scholarly journals Traffic Congestion Index and Level Estimation using Two Phase Fuzzy Controller

Helix ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 4029-4033
Author(s):  
Prachiti Pimple
Keyword(s):  
Traffic Congestion ◽  
Fuzzy Controller ◽  
Two Phase ◽  
Congestion Index

scholarly journals Assessment of network traffic congestion through Traffic Congestability Value (TCV): a new index

2015 ◽  
Vol 30 (30) ◽  
pp. 123-134 ◽  
Author(s):  
Nilanchal Patel ◽  
Alok Bhushan Mukherjee
Keyword(s):  
Land Use ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Spatial Interaction ◽  
Network Congestion ◽  
Surface Conditions ◽  
Time Average ◽  
Index Value ◽  
Congestion Index ◽  
New Formula

Abstract Traffic congestion is a major and growing problem in urban areas across the globe. It reduces the effective spatial interaction between different locations. To mitigate traffic congestion, not only the actual status of different routes needs to be known but also it is imperative to determine network congestion in different spatial zones associated with distinct land use classes. In the present paper, a new formula is proposed to quantify traffic congestion in the different spatial zones of a study area characterized by distinct land use classes. The proposed formula is termed the Traffic Congestability Value (TCV). The formula considers three major influencing factors: congestion index value, pedestrian movement and road surface conditions; since these parameters are significantly related to land use in a region. The different traffic congestion parameters, i.e. travel time, average speed and the proportion of time stopped, were collected in real time. Lower values of TCV correspond to a higher degree of congestion in the respective spatial zones and vice-versa and the results were validated in the field. TCV differs from the previous approaches to quantifying traffic congestion since it focuses on the causes of network congestion while in previous works the focus was generally on link flow congestion.

Analysis and Optimization of Hangzhou East Area Traffic Based on the Congestion Index Detection Platform

2014 ◽  
Vol 1030-1032 ◽  
pp. 2182-2186
Author(s):  
Ling Yan Ge ◽  
Bi Feng Zhu
Keyword(s):  
Automobile Industry ◽  
Traffic Congestion ◽  
High Speed ◽  
Road Traffic ◽  
Rapid Development ◽  
Traffic Demand ◽  
The Road ◽  
Fast Pace ◽  
Urbanization In China ◽  
Congestion Index

With the rapid development of urbanization in China and the motorization’s fast pace of high speed as well as the national automobile industry process, many cities in our country have been facing a huge problem - traffic congestion in recent years. And the essence of the problem is the imbalance between road traffic supply and traffic demand in the process of urban development. Aimed at the problem of traffic congestion, this paper based on Hangzhou city’s traffic congestion index of monitoring data from testing platform and statistical data from field survey , studied the Hangzhou east area of road traffic running situation, analyzed the causes of the east area of Hangzhou road congestion, and thus to adjust and optimize the road traffic system of the area, put forward reasonable system solutions and proposals to improve the management level

scholarly journals Research on road traffic congestion index based on comprehensive parameters: Taking Dalian city as an example

2018 ◽  
Vol 10 (6) ◽  
pp. 168781401878148 ◽  
Author(s):  
Wan-Xiang Wang ◽  
Rui-Jun Guo ◽  
Jing Yu
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Travel Speed ◽  
Service Level ◽  
Evaluation Indexes ◽  
Traffic Conditions ◽  
Calculation Results ◽  
Congestion Index ◽  
Operation Status ◽  
Road Traffic Congestion

Traffic congestion index reflects the state of traffic flow. The detection and analysis on traffic congestion index can be used to estimate the operation status of roads, to plan and organize road traffic for traffic managers, and to make the reasonable decisions of travelers to travel. The traffic conditions of several evaluation indexes were analyzed. Based on the theory of fuzzy mathematics, some membership functions of the evaluating indexes were designed. Three calculation methods of traffic congestion index were proposed. Their calculation results were compared mutually. The conclusion revealed that using saturation calculated by the corresponding service level of traffic congestion index not well reflect the traffic situation, what’s more, travel speed is used to calculate the congestion index of the first method. Using comprehensive parameters can calculate the congestion index of the third method. Both them are roughly similar and in line with the actual traffic phenomenon.

Study on the External Cost of Highway Congestion: Estimation Method and Application

2013 ◽  
Vol 295-298 ◽  
pp. 781-786
Author(s):  
Yang Li ◽  
Chun Chao Chu ◽  
Jian Ying Chen
Keyword(s):  
Traffic Congestion ◽  
Estimation Method ◽  
Estimation Methods ◽  
External Costs ◽  
Road Transportation ◽  
The Sustainable Development ◽  
Highway Transportation ◽  
Calculation Results ◽  
Congestion Index ◽  
External Time

The losses incurred by traffic congestion are an important part of the external costs of highway transportation. In this paper, traffic congestion index was proposed to estimate external costs of highway congestion. On basis of analyzing the composition and type of the external costs of traffic congestion, estimation methods about each type external costs were presented. By virtue of presented traffic congestion index and estimation methods, an application case was conducted on external time costs estimation about 2010 annual Beijing expressway congestion. Finally, some strategies to improve highway congestion were proposed according to the calculation results, which provided a reference for promoting the sustainable development of road transportation.

Freeway Traffic Congestion Identification Based on Fuzzy Logic Inference

2013 ◽  
Vol 397-400 ◽  
pp. 2227-2230
Author(s):  
Ming Long Peng ◽  
Xin Rong Liang ◽  
Chao Jun Dong ◽  
Yan Yan Liu
Keyword(s):  
Fuzzy Logic ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Weather Conditions ◽  
Freeway Traffic ◽  
Fuzzy Logic Inference ◽  
Identification Method ◽  
Congestion Detection ◽  
Congestion Index ◽  
Logic Inference

Traffic congestion detection is the basis of dynamic traffic control and real time guidance. This study proposes a fuzzy logic based traffic congestion identification method. The components of a fuzzy logic inference are firstly formulated. According to such information as the speed and occupancy of freeway traffic flow, and the weather conditions on the freeway, a congestion identification method based on fuzzy logic inference is then designed. Gauss curves are assumed for the membership functions of the input and output variables, and 45 fuzzy rules are also established. Finally, the congestion identification method is simulated. Simulation results verify the effectiveness of the above method. Fuzzy logic inference is suitable for estimating the traffic congestion index.

scholarly journals EXPLORING THE POTENTIAL OF TRAFFIC INDEX DATA TO ANALYZE ESSENTIAL TRAFFIC IMPACT IN DEVELOPING CITIES

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 137-141
Author(s):  
T. Moyo ◽  
A. Kibangou ◽  
W. Musakwa
Keyword(s):  
Traffic Congestion ◽  
Daily Basis ◽  
Economic Activities ◽  
Pollution Levels ◽  
Global Pandemic ◽  
Metropolitan Cities ◽  
Traffic Impact ◽  
Congestion Index ◽  
The Impact ◽  
The City

Abstract. In developing countries, metropolitan cities, due to their economic activities, attract an increasing amount of commuters on a daily basis. This has led to major freeways and roads experiencing high levels of congestion and consequently high pollution levels. In 2020, due to a global pandemic of an outbreak of Corona Virus (COVID-19), the national government declared a national shutdown with only essential traffic being allowed to operate. Given the scenario of the national lock-down this allows for the statistical analysis of the impact of essential traffic on the overall transportation system. Consequently the aim of the paper was to assess the congestion and CO2 emission impact of essential traffic for the City of Johannesburg. Using an exploratory approach, we monitored and collected traffic congestion data from the Tomtom traffic index for the metropolitan city of Johannesburg, South Africa. We develop a relationship between congestion and pollution to visualise the daily variations in pollution and congestion levels. We demonstrate this by comparing variations in congestion levels in two epochs, viz the period without movement restrictions and the period whereby movement is restricted. The results reveal essential traffic on the congestion index to be below 22 percent for both weekends and weekdays. A scenario common only during weekends in 2019. Whilst for the emission index, CO2 levels are approximately less than 45 percent throughout the week. The paper concludes the investment into mining and analysing traffic data has a significantly role for future mobility planning in both the developed and developing world and, more generally, improving the quality of commuting trips in the city.

scholarly journals Carpooling scheme selection for taxi carpooling passengers: a multi-objective model and optimisation algorithm

2017 ◽  
Vol 42 (2) ◽  
pp. 85-92 ◽  
Author(s):  
Qiang Xiao ◽  
Rui-chun He
Keyword(s):  
Traffic Congestion ◽  
Weight Vector ◽  
Urban Traffic ◽  
Experimental Result ◽  
Two Phase ◽  
Network Nodes ◽  
Multi Objective ◽  
Optimisation Algorithm ◽  
Objective Model ◽  
Scheme Selection

Carpooling has been long deemed a promising approach to better utilizing existing transportation infrastructure, the carpooling system can alleviate the problems of traffic congestion and environmental pollution effectively in big cities. However, algorithmic and technical barriers inhibit the development of taxi carpooling, and it is still not the preferred mode of commute. In order to improve carpooling efficiency in urban, a taxi carpooling scheme based on multi-objective model and optimisation algorithm is presented. In this paper, urban traffic road network nodes were constructed from the perspective of passenger carpooling. A multi-objective taxi carpooling scheme selection model was built based on an analysis of the main influences of carpooling schemes on passengers. This model aimed to minimise get-on-and-get-off distance, carpooling waiting time and arriving at the destination. Furthermore, a two-phase algorithm was used to solve this model. A rapid searching algorithm for feasible routes was established, and the weight vector was assigned by introducing information entropy to obtain satisfying routes. The algorithm is applied to the urban road, the Simulation experimental result indicates that the optimisation method presented in this study is effective in taxi carpooling passengers.

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