Research on Urban Transportation Development Strategy Transition

2012 ◽  
Vol 209-211 ◽  
pp. 1017-1020
Author(s):  
Jian Jun Wang ◽  
Dan Xiong ◽  
Da Lei ◽  
Yue Qiu ◽  
Jing Jing Fu

With the rapid development of the economy, most of our cities have entered a period of rapid development, urban traffic congestion and other problems have become increasingly prominent. In view of the above situation, we specially analyze domestic and international urban transportation development strategy and the formation of traffic pattern; explore the rule of urban transportation development strategy; comprehensively compare and analyze the advanced experience of domestic and international transportation development strategy; sum up urban transportation development strategy transition mode, the future developing trend and some macro traffic control strategy. It indicates the direction of alleviating urban traffic congestion and promotes the development of modern cities sound and rapid.

2011 ◽  
Vol 97-98 ◽  
pp. 1032-1037
Author(s):  
Wei Kou ◽  
Lin Cheng

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.


2014 ◽  
Vol 624 ◽  
pp. 520-523
Author(s):  
Dan Ping Wang ◽  
Kun Yuan Hu

With the rapid development of economics and technology; the number of vehicles has largely increased. In this paper, traffic guidance and traffic control systems were researched as well as the Internet of Things (IOT). The author tried to combine these three parts to send traffic data to road users so as to let them choose the best route to travel. Meanwhile, traffic network optimization has been realized to reduce traffic congestion areas. This paper has optimized regional traffic signal control systems based on IOT, traffic guidance as well as traffic assignment, involved data sources, IOT design patterns, data collection as well as the relationship between guidance obeisance rate and traffic jam. It also involved the definition of ideal traffic shortest routes, planning and designing of traffic control systems. Results and researches could hope to combine with reality in order to reduce traffic congestion.


Author(s):  
Shuai Ling ◽  
Shoufeng Ma ◽  
Ning Jia

AbstractThe rapid development of economics requires highly efficient and environment-friendly urban transportation systems. Such requirement presents challenges in sustainable urban transportation. The analysis and understanding of transportation-related behaviors provide one approach to dealing with complicated transportation activities. In this study, the management of traffic systems is divided into four levels with a structural and systematic perspective. Then, several special cases from the perspective of behavior, including purchasing behaviors toward new energy vehicles, choice behaviors toward green travel, and behavioral reactions toward transportation demand management policies, are investigated. Several management suggestions are proposed for transportation authorities to improve sustainable traffic management.


2020 ◽  
Author(s):  
Min Zhang

<p>With the rapid development of urbanization, many problems become more serious in big cities, such as traffic congestion. Different urban land use type can have different influence on traffic, therefore, the analysis of relationship between urban traffic and urban land use is important for better understanding of urban traffic status. This study firstly utilizes spatial data analysis method and time series analysis method to obtain urban traffic pattern from the spatial and temporal perspective, using one-week traffic sensor data, we measure the urban commuting patterns, which include weekday mode and weekend mode. Secondly, this study analyzes the relationship between traffic status and land use type in traffic analysis zone (TAZ) level, which indicates traffic status has spatial autocorrelation, besides, commercial land use and mixed land use type may result in more serious traffic congestion. The research can be of value for urban understanding and decision making in areas of urban management, urban plan and traffic control.</p>


2014 ◽  
Vol 1030-1032 ◽  
pp. 2254-2259
Author(s):  
Jin De Cai ◽  
Ke Zhang

With the increasingly serious problem of urban traffic congestion, more attention is focused on the Park and Ride (P&R) schemes based on urban transportation demand (TDM) management. The P&R locating research, as an important part of the scheme, plays an important role to strengthen the transportation management. On the basis of identifying all the potential P&R locations, and from the macroscopic perspective of urban transportation network, this paper establishes a model of P&R locating in order to minimize their construction costs as well as the total transportation costs. Example analysis is finally carried out with the help of Lingo software, thus testifying the validity of this research.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Hongna Dai ◽  
Enjian Yao ◽  
Rui Zhao

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.


2014 ◽  
Vol 971-973 ◽  
pp. 2208-2212
Author(s):  
Hong Duo Zhuo ◽  
Juan Yu Wu

Under the situation of rapid development of urban vehicles, worsening traffic congestion and the energy shortage, slow traffic system reflects concept of sustainable development of people-oriented and green environmental protection which is attracting more and more attention and recognition from the citizens. The efficient slow traffic system can not only save energy and alleviate the urban traffic congestion, but also improve the comfort and security of the citizens and guide them to form a new concept of green travel. In recent years, Guangzhou has set up the slow traffic system which based on the development of the Asian Games’ greenway, but on the detail design and user’s experience is questionable. This article will be based on the analysis and summary of the existing domestic and foreign slow system development model and the actual case studies. Then draw lessons from the experience, study the case of Ersha Island and combine with existing design of the greenway in Guangzhou. Use the bottom-up perspective to explore the slow traffic system design in central city of Guangzhou. In the future development, we should optimize for the detailed design in slow traffic system construction as well as the relevant planning and policy, and finally to promote the development of slow traffic system.


2021 ◽  
pp. 1-14
Author(s):  
Wanxin Hu ◽  
Fen Cheng

With the development of society and the Internet and the advent of the cloud era, people began to pay attention to big data. The background of big data brings opportunities and challenges to the research of urban intelligent transportation networks. Urban transportation system is one of the important foundations for maintaining urban operation. The rapid development of the city has brought tremendous pressure on the traffic, and the congestion of urban traffic has restricted the healthy development of the city. Therefore, how to improve the urban transportation network model and improve transportation and transportation has become an urgent problem to be solved in urban development. Specific patterns hidden in large-scale crowd movements can be studied through transportation networks such as subway networks to explore urban subway transportation modes to support corresponding decisions in urban planning, transportation planning, public health, social networks, and so on. Research on urban subway traffic patterns is crucial. At the same time, a correct understanding of the behavior patterns and laws of residents’ travel is a key factor in solving urban traffic problems. Therefore, this paper takes the metro operation big data as the background, takes the passenger travel behavior in the urban subway transportation system as the research object, uses the behavior entropy to measure the human behavior, and actively explores the urban subway traffic mode based on the metro passenger behavior entropy in the context of big data. At the same time, the congestion degree of the subway station is analyzed, and the redundancy time optimization model of the subway train stop is established to improve the efficiency of the subway operation, so as to provide important and objective data and theoretical support for the traveler, planner and decision maker. Compared to the operation graph without redundant time, the total travel time optimization effect of passengers is 7.74%, and the waiting time optimization effect of passengers is 6.583%.


SIMULATION ◽  
2018 ◽  
Vol 95 (3) ◽  
pp. 271-285 ◽  
Author(s):  
Guangyu Zou ◽  
Levent Yilmaz

This paper presents a self-organizing model to design effective traffic signaling strategies in order to reduce traffic congestion in urban areas. The proposed traffic signaling system is based on a pattern model of self-organization, i.e., digital infochemicals (DIs), which are analogous to chemical substances that convey information between interactive elements mediated via the environment. In the context of traffic systems, the DIs refer to information generated by vehicles and dissipated by the urban transportation infrastructure. Based on the exploratory analysis with one single intersection, we demonstrate that the DI-based strategy performs significantly better than both the fixed and trigger-based scheduling strategies in terms of queue length and waiting time under both fixed and dynamic traffic demands.


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