Urban Traffic Congestion Pricing Model with the Consideration of Carbon Emissions Cost

Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode) urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.

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Research on the Urban Transportation Development in Our Country Based on the Traffic Congestion Pricing

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.97-98.1032 ◽

2011 ◽

Vol 97-98 ◽

pp. 1032-1037

Author(s):

Wei Kou ◽

Lin Cheng

Keyword(s):

Traffic Congestion ◽

Marginal Cost ◽

Demand Management ◽

Urban Transportation ◽

Congestion Pricing ◽

Developed Countries ◽

Urban Traffic ◽

Theory And Practice ◽

Traffic Demand ◽

Transportation Development

With the development and realization of industrialization and urbanization in the world, urban traffic volume grows rapidly; many big cities face more and more serious traffic problem. As a mean of traffic demand management, traffic congestion pricing has important significance in theory and practice. Traffic congestion pricing can counteract external diseconomy caused by network congestion, and the price of congestion is tantamount to the difference between social marginal cost and private marginal cost. This paper analyzes the economic theory of congestion pricing. Combined the effect of traffic congestion pricing that implemented in the developed countries, it researches the influence of urban transportation development in our country in the future based on the implementing congestion pricing.

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AN ECO-ENGINEERING MATHEMATICAL MODEL FOR THE TRAFFIC CONGESTION FEE

The Singapore Economic Review ◽

10.1142/s0217590810003900 ◽

2010 ◽

Vol 55 (03) ◽

pp. 575-583

Author(s):

MALIK BESHIR MALIK ◽

MUSTAFA BABIKER

Keyword(s):

Mathematical Model ◽

Data Collection ◽

Public Participation ◽

Traffic Congestion ◽

Congestion Pricing ◽

Road Networks ◽

Parametric Estimation ◽

Pricing Model ◽

The World ◽

Physical Expansion

Traffic congestion is becoming a problem all over the world and physical expansion of road networks is becoming not the best option due to cost and other reasons. This paper considers the option of a congestion pricing model and explains its rationale and parametric estimation. The case of a city is studied to reflect on the potential of data collection mechanisms and public participation and awareness.

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Correlation Analysis of Internet Car and Urban Traffic Congestion Based on Logistics Regression Congestion

CICTP 2020 ◽

10.1061/9780784483053.309 ◽

2020 ◽

Author(s):

Guangliang Zhang ◽

Jian Wang ◽

Xiaowei Hu

Keyword(s):

Correlation Analysis ◽

Traffic Congestion ◽

Urban Traffic ◽

Logistics Regression

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Comprehensive Pricing Model of Urban Traffic Air Pollution Based on Bi-Level Programming

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.253-255.1913 ◽

2012 ◽

Vol 253-255 ◽

pp. 1913-1917

Author(s):

Ze Bin Zhao

Keyword(s):

Air Pollution ◽

Negative Impact ◽

Urban Traffic ◽

Vehicle Speed ◽

Pricing Model ◽

The Sustainable Development ◽

Transport Services ◽

Relationship Model ◽

The Relationship

In order to reduce the negative impact of urban traffic air pollution, this paper firstly analyzes the relationship between urban traffic air pollution and vehicle speed, after providing the relationship model, the paper establishes a comprehensive pricing model of urban traffic air pollution based on bi-level programming, the model considers the traffic air pollution pricing, and includes the factors of congestion pricing, bus fee, pricing revenue redistribution on improvement of public transport services and the expansion of road capacity. The case study shows that the implementation of comprehensive pricing of urban traffic air pollution can reduce traffic pollution and unreasonable traffic flow, which is conducive to the sustainable development of the city.

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Population Density or Populations Size. Which Factor Determines Urban Traffic Congestion?

Sustainability ◽

10.3390/su13084280 ◽

2021 ◽

Vol 13 (8) ◽

pp. 4280

Author(s):

Yu Sang Chang ◽

Sung Jun Jo ◽

Yoo-Taek Lee ◽

Yoonji Lee

Keyword(s):

Population Density ◽

Population Size ◽

Traffic Congestion ◽

Critical Role ◽

Small Population ◽

High Density ◽

Urban Traffic ◽

Contradictory Result ◽

Low Density

A large number of articles have documented that as population density of cities increases, car use declines and public transit use rises. These articles had a significant impact of promoting high-density compact urban development to mitigate traffic congestion. Another approach followed by other researchers used the urban scaling model to indicate that traffic congestion increases as population size of cities increases, thus generating a possible contradictory result. Therefore, this study examines the role of both density and population size on traffic congestion in 164 global cities by the use of Stochastic Impacts by Regression on Population, Affluence and Technology model. We divide 164 cities into the two subgroups of 66 low density cities and 98 high density cities for analysis. The findings from the subgroups analysis indicated a clear-cut difference on the critical role of density in low-density cities and the exclusive role of population size in high-density cities. Furthermore, using threshold regression model, 164 cities are divided into the two regions of large and small population cities to determine population scale advantage of traffic congestion. Our findings highlight the importance of including analysis of subgroups based on density and/or population size in future studies of traffic congestion.

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