scholarly journals The impact of optimizing delivery areas on urban traffic congestion

2020 ◽  
Vol 37 ◽  
pp. 100569
Author(s):  
Farouk Hammami
Keyword(s):  
Traffic Congestion ◽  
Urban Traffic ◽  
The Impact

scholarly journals The Feasibility of Opening Communities -- Based on the Wiedemann Car-Following Model

2018 ◽  
Vol 11 (3) ◽  
pp. 57
Author(s):  
Xiao-Yan Cao ◽  
Bing-Qian Liu ◽  
Bao-Ru Pan ◽  
Yuan-Biao Zhang
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Gated Communities ◽  
Urban Traffic ◽  
Average Delay ◽  
Traffic Demand ◽  
Car Following ◽  
Car Following Model ◽  
Urbanization In China ◽  
The Impact

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.

scholarly journals Evaluation of driver exposure risk on toxins emitted from exhausts engine in traffic congestion simulated conditions

2018 ◽  
Vol 44 ◽  
pp. 00163
Author(s):  
Maria Skrętowicz ◽  
Anna Janicka ◽  
Radosław Wróbel ◽  
Maciej Zawiślak
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Traffic Congestion ◽  
Urban Traffic ◽  
Exhaust Emission ◽  
Passenger Cars ◽  
Traffic Lights ◽  
Traffic Conditions ◽  
Volatile Organic ◽  
The Impact

The increase in the number of vehicles and better availability of car purchase cause that nowadays people tend to spend more time inside cars. In urban traffic conditions, vehicles moves at low speeds. In addition, traffic lights and high traffic flows cause frequent stops of vehicles and often lead to congestions. The consequence is high amount of exhaust emission and high levels of the concentration of pollutants in the air. In such conditions, pollutants including hydrocarbons from the group of volatile organic compound enter the interior of vehicles with air passing into the cabin. It accumulates mainly in the area of the driver and the passengers heads. In this paper the results of the research of volatile organic compounds concentration inside two different passenger cars in simulated traffic congestion conditions are presented. The study involved vehicles of various ages: new (2011) and old (1999). On the basis of the study the driver exposure inside these vehicles to the impact of volatile organic compounds has been evaluated.

Net Impacts of Streetcar Operations on Traffic Congestion in Melbourne, Australia

2017 ◽  
Vol 2648 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Duy Q. Nguyen-Phuoc ◽  
Graham Currie ◽  
Chris De Gruyter ◽  
William Young
Keyword(s):  
Traffic Congestion ◽  
Urban Traffic ◽  
Future Research ◽  
Total Delay ◽  
Mode Shift ◽  
The Road ◽  
Long Term Effect ◽  
On The Road ◽  
Negative Impacts ◽  
The Impact

Public transit is widely recognized to reduce urban traffic congestion, as it encourages automobile travelers off the road. However, streetcars have been criticized for causing traffic congestion because large trams must operate in mixed traffic on narrow, congested streets. At the same time, streetcars reduce congestion by encouraging automobile drivers to use trams. So what is the net effect of streetcars on congestion? This paper presents a new method for assessing the net traffic congestion effects associated with streetcar operations in Melbourne, Australia, which has the largest streetcar network in the world. Impacts were determined with the use of a traffic network model to compare congestion with trams and without trams. The positive impacts of trams were estimated by using mode shift from tram to automobile when tram services were removed. Negative impacts were explored by considering streetcar traffic operations, the impact of curbside tram stops, and the effect of exclusive priority tram lanes on traffic flow. Findings show that the streetcar network in inner Melbourne results in a net congestion benefit to traffic; a 3.4% decrease in vehicle time traveled and total delay on the road network was established. The streetcar network also contributes to reducing the number of moderately congested links by 16%. Areas for future research are suggested, such as exploring the spatial distribution of the mode shift to automobile and the long-term effect of trams on traffic.

scholarly journals Impact of Rainfall on Traffic Speed in Major Cities of China

2021 ◽  
Vol 13 (16) ◽  
pp. 9074
Author(s):  
Min Zhang ◽  
Yufu Liu ◽  
Wenqi Sun ◽  
Yixiong Xiao ◽  
Chang Jiang ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Vulnerability Index ◽  
Urban Traffic ◽  
Healthy Development ◽  
Physical Examinations ◽  
Traffic Speed ◽  
Evaluation Mechanism ◽  
Congestion Index ◽  
The Impact ◽  
Important Basis

The construction of healthy transportation is an important ingredient for promoting the healthy development of cities. The establishment of an urban traffic evaluation mechanism can provide an important basis for the construction of healthy transportation. This study focused on the impact of precipitation on traffic speed and developed an urban traffic vulnerability index. This index reflects the degree of traffic affected by precipitation, which is calculated based on the traffic congestion index under different rainfall intensities. The traffic vulnerability indices of 41 major cities in China under rainfall conditions were evaluated. Based on the above traffic vulnerability indexes, the impact of socioeconomic factors on urban traffic vulnerability was analyzed. The three key findings of this study are as follows: there was a positive correlation between the vulnerability index and the gross domestic product (GDP); the urban population (POP) had a significant impact on the urban traffic vulnerability; and urban car ownership had little impact on traffic vulnerability. Based on these findings, possible measures to improve urban traffic vulnerability are proposed. The construction of an index system provides a basis for enhancing the urban traffic assessment mechanism, promoting the development of urban physical examinations and building healthy transportation and healthy cities.

scholarly journals GIS-Based Survey over the Public Transport Strategy: An Instrument for Economic and Sustainable Urban Traffic Planning

2021 ◽  
Vol 11 (1) ◽  
pp. 16
Author(s):  
Gabriela Droj ◽  
Laurențiu Droj ◽  
Ana-Cornelia Badea
Keyword(s):  
Network Analysis ◽  
Public Transport ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Accidents ◽  
Urban Traffic ◽  
The Public ◽  
Real Time Traffic ◽  
The Impact

Traffic has a direct impact on local and regional economies, on pollution levels and is also a major source of discomfort and frustration for the public who have to deal with congestion, accidents or detours due to road works or accidents. Congestion in urban areas is a common phenomenon nowadays, as the main arteries of cities become congested during peak hours or when there are additional constraints such as traffic accidents and road works that slow down traffic on road sections. When traffic increases, it is observed that some roads are predisposed to congestion, while others are not. It is evident that both congestion and urban traffic itself are influenced by several factors represented by complex geospatial data and the spatial relationships between them. In this paper were integrated mathematical models, real time traffic data with network analysis and simulation procedures in order to analyze the public transportation in Oradea and the impact on urban traffic. A mathematical model was also adapted to simulate the travel choices of the population of the city and of the surrounding villages. Based on the network analysis, traffic analysis and on the traveling simulation, the elements generating traffic congestion in the inner city can be easily determined. The results of the case study are emphasizing that diminishing the traffic and its effects can be obtained by improving either the public transport density or its accessibility.

The impact of subway operation on urban traffic: A GRA-BNs based study

2021 ◽  
pp. 1-16
Author(s):  
Lixin Yan ◽  
Tao Zeng ◽  
Yubing Xiong ◽  
Zhenyun Li ◽  
Qingmei Liu
Keyword(s):  
Bayesian Networks ◽  
Operating Characteristic ◽  
Urban Traffic ◽  
Relational Analysis ◽  
Traffic Security ◽  
Structural Network ◽  
Random Decision Forest ◽  
Roc Area ◽  
Grey Relational ◽  
The Impact

With the development of urbanization, urban traffic has exposed many problems. To study the subway’s influence on urban traffic, this paper collects data on traffic indicators in Nanchang from 2008 to 2018. The research is carried out from three aspects: traffic accessibility, green traffic, and traffic security. First, Grey Relational Analysis is used to select 18 traffic indicators correlated with the subway from 22 traffic indicators. Second, the data is discretized and learned based on Bayesian Networks to construct the structural network of the subway’s influence. Third, to verify the reliability of using GRA and the effectiveness of Bayesian Networks (GRA-BNs), Bayesian Networks with full indicators analysis and other four algorithms (Naive Bayes, Random Decision Forest, Logistic and regression) are employed for comparison. Moreover, the receiver operating characteristic (ROC) area, true positive (TP) rate, false positive (FP) rate, precision, recall, F-measure, and accuracy are utilized for comparing each situation. The result shows that GRA-BNs is the most effective model to study the impact of the subway’s operation on urban traffic. Then, the dependence relations between the subway and each index are analyzed by the conditional probability tables (CPTs). Finally, according to the analysis, some suggestions are put forward.

scholarly journals Behavior of Traffic Congestion and Public Transport in Eight Large Cities in Latin America during the COVID-19 Pandemic

2021 ◽  
Vol 11 (10) ◽  
pp. 4703
Author(s):  
Renato Andara ◽  
Jesús Ortego-Osa ◽  
Melva Inés Gómez-Caicedo ◽  
Rodrigo Ramírez-Pisco ◽  
Luis Manuel Navas-Gracia ◽  
...  
Keyword(s):  
Latin American ◽  
Public Transport ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Urban Transport ◽  
Control Measures ◽  
Johns Hopkins Hospital ◽  
Large Cities ◽  
Public Data ◽  
The Impact

This comparative study analyzes the impact of the COVID-19 pandemic on motorized mobility in eight large cities of five Latin American countries. Public institutions and private organizations have made public data available for a better understanding of the contagion process of the pandemic, its impact, and the effectiveness of the implemented health control measures. In this research, data from the IDB Invest Dashboard were used for traffic congestion as well as data from the Moovit© public transport platform. For the daily cases of COVID-19 contagion, those published by Johns Hopkins Hospital University were used. The analysis period corresponds from 9 March to 30 September 2020, approximately seven months. For each city, a descriptive statistical analysis of the loss and subsequent recovery of motorized mobility was carried out, evaluated in terms of traffic congestion and urban transport through the corresponding regression models. The recovery of traffic congestion occurs earlier and faster than that of urban transport since the latter depends on the control measures imposed in each city. Public transportation does not appear to have been a determining factor in the spread of the pandemic in Latin American cities.

scholarly journals An Efficiency Enhancing Methodology for Multiple Autonomous Vehicles in an Urban Network Adopting Deep Reinforcement Learning

2021 ◽  
Vol 11 (4) ◽  
pp. 1514 ◽  
Author(s):  
Quang-Duy Tran ◽  
Sang-Hoon Bae
Keyword(s):  
Reinforcement Learning ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Effective Means ◽  
Urban Network ◽  
Learning Agents ◽  
Policy Optimization ◽  
The Impact

To reduce the impact of congestion, it is necessary to improve our overall understanding of the influence of the autonomous vehicle. Recently, deep reinforcement learning has become an effective means of solving complex control tasks. Accordingly, we show an advanced deep reinforcement learning that investigates how the leading autonomous vehicles affect the urban network under a mixed-traffic environment. We also suggest a set of hyperparameters for achieving better performance. Firstly, we feed a set of hyperparameters into our deep reinforcement learning agents. Secondly, we investigate the leading autonomous vehicle experiment in the urban network with different autonomous vehicle penetration rates. Thirdly, the advantage of leading autonomous vehicles is evaluated using entire manual vehicle and leading manual vehicle experiments. Finally, the proximal policy optimization with a clipped objective is compared to the proximal policy optimization with an adaptive Kullback–Leibler penalty to verify the superiority of the proposed hyperparameter. We demonstrate that full automation traffic increased the average speed 1.27 times greater compared with the entire manual vehicle experiment. Our proposed method becomes significantly more effective at a higher autonomous vehicle penetration rate. Furthermore, the leading autonomous vehicles could help to mitigate traffic congestion.

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