, this is the first study that assessed factors affecting maintenance cost in public buildings run by TBA and NHC from the tenant and expert perspectives.

scholarly journals Traffic Congestion in Dar es Salaam: Implications for Workers’ Productivity

2016 ◽  
Vol 9 (6) ◽  
pp. 103 ◽  
Author(s):  
Hosea Mpogole ◽  
Samira Msangi
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Dar Es Salaam ◽  
Transport Systems ◽  
Peak Period ◽  
Traffic Jam ◽  
Average Travel Time ◽  
Commuting Time ◽  
Travel Time Index ◽  
The City

Inadequately planned transport systems result to traffic congestion, a challenge that has for long been a thorn in Dar es Salaam, the city most affected in Tanzania. Although traffic congestion has been a major concern in Dar es Salaam, marked reluctance has been noticed in taking measures towards a lasting solution thus, it is of diminutive surprise that limited studies and documentations on the same are in existence. Therefore, this study assesses traffic congestion in Dar es Salaam and particularly its implications for workers’ productivity. Travel time and productivity indexes were established from a sample of 96 workers who used public transport along Morogoro and Mandela Roads. Travel time index (TTI) is the ratio of the average travel time during peak period to the travel time during off-peak period. Findings reveal that TTI was 2.19. Workers spent about 2 times of the average commuting time to work and 3 times of the same commuting from work to their various residences. About 2.5 hours were lost on traffic jam per day and that people worked 1.4 times less than the required time due to traffic congestion. It was further established that in 10 working days, almost 3 days were lost to traffic congestion. Since there are ongoing efforts to improve the transport system through the Bus Rapid Transit (BRT) project, it remains to be seen as to what extent traffic congestion will be reduced. In either case, this study provides a benchmark for comparisons.

scholarly journals IMPLEMENTATION OF TRADE SECRET CASE STUDY SAMSUNG MOBILE PHONE

2019 ◽  
Author(s):  
Arie Setya Putra
Keyword(s):  
Economic Status ◽  
School Context ◽  
School Type ◽  
Main Role ◽  
Effective Teacher ◽  
Factors Affecting ◽  
Complex Process ◽  
Computer Knowledge ◽  
Major Factors

Academic achievement is one of the major subjects in the educational researches.Academic achievement is defined as the outcomes of the education. Preventingstudents from failure is related with identifying the factors affecting the achievement.By defining the important factors affecting the students’ achievement, failure can beunder controlled [Ozguven, 1974]. Education is a complex process and many factorsdirectly or indirectly may affect achievement. Besides, it is difficult to properly definethe major factors influencing students' achievement. Although researchers haveidentified several factors affecting the student achievement, there are still somearguments about them. Some researchers attribute the student’s achievement to theschool; others indicate that the school makes little impact on academic outcome. Otherresearchers say that the effective teacher is the only one who can play the main role interms of student progress. All the factors such as teacher, school context, classroomcontext and the community around the school contribute or impact student’sachievement somehow [Harris, 1999]. In all these thoughts, we can see that there arethree common factors affecting the students’ achievement. Factors related withteachers, students and lastly environment. All these factors are affective on thestudents’ grade more or less. In our research, we handle the students’ perspective andsearch for the factors affecting the students’ achievement i n their demographic itemssuch as age, sex, and their academic background such as high school type, grade,University Entrance score, their families’ social and economic status, income, housing,computer knowledge skills and social behaviors and mannerism. The aim of this studyis to find out what kinds of factors have effects on students’ exam success among thestudents at School of Transportation and Logistics by using the path analysis.

scholarly journals Factors Affecting Road Rating

2020 ◽  
Vol 3 (1) ◽  
pp. 17
Author(s):  
Fei Wang ◽  
Bokuan Zhang ◽  
Ruishu Gong
Keyword(s):  
Neural Network ◽  
Travel Time ◽  
Traffic Congestion ◽  
Queuing Theory ◽  
Vehicle Speed ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
Important Research Topic ◽  
Learning Machine ◽  
The Stability

The decision of traffic congestion degree is an important research topic today. In severe traffic jams, the speed of the car is slow, and the speed estimate is very inaccurate.This paper first uses the data collected by Google Maps to reclassify road levels by using analytic hierarchy process. The vehicle speed, road length, normal travel time, traffic volume, and road level are selected as the input features of the limit learning machine, and the delay coefficient is selected. As the limit learning machine as the output value, 10-fold cross-validation is used. Compared with the traditional neural network, it is found that the training speed of the limit learning machine is 10 times that of the traditional neural network, and the mean square error is 0.8 times that of the traditional neural network. The stability of the model Significantly higher than traditional neural networks.Finally, the delay coefficient predicted by the extreme learning machine and the normal travel time are combined with the knowledge of queuing theory to finally predict the delay time.

scholarly journals Saving Travel Time as an Urban Planning Instrument. Case Study: Manizales, Colombia

2018 ◽  
Vol 12 (6) ◽  
pp. 44 ◽  
Author(s):  
Carlos Alberto Moncada ◽  
Santiago Cardona ◽  
Diego Alexander Escobar
Keyword(s):  
Travel Time ◽  
Direct Influence ◽  
Urban Mobility ◽  
Road Infrastructure ◽  
Urban Road ◽  
The Road ◽  
Average Travel Time ◽  
Future Situation ◽  
The City

This research explores the benefits of a proposal for urban road infrastructure which aims to improve road connection between northwest and western neighborhoods of the city of Manizales, Colombia, as well as to expand the ring of urban mobility that runs through the city. By calculating the global average accessibility and comparing the current and future situation, by averages of savings gradient, timesaving generated by this alternative are obtained in terms of average travel time. There is evidenced that suggest the road infrastructure proposal would generate savings in the average travel times for the entire city, especially to the neighborhoods located in the area of direct influence.

An Assessment of Factors Affecting Absenteeism: Case Study of a Major South African Manufacturer

2021 ◽  
Vol 44 ◽  
Author(s):  
Lewisham Gutsa ◽  
Rosemary-Jane Luke
Keyword(s):  
South African ◽  
Personal Development ◽  
Quantitative Research ◽  
Future Research ◽  
Development Working ◽  
Family Responsibilities ◽  
Factors Affecting ◽  
Number Of Factors ◽  
Major Factors

Absenteeism is a major problem globally and, in South Africa, costs the country and companies millions of rands each year. Given the financial constraints on businesses at present, it is necessary to understand the causes of absenteeism in order to determine possible interventions to reduce these causes. A quantitative research design was used to investigate the factors that influence absenteeism at a major South African manufacturer. An exploratory factor analysis was used to reduce the number of factors. The study found that there were seven major factors that had an impact on absenteeism, namely, external factors, management factors, illness, family responsibilities, personal development, working conditions, and motivation. These factors were found to affect different employees differently, and were mainly dependent on the demographic characteristics of the employees. This study provides insights into absenteeism in a typical South African situation. The study finds that because factors that have an impact on absenteeism are different for various employees and are dependent largely on demographic and related attributes, organisations need to develop diverse strategies to deal with the absenteeism issues of different employees in organisations. Future research should investigate the efficacies of various interventions to determine which are most likely to meet the needs of the various groups of employees and thereby reduce absenteeism levels.

An Approach to Boundary Finding of Intersection Group for Traffic Analysis due to Intersection Improvements

2015 ◽  
Vol 743 ◽  
pp. 413-421
Author(s):  
Ying Ying Ma ◽  
Ying Zeng
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Road Network ◽  
Laplacian Matrix ◽  
Traffic Analysis ◽  
Saturation Degree ◽  
Correlation Degree ◽  
Two Measures ◽  
Group Boundary

Increased traffic congestion makes intersection improvements are necessary to improve the capacity and traffic running conditions. Because of the influence of a certain intersection improvements is not limit to itself, but covers the intersections around it. The approach to find the boundary of signal group for traffic analysis due to a certain intersection improvements is discussed in this paper. Firstly, two kinds of correlation degree are modeled, which are the basis of intersection grouping. Saturation degree and free flow travel time are considered in the model of correlation degree between two adjacent intersections considers, while correlation degree between any two intersections in the network is analyzed using Laplacian matrix algorithm. Secondly, the approach to find intersection group boundary is proposed. Thirdly, two measures are adopted in quantifying the results of intersection grouping: minimum average cut correlation degree and minimum traffic influence on the intersections outside of boundary. At last, the developed method is used on a city road network. The results of case study confirm the validity of the proposed approach.

scholarly journals Individual Subjective Initiative Merge Model Based on Cellular Automaton

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Yin-Jie Xu ◽  
Yu-Guang Chen ◽  
Chao Yang ◽  
Yi-Chao Pu
Keyword(s):  
Travel Time ◽  
Positive Impact ◽  
Work Zones ◽  
Lane Changing ◽  
Traffic System ◽  
Input Condition ◽  
Average Travel Time ◽  
System Output ◽  
The Individual ◽  
Vehicle Travel Time

The merge control models proposed for work zones are classified into two types (Hard Control Merge (HCM) model and Soft Control Merge (SCM) model) according to their own control intensity and are compared with a new model, called Individual Subjective Initiative Merge (ISIM) model, which is based on the linear lane-changing probability strategy in the merging area. The attention of this paper is paid to the positive impact of the individual subjective initiative for the whole traffic system. Three models (ISIM, HCM, and SCM) are established and compared with each other by two order parameters, that is, system output and average vehicle travel time. Finally, numerical results show that both ISIM and SCM perform better than HCM. Compared with SCM, the output of ISIM is 20 vehicles per hour higher under the symmetric input condition and is more stable under the asymmetric input condition. Meanwhile, the average travel time of ISIM is 2000 time steps less under the oversaturated input condition.

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