Understanding public response to a congestion charge: A random-effects ordered logit approach

Public acceptance is consistently listed as having an enormous impact on the implementation and success of a congestion charge scheme. This paper investigates public acceptance of such a scheme in Australia. Surveys were conducted in Brisbane and Melbourne, the two fastest growing Australian cities. Using an ordered logit modeling approach, the survey data including stated preferences were analyzed to pinpoint the important factors influencing people’s attitudes to a congestion charge and, in turn, to their transport mode choices. To accommodate the nature of, and to account for the resulting heterogeneity of the panel data, random effects were considered in the models. As expected, this study found that the amount of the congestion charge and the financial benefits of implementing it have a significant influence on respondents’ support for the charge and on the likelihood of their taking a bus to city areas. However, respondents’ current primary transport mode for travelling to the city areas has a more pronounced impact. Meanwhile, respondents’ perceptions of the congestion charge’s role in protecting the environment by reducing vehicle emissions, and of the extent to which the charge would mean that they travelled less frequently to the city for shopping or entertainment, also have a significant impact on their level of support for its implementation. We also found and explained notable differences across two cities. Finally, findings from this study have been fully discussed in relation to the literature.     

Variable guidance for pedestrian evacuation considering congestion,hazard, and compliance behavior

A methodology for optimizing variable pedestrian evacuation guidance in buildings with convex polygonal interior spaces is proposed. The optimization of variable guidance is a bi-level problem. The calculation of variable guidance based on the prediction of congestion and hazards is the upper-level problem. The prediction of congestion provided the variable guidance is the lower-level problem. A local search procedure is developed to solve the problem. The proposed methodology has three major contributions. First, a logistic regression model for guidance compliance behavior is calibrated using a virtual reality experiment and the critical factors for the behavior are identified. Second, the guidance compliance and following behaviors are considered in the lower-level problem. Third, benchmarks are calculated to evaluate the performance of optimized variable guidance, including the lower bound of the maximum evacuation time and the maximum evacuation time under a fixed guidance. Finally, the proposed methodology is validated with numerical examples. Results show that the method has the potential to reduce evacuation time in emergencies.     

Sensor location problems in path-differentiated congestion pricing

Path-differentiated congestion pricing is a tolling scheme that imposes tolls on paths instead of individual links. One way to implement this scheme is to deploy automated vehicle identification sensors, such as toll tag readers or license plate scanners, on roads in a network. These sensors collect vehicles’ location information to identify their paths and charge them accordingly. In this paper, we investigate how to optimally locate these sensors for the purpose of implementing path-differentiated pricing. We consider three relevant problems. The first is to locate a minimum number of sensors to implement a given path-differentiated scheme. The second is to design an optimal path-differentiated pricing scheme for a given set of sensors. The last problem is to find a path differentiated scheme to induce a given target link-flow distribution while requiring a minimum number of sensors.     

Factors driving public support for road congestion reduction policies: Congestion charging,free public transport and more roads in Stockholm,Helsinki and Lyon

Based on an across-the-board survey conducted among residents of Stockholm, Helsinki and Lyon, we explore the opinions on three policy measures to combat road congestion: congestion charging, free public transport and building more roads. The support for the two latter policies is substantially higher than the support for congestion charging, which is only supported by a majority in Stockholm. Self-interest is important for the formation of the opinion to all three policies. However, fundamental values and general political views, indicated by four attitudinal factors, are even more important in forming opinions towards the three transport policies. Of all attitudinal factors, the one indicating environmental concern most influences the support for all policies. Equity concerns, however, increase the support for free public transport and opposition to taxation increases the support for building more roads.Our results further suggest that the opinions towards free public transport and building more roads can be mapped along the left–right political axis, where Environment and Equity are to the left and Pricing and Taxation are to the right. However, the opinion towards congestion charging cuts right through the political spectrum. The impact of the fundamental values and self-interest variables are similar for Stockholm and Helsinki, indicating that even if experience increases the overall support for charging, it does not change the relative strength of different political arguments to any major extent.     

A novel peer-to-peer congestion pricing marketplace enabled by vehicle-automation

This paper proposes a novel concept of congestion pricing based on voluntary peer-to-peer exchange of money between motorists in exchange for one ceding priority to another in a traffic stream. While in the classical congestion charging paradigm payments are compulsory and flow only towards the system operator, in the proposed marketplace participation is voluntary and motorists directly compensate each other. A particular motorist may find that he/she is a ‘payer’ at certain points in a given journey and a ‘payee’ at others.Humans would not be expected to successfully seek, negotiate and execute a continuous series of peer-to-peer trades involving micro-payments while also handling the cognitively-demanding task of driving; real-world implementation will therefore require vehicles operating under fully-automated control in both the longitudinal and lateral dimensions during the time periods that they seek and engage in trades. The automated vehicle control algorithms must be sufficiently intelligent and adaptable to enable alternative maneuvers on short timescales, given the inherent uncertainty of whether or not a potential trade will in fact be executed. The peer-to-peer trading would be executed algorithmically, subject to strategic-level guidance given by a vehicle’s occupant(s) regarding the occupant’s relative valuation of money and priority in the traffic stream.In this paper we detail the prospective marketplace and present a simple simulation model to expose its properties. We show that the proposed peer-to-peer marketplace could lead to both desirable and undesirable outcomes; which of these would be predominant is a matter requiring empirical study. The paper concludes with a discussion of further research needs to refine and develop these concepts into practice.     

Congestion pricing for Latin America: Prospects and constraints

In an effort to reduce the adverse impacts of the car and promote sustainable transport in Latin America, some governments have either implemented travel demand management policies or have considered ways of directly reducing the number of vehicles in congested areas. While demand management measures have been promoted in a small number of countries, including vehicular restrictions as well as the promotion of public transport modes, there are currently no congestion pricing programmes in operation in Latin America. This paper begins with an overview of travel demand management, including its principal aims as well as its primary objectives within the Latin American context. It discusses past efforts to promote traffic restraint and perspectives for developing congestion pricing schemes in both São Paulo and Santiago. Finally, it examines the potential role of congestion pricing as a demand management tool. While it is one of the most effective demand management measures in the industrialised world, a number of barriers currently prevent it from being widely adopted in Latin America.     

交通拥挤收费原理与对策研究

交通拥挤收费(Congestion Pricing)作为现代化城市交通需求管理(TDM)的有效措施之一,虽然在实践中颇多微词,但是其在减少交通吸引、控制交通流量、提高车速与路段通行能力、提高能源利用效率及提高路网的运行效率等方面效果显著,并且在缓解交通拥堵压力的同时带来了财政副收入。从经济学原理出发,利用边际成本定价理论、收入再分配理论以及公共产品和产权经济学理论分析了交通拥挤收费的本质、理论依据,最后提出交通拥挤收费的相关建议和措施。     

基于V-支持向量分类机的交通事件检测方法研究

基于支持向量机在解决分类问题的优势，本文提出基于V-支持向量分类机的交通事件检测方法。首先把交通事件是否发生看成是一个特殊的分类问题，选取V-支持向量分类机和核函数，根据以往的交通事件是否发生的检测数据，即分别在发生交通事件和不发生交通事件两种情况下的上下游车道占有率，计算出其当前时段的上下游车道占有率的绝对差、相对差，以及下游前两时段与当前时段车道占有率的相对差，以此作为V-支持向量分类机的输入，对其进行训练，然后输入现阶段检测到的相应车道占有率统计结果，利用训练完成的V-支持向量分类机来判别是否发生交通事件。最后，本文以微观交通模拟的数据验证模型的效果。     

城市交通拥挤的社会成本分析初探

交通拥挤的社会成本可分为生产成本、使用成本、时间耗费成本及外部成本,本文在定性分析的基础上,对使用成本和时间耗费成本做了定量分析,给出了计算公式,并通过对大连市西南路某路段在拥挤时段的调查,计算出了居民出行时间成本的损失和城市交通使用成本的损失,这一结果可以推广到整条道路或区域路网,从而为城市交通的良性发展和减少经济损失等方面提供了有效的理论依据。     

Labour market effects in assessing the costs and benefits of road pricing

Traffic congestion and the policies used to combat it have been studied extensively. One area which has received less attention is the secondary impacts of such policies. This paper uses a micro-simulation framework to study the effect on labour markets of road pricing. The key benefit of our chosen methodology is that it allows a simultaneous consideration of both commuting and migration decisions. We show that while welfare gains can be achieved through optimal charging, this may come at the price of decreased integration. This may manifest through either greater centralisation tendencies in population, or through unemployment disparities between regions.