Edinburgh's Congestion Charging Plans: An Analysis of Reasons for Non-Implementation

Abstract

The City of Edinburgh in Scotland in the UK had advanced plans for a congestion charging scheme until 25 February 2005. However, these plans were abandoned at that time after a referendum that resulted in a ‘no vote’. This paper explains the origins of the scheme, outlines its nature, extent, charging technology and predicted effect; it also analyses the difficulties that exist when attempting to plan and implement such a scheme in a particular governance context, and when there is little unanimity of public opinion about the need for a scheme.

As well as the primary documentation from the proposals (e.g. public inquiry submissions, papers to government), the paper also draws upon a series of face-to-face interviews that were undertaken with key stakeholders. It also provides an analysis of press coverage in the local (Edinburgh) and national (Scottish) newspapers in the run-up to the referendum. These sources explain both the systemic and more local barriers to the scheme's implementation.

The paper draws key lessons which are important for authorities considering the implementation of a road user charging scheme, by suggesting how legislative and governance barriers to implementation can be reduced. The lessons are of relevance world wide.     

Historic vehicles: an overview from a transport policy perspective

Historic vehicles (HVs) are the heritage of road transport that have surprisingly received little attention in the academic literature. This study presents an overview of the literature on HVs, focusing on the three topics that dominate the policy debate on transport: environmental, safety and congestion impacts. We observed that polluting emissions of HVs are per kilometre much higher (often a factor 5 or more) than those of moderns vehicles. The annual average mileage per vehicle per year of HVs is much lower than other vehicles. The lower active and passive safety levels of HVs are compensated by the way these vehicles are driven, resulting in the risk factors per kilometre being roughly equal or lower than other vehicles. The contribution of HVs to congestion is negligible. However, the transport policy discourse is divided on the topic of HVs. More comprehensive and effective laws and regulation are needed to protect this aspect of the heritage of road transport whilst concurrently avoiding or limiting the problems caused by them.     

Direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem

This paper proposes simple and direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem. It is only necessary to account for random variables independent of link flows by performing a simple transformation of the perceived link travel time with a normal distribution. At every iteration of a Monte-Carlo simulation procedure, the values of the random variables are sampled based on their probability distributions, and then a regular deterministic user equilibrium assignment is carried out to produce link flows. The link flows produced at each iteration of the Monte-Carlo simulation are averaged to yield the final flow pattern. Two test networks demonstrate that the proposed algorithms and the traditional algorithm (the Method of Successive Averages) produce similar results and that the proposed algorithms can be extended to the computation of the case in which the random error term depends on measured travel time.     

An improved cellular automaton with axis information for microscopic traffic simulation

Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells’ states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

Tradable network permits: A new scheme for the most efficient use of network capacity

Akamatsu et al. (2006) proposed a new transportation demand management scheme called “tradable bottleneck permits” (TBP), and proved its efficiency properties for a single bottleneck model. This paper explores the properties of a TBP system for general networks. An equilibrium model is first constructed to describe the states under the TBP system with a single OD pair. It is proved that equilibrium resource allocation is efficient in the sense that the total transportation cost in a network is minimized. It is also shown that the “self-financing principle” holds for the TBP system. Furthermore, theoretical relationships between TBP and congestion pricing (CP) are discussed. It is demonstrated that TBP has definite advantages over CP when demand information is not perfect, whereas both TBP and CP are equivalent for the perfect information case. Finally, it is shown that the efficiency result also holds for more general demand conditions.     

Closed-form multiclass cell transmission model enhanced with overtaking,lane-changing,and first-in first-out properties

A novel multiclass macroscopic model is proposed in this article. In order to enhance first-in, first-out property (FIFO) and transmission function in the multiclass traffic modeling, a new multiclass cell transmission model with FIFO property (herein called FM-CTM) is extended from its prior multiclass cell transmission model (M-CTM). Also, to enhance its analytical compactness and resultant computational convenience, FM-CTM is formulated in this paper as a set of closed-form matrix equations. The objective is to improve the accuracy of traffic state estimation by enforcing FIFO property when a fast vehicle cannot overtake a slow vehicle due to a limitation of a single-lane road. Moreover, the proposed model takes into account a different priority for vehicles of each class to move forward through congested road conditions, and that makes the flow calculation independent from their free-flow speeds. Some hypothetical and real-world freeway networks with a constant or varying number of lanes are selected to verify FM-CTM by comparing with M-CTM and the conventional CTM. Observed densities of VISSIM and real-world dataset of I-80 are selected to compare with the simulated densities from the three CTMs. The numerical results show that FM-CTM outperforms the other two models by 15% of accuracy measures in most cases. Therefore, the proposed model is expected to be well applicable to the road network with a mixed traffic and varying number of lanes.     

驾驶过程中手机使用行为数据采集及分析

驾驶过程中使用手机的行为存在安全隐患,是当今导致交通安全事故的原因之一.文章借助于信息技术开发出采集使用手机行为数据的App,从真实数据出发,客观地分析驾驶员在开车过程中使用手机这一不良驾驶行为的覆盖程度及危险程度,并提出将手机使用行为作为驾驶风险评价因子.     

面向常发拥堵点的主动交通诱导方法

基于动态用户均衡、系统最优分配的诱导方法,侧重路网需求的宏观预测和调节,难以准确辨识道路拥堵点的关联车流,制约了诱导效果。为精准调控致堵车流,有效缓解常发性拥堵,研究基于需求溯源的主动交通诱导方法。遵循靶向诱导的思路,分析车辆行驶轨迹和常发拥堵点的交通流关联性,运用卡尔曼滤波对关联车流进行短时预测,在此基础上,结合流量占比、路径饱和度等指标,对诱导目标车流进行优选。同时,从负荷均衡的角度出发,基于路段与路径交通流的时空关联更新路网交通状态,建立以饱和度均衡为目标的主动诱导优化模型。仿真结果表明：相比反应型诱导与基于路径偏好的主动型诱导,所提方法使常发拥堵点的车均延误、停车次数等下降30%~60%,路网车均延误、停车次数等下降10%~15%,模型收敛速度提高,交通效益提升,验证了该方法的有效性。

     

网络条件下高速公路收费费率优化方法研究

以区域公路网为研究对象,在分析高速公路收费费率与交通量之间关系的基础上,建立收费费率优化双层规划模型,兼顾经营者和使用者的利益,并考虑路网交通流分布,设计了模型的实用求解算法。该方法弥补了已有方法多以运输通道为研究对象的不足之处,可以在收费系数确定的情况下根据优化目标直接得到优化结果,具有较为广泛的适用性。