scholarly journals Does Road Traffic Congestion Increase Fuel Consumption of Households in Kathmandu City?

2021 ◽  
Vol 3 (2) ◽  
pp. 67-79
Author(s):  
Raghu Bista ◽  
Surendra Paneru

The growth of vehicle and road traffic congestion is characteristics of urbanization and urban city and indicators of urban life in developing countries. In Nepal, non-economic factors and non-state factors have accelerated unexpectedly and haphazardly urbanization process, although the country was reengineered into seven provincial federal structure. In this backdrop, this paper empirically examines the growth of traffic congestion and its impact on urban households and livelihood based on 160 vehicle owners and users’ survey at six major traffic routes of two urban cities by applying mixed analytical methods (qualitative cum quantitative), descriptive statistics and multiple regression model. The descriptive statistics result of the study reveals nearly 94 percent acceptance level of vehicle owners and users about the growth of traffic congestion. Despite short distances of the road i.e. 2-4 kilometers and vehicle efficiency, the growth of traffic congestion increases 14036-liters fuel additional consumption. Per month, additional cost of fuel is estimated at 18,808 US dollars for a sum of distance i.e. 72,992 km between residence location and workplace each month. In the case of commuters, the estimation result of the study is 1188 hours of additional time loss with 6706 US dollars’ worth per month. The estimation of total economic loss is 25514 US dollars per month. Specifically, per month, economic loss of doctors and taxi drivers is 6556 US dollars but teachers and bankers have not economic loss.

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Chang-jiang Zheng ◽  
Rui He ◽  
Xia Wan ◽  
Chen Wang

Currently, the urban road traffic congestion is serious and the traffic accident is happening at a high frequency; thus it has not satisfied the travel needs of security and affects the quality of urban trips. In order to effectively relieve the confliction of people and motor vehicle, to make sure of the safety of pedestrians crossing the road, and to improve the capacity of urban roads, this passage focuses on studying the influence of pedestrians crossing the roads on the capacity of urban roads in three pedestrian crossing approaches including freely crossing the street, uncontrolled crossing of the pedestrian crosswalk, and controlled crossing of the pedestrian crosswalk. Firstly, it confirms the general formula of the road capacity when pedestrians are crossing the road based on three preassumptions, combined with the survey data, and then constructs the empirical mathematical model of pedestrian crossing on the capacity impact. Lastly, it takes the step of case calculation and simulation evaluation and calculates errors between them, finding that the error between the model calculation and software simulation is small. The efficiency of the model is validated and improved.


2021 ◽  
pp. 335-345
Author(s):  
Zainab A. Abood ◽  
Hazeem B. Taher ◽  
Rana F. Ghani

Intelligent Transportation Systems (ITS) have been developed to improve the efficiency and safety of road transport by using new technologies for communication. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) are a subset of ITS widely used to solve different issues associated with transportation in cities. Road traffic congestion is still the most significant problem that causes important economic and productivity damages, as well as increasing environmental effects. This paper introduces an early traffic congestion alert system in a vehicular network, using the internet of things (IoT) and fuzzy logic, for optimizing the traffic and increasing the flow. The proposed system detects critical driving conditions, or any emergency situation blocking the road, and broadcasts remote warnings to the following vehicles. Since not all vehicles are equipped with new technologies, Liquid Crystal Display (LCD) fixed on the roads displays the alert to warn the other vehicles which have neither communication nor sensors. The system was designed with Raspberry Pi 3 Model B equipped with sensors and GPS module to emulate real-world vehicles. The results and observations collected during the experiments showed that the proposed system is able to monitor the road conditions, detect the emergency situation, and broadcast a warning message to the approaching vehicles.


Many cities in the world face jamming problems in road traffic, particularly in metropolitan cities. At present the traffic controlling systems aresemiautomatic in nature. With the introduction of IoT in road traffic management systems, it revolutionizes the field of road traffic management system and improves the road traffic congestion problem.This paper proposes an IoT-based road traffic management system for metropolitan cities. The proposed system provides the hassle free movement of the vehicles to avoid inconvenience and reroute the higher priority vehicles. Experimental results show that the proposed system gives higher success rate for the low traffic density in the lane.


2011 ◽  
Vol 97-98 ◽  
pp. 907-910
Author(s):  
Zhi Min Gao ◽  
Fa Sheng Liu ◽  
Meng Chen

The urban road traffic congestion has not only brought many inconvenient for people's routine work and life, but also will restrict the growth of the economical, to accelerate the urban environment worsening and serious influence the city sustainable development. This paper studies based on the dynamic detection of urban road traffic congestion condition recognition technology can fast and accurate discover in the road network which already had the traffic congestion or soon occurs, then estimated the crowded proliferation scope and duration, which are advantageous to carry on the transportation induction and the traffic control promptly. And according to the different target client to the different emphasis point to the distinguish algorithm, has designed the urban road traffic congestion recognition grading warning system.


2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.


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