计重收费模式下车辆逃费的主要方式及治理对策

计重收费是以收费站现场实际测量的车货总重为依据,对载货类机动车辆计重收取通行费的征收方式。文章对计重收费模式下货运车辆偷逃通行费的主要方式及特点进行了分析,阐述了当前车辆逃费治理工作中存在的困难及建议,提出了治理计重收费模式下货运车辆偷逃通行费的对策。     

浅议计重收费模式下治理车辆超限超载的对策与思考

对我省计重收费与治超现状、计重收费对治理超限超载的影响进行了阐述,并提出处理好计重收费与治理超限超载的关系及对策。     

公路建设

3月15日零时30分起,昆石高速公路开始全面实行载货类汽车计重收费。据悉,昆石高速公路计重收费历经三年的研究论证、社会听证后,于今年2月10日才正式得到云南省政府的批复。昆石高速公路实施计重收费后将有效控制超限超载车辆,更好地维护旅游大通道的安全、畅通。     

论实施计重收费后超限运输治理的开展

计重收费是对原公路货运收费模式的一种改善,但其不能完全遏制和消除超限运输行为.严重超限运输对公路造成的隐性破坏,不但威胁公路桥梁的安全,而且损害公路经营者的利益.文章提出应利用科技化手段,结合计重收费的数据信息,深入开展超限运输治理.     

高速公路计重收费系统研究

计重收费不仅是高速公路还贷的主要收入,而且是控制高速公路超重超载现象的最有效方式,但目前计重收费主要采用依赖人工的半自动收费方式,效率低下。为此,从传统的计重收费系统的调查研究出发,提出了不停车计重收费(ETC)系统。该系统成功完成动态称重、缴费,实现收费站与车辆之间的无线通信,完成车辆的识别及收费工作,在我国具有广阔的发展前景。     

浅析青海省高速公路计重收费的现状、问题与对策

随着高速公路计重收费车道的不断增加,计重收费设备的大量应用,计重收费在政策、技术、产品、管理等方面也出现了一些问题,制约着计重收费的发展,如何应对这些问题,促进计重收费不断完善和发展,是值得探讨的问题.     

综合

陕西高速公路全面实行货车计重收费经陕西省政府批准，省交通运输厅、省财政厅、省物价局联合下发通告，5月10日10时（联网收费公路为出口时间）起，陕西省高速公路取消按货车车型收费，对所有载货类机动车辆全面实施计重收费。目前，     

实行计重收费后交通量变化的原因与对策

文章针对广西高速公路实行计重收费后交通量、通行费收入的变化情况,分析了高速公路通行费收入变化的特点与原因,提出了应对高速公路交通量流失的对策和方法。     

青海省实施计重收费的回顾

从车型收费到计重收费,不仅仅是收费模式的简单转变,从管理上带来的变化无疑是巨大的.就青海省在计重收费过程中的一些具体做法,针对出现的问题所采取的措施和对策,以及实际工作中的体会作一介绍.     

高速公路计重收费发展趋势

为了有效地避免高速公路超载现象的产生,必须对货车进行集中计重收费。鉴于此,介绍了计重收费生的背景和现状以及计重收费的概念,重点阐述了高速公路计重收费的发展趋势。     

Behavioural responses to vehicle emissions charging

Road pricing as an economic construct is not a new phenomenon in transportation research. Whilst fuel taxation and tolling of roads are common ways of raising revenue in many countries, these initiatives are primarily aimed at road infrastructure financing. Worldwide there has been growing interest in pricing structures designed to also manage the growing levels of traffic congestion and, in recent times, an increasing focus on generating reductions in carbon emissions from vehicle ownership and use. This paper presents a stated choice experiment undertaken in response to the increasing interest in the environmental externalities of travel behaviour. The aim of this choice experiment is to identify the potential to switch to more fuel efficient cars that emit lower emissions, under differing pricing and technology scenarios. Results indicate that annual and variable emissions surcharges targeted very specifically to vehicle emission rates have a noticeable role in modifying vehicle purchasing decisions.     

Time-dependent congestion pricing system for large networks: Integrating departure time choice,dynamic traffic assignment and regional travel surveys in the Greater Toronto Area

Congestion pricing is one of the widely contemplated methods to manage traffic congestion. The purpose of congestion pricing is to manage traffic demand generation and supply allocation by charging fees (i.e., tolling) for the use of certain roads in order to distribute traffic demand more evenly over time and space. This study presents a framework for large-scale variable congestion pricing policy determination and evaluation. The proposed framework integrates departure time choice and route choice models within a regional dynamic traffic assignment (DTA) simulation environment. The framework addresses the impact of tolling on: (1) road traffic congestion (supply side), and (2) travelers’ choice dimensions including departure time and route choices (demand side). The framework is applied to a simulation-based case study of tolling a major freeway in Toronto while capturing the regional effects across the Greater Toronto Area (GTA). The models are developed and calibrated using regional household travel survey data that reflect the heterogeneity of travelers’ attributes. The DTA model is calibrated using actual traffic counts from the Ontario Ministry of Transportation and the City of Toronto. The case study examined two tolling scenarios: flat and variable tolling. The results indicate that: (1) more benefits are attained from variable pricing, that mirrors temporal congestion patterns, due to departure time rescheduling as opposed to predominantly re-routing only in the case of flat tolling, (2) widespread spatial and temporal re-distributions of traffic demand are observed across the regional network in response to tolling a significant, yet relatively short, expressway serving Downtown Toronto, and (3) flat tolling causes major and counterproductive rerouting patterns during peak hours, which was observed to block access to the tolled facility itself.     

Auction-based tolling systems in a connected and automated vehicles environment: Public opinion and implications for toll revenue and capacity utilization

Autonomous and connected vehicles are expected to enable new tolling mechanisms, such as auction-based tolls, for allocating the limited roadway capacity. This research examines the public perception of futuristic auction-based tolling systems, with a focus on the public acceptance of such systems over current tolling practices on highways (e.g., dynamic and fixed tolling methodologies). Through a stated-preference survey, responses from 159 road-users residing in Virginia are elicited to understand route choice behavior under a descending price auction implemented on a hypothetical two-route network. Analysis of the survey data shows that there is no outright rejection of the presented auction-based tolling among those who are familiar with the current tolling methods. While males strongly support the new method, no clear pattern emerges among other demographic variables such as income and education level, and age. While high income respondents and regular commuters are more likely to pay higher tolls, no statistical significance between different genders, age groups, household sizes, and education levels is found. Based on the modeling results and the hypothetical road network, it is found that descending price tolling method yields higher average toll rates, and generates at least 70% more revenue when travel time saving is 30 min, and improves capacity utilization of the toll road significantly compared to fixed tolls.     

广西高速公路电子不停车收费ETC系统的应用研究

电子不停车收费技术是一种先进的电子收费技术方式,文章介绍了目前全国电子不停车收费技术的研究及应用情况,并针对广西的实际,提出了具体的研究内容及实施方案,为电子不停车技术在广西的应用提供依据。     

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.     

Congestion tolling in the bottleneck model with heterogeneous values of time

When analysing the effects of transport policies it is important to adequately control for heterogeneity: previous studies note that ignoring heterogeneity biases the estimated welfare effects of tolling. This paper examines the effects of tolling, in a bottleneck model, with a continuously distributed value of time. With homogeneous users, first-best public tolling has no effect on prices. With heterogeneity it does: low values of time lose, and high values of time gain. The average congestion externality decreases with the heterogeneity in the value of time. Consequently, the welfare gain of first-best tolling also decreases. The more heterogeneous the value of time is, the lower the relative efficiency of a public pay-lane. This finding contrasts with the previous literature. Earlier studies, using static flow congestion, conclude that the relative efficiency increases with this type of heterogeneity. With more heterogeneity in the value of time, the relative efficiency of a private pay-lane is also lower, while that of a public time-invariant toll is higher. Our results suggest that the welfare gains of different tolling schemes are affected differently by heterogeneity. Further, the impact of heterogeneity on the effects of a policy also depends on the type of congestion considered.     

远程控制在公路收费系统中的应用

近年来,广西壮族自治区高速公路发展迅速,通车里程已达1400多公里,并且全部实现了电脑联网"一卡通"收费。随着收费站点的增多,收费终端计算机已经快达到600台,收费系统的升级和日常维护工作日显突出。文章介绍了远程控制技术在广西高速公路收费系统中的应用情况。     

Step-tolling with price-sensitive demand: Why more steps in the toll make the consumer better off

Most dynamic models of congestion pricing use fully time-variant tolls. However, in practice, tolls are uniform over the day, or at most have just a few steps. Such uniform and step tolls have received surprisingly little attention from the literature. Moreover, most models that do study them assume that demand is insensitive to the price. This seems an empirically questionable assumption that, as this paper finds, strongly affects the implications of step tolling for the consumer. In the bottleneck model, first-best tolling has no effect on the generalised price, and thus consumer surplus remains the same as without tolling. Conversely, under price-sensitive demand, step tolling increases the price, making the consumer worse off. The more steps the toll has, the closer it approximates the first-best toll, thereby increasing the welfare gain and making consumers better off. This indicates the importance for real-world tolls to have as many steps as possible: this not only raises welfare, but may also increase the political acceptability of the scheme by making consumers better off.     

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.     

Accurate and cost-effective traffic information acquisition using adaptive sampling: Centralized and V2V schemes

The new generation of GPS-based tolling systems allow for a much higher degree of road sensing than has been available up to now. We propose an adaptive sampling scheme to collect accurate real-time traffic information from large-scale implementations of on-board GPS-based devices over a road network. The goal of the system is to minimize the transmission costs over all vehicles while satisfying requirements in the accuracy and timeliness of the traffic information obtained. The system is designed to make use of cellular communication as well as leveraging additional technologies such as roadside units equipped with WiFi and vehicle-to-vehicle (V2V) dedicated short-range communications (DSRC). As opposed to fixed sampling schemes, which transmit at regular intervals, the sampling policy we propose is adaptive to the road network and the importance of the links that the vehicle traverses. Since cellular communications are costly, in the basic centralized scheme, the vehicle is not aware of the road conditions on the network. We extend the scheme to handle non-cellular communications via roadside units and vehicle-to-vehicle (V2V) communication. Under a general traffic model, we prove that our scheme always outperforms the baseline scheme in terms of transmission cost while satisfying accuracy and real-time requirements. Our analytical results are further supported via simulations based on actual road networks for both the centralized and V2V settings.