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With ongoing urbanization, traffic congestion and the air pollution it induces are worsening. Using a system dynamics (SD) approach, this study constructed a driving-restriction policy model to explore the effects of different stages of policy implementation on variables such as traffic congestion, emissions, and parking demand. Medium- and long-term dynamic simulation showed that the effect of the policy was obvious in the initial stage but gradually weakened in the medium term, leading to a "fading" effect on traffic-congestion alleviation; a "rebound" effect was even observed at the end of the simulation. Thus, the policy will not effectively reduce traffic congestion in the long term and will induce a new demand for car purchases, resulting in paradoxical effects, which will aggravate parking demand, congestion, and pollution. Yet, it was also found that introducing penalty policies and an air pollution charging fee could weaken the paradoxical effects and compensate for some defects of the policy. Such strategies could help reduce emissions, traffic congestion, parking demand, the number of illegal trips, and the overall number of vehicle trips. These findings can provide not only a theoretical basis for further research but also practical guidance for policy improvement. [ABSTRACT FROM AUTHOR]

As a market-based instrument of transportation demand management, congestion charge can not only effectively reduce traffic congestion, but also improve air quality. However, due to its low public acceptability, this policy only has a few urban practices. As one of the fast-growing metropolises in emerging economies that are facing both traffic congestion and industrial pollution problems, Beijing is now considering the feasibility of implementing congestion charging. Some researchers address that though people with strong environmental concerns are more prone to support congestion charges, the associations between environmental concerns and support for congestion charges are context-dependent. A survey was conducted in Beijing in 2016 to understand how the pollution context in cities of emerging economies affects these associations. We find that the acceptability in Beijing is 33%, and expected policy effects and environmental concerns are the most important impact factors. Due to the influence of the regional industrial pollution context, most residents in Beijing do not consider congestion charge to be an effective way to tackle air pollution. Under these circumstances, even if the public environmental concerns, in general, are high and congestion charges are "marketed" as environmental policies, there is no guarantee that policy support will rise. [ABSTRACT FROM AUTHOR]

• The effectiveness of existing traffic measures in Beijing is investigated. • A survey on drivers' opinions and attitudes towards the traffic situation is given. • Most respondents think congestion is still serious in Beijing. • The perceived impact of congestion on personal car use is relatively low. • The symbolic meaning of personal cars has large impact on willingness to change. Facing serious challenges of traffic congestion and air pollution, Beijing has implemented a series of traffic polices. In this paper, we first investigate the effectiveness of existing traffic measures in Beijing and analyse the underlying factors from the perspective of drivers, which provide insights for the traffic regulations in other cities worldwide. While the car ownership restriction has effectively limited the total number of vehicle in Beijing, the effect of the car use restriction only lasts for a short period. A survey on drivers' opinions and attitudes towards the traffic situation and a potential measure, i.e., tradable driving credit (TDC), is conducted. Although traffic data shows that congestion improved and traffic was slightly congested in recent years in Beijing, most respondents believe congestion is still serious in Beijing. However, they think the impact of traffic congestion on their personal car use is relatively low, which could partly explain why so many travellers still depend on driving given the relative convenient transit facilities in Beijing. In addition, a large proportion of respondents treat personal cars as a representation of social status and think driving bring them pleasures, which indicates that it may be hard to further decrease the share of car trips in Beijing. According to their attitudes and social-economical characters, respondents' willingness on their changes of travel behaviours under TDC is investigated. The results show that individuals' social-economic characters such as income level, education and family size and the symbolic meaning of personal cars have significant influence on respondents' willingness to switch to other transport modes. [ABSTRACT FROM AUTHOR]

On the basis of analyzing connotation of congestion pricing, through the qualitative analysis of the main content and implementation effect of the congestion policy in cities such as Singapore, London and Stockholm, the basic conditions for urban congestion charges were summarized. Compared with Beijing's urban development, traffic development status, urban transport infrastructure and social factors, the current policy of traffic congestion charging is still not available from the perspective of the current status of car ownership in Beijing, residents' travel composition, and population density distribution. [ABSTRACT FROM AUTHOR]

Urban public transport is a very essential mode for urban residents' commute travel; however, the unbalanced spatial and temporal distribution of travel demand usually leads to passenger flow congestion risk at certain section and time. Meanwhile, the risk is short of quantified description. Based on the Pressure-State-Response framework, the study puts forward three bus passenger flow congestion risk evaluation indexes including the alternative pressure, the congestion intensity, and the transport efficiency. Then, the evaluation model is proposed based on the entropy method, and the risk is divided into four levels by K -means clustering. The article considers the 3rd Ring Road corridor in Beijing as a case to identify the risk level. The results show that the risk in the peak hours of weekdays is generally about 1.5 times higher than the risk in the weekends. The congestion risk is stable in level 3 during the majority time of morning peak hours. The duration intensity of level 4 risk is less than 0.1 during weekdays, indicating that the highest flow congestion can be quickly evacuated in a short time. The integrated passenger risk identification and evaluation model was proposed to identify the passenger flow risk level and induce the network flow distribution more reasonable. The study also provides technical support for ensuring the public transit system safety. [ABSTRACT FROM AUTHOR]

Airport congestion is worsening worldwide, and is one of the bottlenecks constraining the development of global air transportation. Based on a comparison of the current airport congestion models, this paper improves the diffusion approximation model for airport congestion pricing developed by Milan Janic in 2005 in the following three areas: (1) redefining the processes of the congestion queue, (2) adding the threshold of congestion queue, and (3) amending the sub-model of delay costs. This new diffusion approximation model for airport congestion pricing was applied to Beijing Capital International Airport (PEK). After calculating delay times and delay costs at this airport on 21st July, 2007, the congestion tolls for various airlines at various times were calculated. This paper provides a solution for airport congestion. [ABSTRACT FROM AUTHOR]

Alleviating traffic congestion is one of the main challenges for the Internet of Vehicles (IoV) in smart cities. Many congestion pricing systems have been proposed recently. However, most of them focus on punishing the vehicles that use certain roads during peak hours, neglecting the proven fact that rewards can encourage drivers to follow the rules. Therefore, in this paper, we propose a new congestion pricing system based on reward and punishment policies for the IoV in a smart city environment, where the vehicles are rewarded for voluntarily choosing to take an alternative path to alleviate traffic congestion. The proposed system is implemented using vehicular ad hoc networks, which eliminate the need for installing a costly electronic toll collection system. We propose a new virtual currency called T-Coin (traffic coin), that is used to reward the vehicles for their positive attitude. T-Coin is also used in the tender between vehicles to manage the road reservation process. The proposed system uses dynamic pricing to adapt to peak-hour traffic congestion. Using simulated traffic on a real map of Beijing city, we prove the usefulness of T-Coin as a traffic congestion pricing system. [ABSTRACT FROM AUTHOR]

• A SD method is proposed to model the external impact, operation and development of URFT system. • Real-world scenarios of Beijing city are selected to perform long-term simulation. • An urban-scale URFT network can reduce billions of environmental and social losses per year. • Investment policy and system scale affect URFT performance in terms of pricing, income, market share and benefits. Integrating logistics activities into urban passenger rail transit network (URFT) is regarded as an effective approach to promote urban sustainability and reduce the negative externalities of road-based transportation. This study applied a system dynamics method to simulate URFT system development by focusing on internal operations and external impacts. The characteristics of four major stakeholders (i.e., the government, URFT operator, market, and road freight sector) as well as a series of variables affecting system operations, such as metrics of social and environmental externalities, pricing, investment, and subsidies, were incorporated into two submodels. A case study of Beijing, China was provided to demonstrate the historical validity and rationality of simulation results from 2007 to 2035. Three decision variables (i.e., investment policy, network scale and market competitiveness) were combined into eight distinct scenarios to examine the external benefits, pricing strategies, capital funding structure and business volume of URFT. The findings show that URFT schemes with higher funding and capacity lead to greater reductions in the losses of traffic congestion, air pollution, and accidents. Furthermore, both government support in the early stage and regulation mechanisms among price, supply–demand level, and investment play significant roles in improving the system performance. [ABSTRACT FROM AUTHOR]