Road pricing: An international perspective

This paper reviews experience with road pricing in Europe and Asia. It considers the objectives of road pricing, and demonstrates that differences in objectives lead to differences in scheme design and performance. It reviews the criteria for design of road pricing systems, and the development of charging structures and technologies to meet those criteria. In particular it discusses the relative merits of pre-determined and congestion-dependent charging structures, and of off-vehicle and on-vehicle charging systems. It assesses the performance of road pricing systems to date, discusses objections to road pricing and demonstrates that the role of road pricing within a wider transport strategy and the use made of the revenue generated, will be important determinants of public acceptability. Finally it assesses the relative merits of alternative approaches to implementation and argues that these will need to pay as much regard to public acceptability as to technical performance.     

Clockwise hysteresis loops in the Macroscopic Fundamental Diagram: An effect of network instability

A recent study reported that the Macroscopic Fundamental Diagram of a medium size city exhibited a clockwise hysteresis loop on a day in which a major disturbance caused many drivers to use unfamiliar routes. It is shown below that, even in a perfectly symmetric network with uniform demand, clockwise loops are to be expected when there are disturbances, especially if the disturbances cause a significant fraction of the drivers to not change routes adaptively. It is also shown that when drivers are not adaptive networks are inherently more unstable as they recover from congestion than as they are loaded. In other words, during recovery congestion tends more strongly toward unevenness because very congested areas clear more slowly than less congested areas. Since it is known that uneven congestion distributions reduce network flows, it follows that lower network flows should arise during recovery, resulting in clockwise loops. Fortunately, the presence of a sufficient number of drivers that choose routes adaptively to avoid congested areas helps to even out congestion during recovery, increasing flow. Thus, clockwise loops are less likely to occur when driver adaptivity is high.     

Distributional impacts of road pricing: The truth behind the myth

This paper shows that road pricing can be regressive, progressive or neutral, and refutes the generalised idea that road pricing is always regressive. The potential distributional impacts of a road pricing scheme are assessed in three English towns. It is found that impacts are town specific and depend on where people live, where people work and what mode of transport they use to go to work. Initial impacts may be progressive even before any compensation scheme for losers is taken into account. When the situation before the scheme is implemented is such that majority of drivers entering the area where the scheme would operate come from households with incomes above the average, it can be expected that, once the scheme is implemented, these drivers coming from rich households will continue to cross the cordon and will be prepared to pay the charge. In such a case the overall effect will be that on average, rich people will pay the toll and poor people will not.     

A forecast air pollution model applied to a hypothetical urban road pricing scheme: An empirical study in Madrid

Reducing the air pollution from increases in traffic congestion in large cities and their surroundings is an important problem that requires changes in travel behavior. Road pricing is an effective tool for reducing air pollution, as reflected currently urban road pricing outcomes (Singapore, London, Stockholm and Milan). A survey was conducted based on establishing a hypothetical urban road pricing system in Madrid (a random sample size n = 1298). We developed a forecast air pollution model with time series analysis to evaluate the consequences of possible air pollution decreases in Madrid. Results reveal that the hypothetical road pricing for Madrid could have highly significant effects on decreasing air pollution outside of the city and in the inner city during the peak operating time periods of maximum congestion (morning peak hours from 7:00 to 10:00 and evening peak hours from 18:00 to 20:00). Furthermore, this system could have significant positive effects on a shift toward using public transport and non-motorized modes inside the hypothetical toll zone. This reveals that the system has a high capacity to motivate a decrease in air pollution and impose more sustainable behavior for public transport users.     

Airline-driven ground delay programs: A benefits assessment

Three decades of research studies in ground delay program (GDP) decision-making, and air traffic flow management in general, have produced several analytical models and decision support tools to design GDPs with minimum delay costs. Most of these models are centralized, i.e., the central authority almost completely decides the GDP design by optimizing certain centralized objectives. In this paper, we assess the benefits of an airline-driven decentralized approach for designing GDPs. The motivation for an airline-driven approach is the ability to incorporate the inherent differences between airlines when prioritizing, and responding to, different GDP designs. Such differences arise from the airlines’ diverse business objectives and operational characteristics. We develop an integrated platform for simulating flight operations during GDPs, an airline recovery module for mimicking the recovery actions of each individual airline under a GDP, and an algorithm for fast solution of the recovery problems to optimality. While some of the individual analytical components of our framework, model and algorithm share certain similarities with those used by previous researchers, to the best of our knowledge, this paper presents the first comprehensive platform for simulating and optimizing airline operations under a GDP and is the most important technological contribution of this paper. Using this framework, we conduct detailed computational experiments based on actual schedule data at three of the busiest airports in the United States. We choose the recently developed Majority Judgment voting and grading method as our airline-driven decentralized approach for GDP design because of the superior theoretical and practical benefits afforded by this approach as shown by multiple recent studies. The results of our evaluation suggest that adopting this airline-driven approach in designing the GDPs consistently and significantly reduces airport-wide delay costs compared to the state-of-the-research centralized approaches. Moreover, the cost reduction benefits of the resultant airline-driven GDP designs are equitably distributed across different airlines.     

Parking taxes: Effectiveness,legality and implementation,some general considerations

This paper evaluates the pros and cons of implementing parking pricing to reduce auto use and traffic through parking taxes. Taxes on parkers and the providers are evaluated in terms of effectiveness in influencing auto use, operations of the tax, and the legality as well as acceptability of the options. The intent is to help local governments evaluate parking tax approaches.Abbreviation TDM Transportation Demand Management     

Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London

Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.     

Model based urban traffic control,part I: Local model and local model predictive controllers

This paper is the first in a series of reports presenting a framework for the hierarchical design of feedback controllers for traffic lights in urban networks. The goal of the research is to develop an easy to understand methodology for designing model based feedback controllers that use the current state estimate in order to select the next switching times of traffic lights. In this paper we introduce an extension of the cell transmission model that describes with sufficient accuracy the major causes of delay for urban traffic. We show that this model is computationally fast enough such that it can be used in a model predictive controller that decides for each intersection, taking into account the vehicle density as estimated along all links connected to the intersection, what switching time minimizes the local delay for all vehicles over a prediction horizon of a few minutes. The implementation of this local MPC only requires local online measurements and local model information (unlike the coordinated MPC, to be introduced in the next paper in this series, that takes into account interactions between neighbouring intersections). We study the performance of the proposed local MPC via simulation on a simple 4 by 4 Manhattan grid, comparing its delay with an efficiently tuned pretimed control for the traffic lights, and with traffic lights controlled according to the max pressure rule. These simulations show that the proposed local MPC controller achieves a significant reduction in delay for various traffic conditions.     

Bayesian updating of trip generation data: Combining national trip generation rates with local data

With traffic impact analyses and impact fee assessment becoming more popular, the need for accurately estimating the trip generation rate of a proposed development is becoming more important. An overwhelming percentage of state transportation agencies depend either partly or entirely on the ITETrip Generation Report to predict the traffic that will be attracted to and/or produced from a proposed development. However, the rates obtained from the ITE publication have been derived from data collected throughout the United States. They represent a national average and fail to take into account the local trip generation characteristics that the site under consideration might have. This paper establishes a methodology for obtaining more reliable local trip generation rates using Bayesian statistics. In this method, the ITE rates are assumed to be the prior information, which are updated using limited local trip generation data that are available. The method also allows for temporal updating, incorporating subjective judgment and using borrowed data in the updating procedure. Sample calculations in this paper illustrate the developed methodology.     

Model based urban traffic control,part II: Coordinated model predictive controllers

The present paper describes how to use coordination between neighbouring intersections in order to improve the performance of urban traffic controllers. Both the local MPC (LMPC) introduced in the companion paper (Hao et al., 2018) and the coordinated MPC (CMPC) introduced in this paper use the urban cell transmission model (UCTM) (Hao et al., 2018) in order to predict the average delay of vehicles in the upstream links of each intersection, for different scenarios of switching times of the traffic lights at that intersection. The feedback controller selects the next switching times of the traffic light corresponding to the shortest predicted average delay. While the local MPC (Hao et al., 2018) only uses local measurements of traffic in the links connected to the intersection in comparing the performance of different scenarios, the CMPC approach improves the accuracy of the performance predictions by allowing a control agent to exchange information about planned switching times with control agents at all neighbouring intersections. Compared to local MPC the offline information on average flow rates from neighbouring intersections is replaced in coordinated MPC by additional online information on when the neighbouring intersections plan to send vehicles to the intersection under control. To achieve good coordination planned switching times should not change too often, hence a cost for changing planned schedules from one decision time to the next decision time is added to the cost function. In order to improve the stability properties of CMPC a prediction of the sum of squared queue sizes is used whenever some downstream queues of an intersection become too long. Only scenarios that decrease this sum of squares of local queues are considered for possible implementation. This stabilization criterion is shown experimentally to further improve the performance of our controller. In particular it leads to a significant reduction of the queues that build up at the edges of the traffic region under control. We compare via simulation the average delay of vehicles travelling on a simple 4 by 4 Manhattan grid, for traffic lights with pre-timed control, traffic lights using the local MPC controller (Hao et al., 2018), and coordinated MPC (with and without the stabilizing condition). These simulations show that the proposed CMPC achieves a significant reduction in delay for different traffic conditions in comparison to these other strategies.     

Automated tuning of ITS management and control systems: Results from real-life experiments

The design and deployment of the majority of Management and Control Systems (MCS) for ITS involves a tedious, effort- and time-consuming manual tuning and calibration procedure not only during the initial design and deployment of the ITS but, in most cases, during its whole lifetime. Recently, we have developed and evaluated, both by means of theoretical analysis and extensive simulation experiments, a new methodology which fully automatically takes over the manual tuning and calibration procedure. Most importantly, this new methodology, called Adaptive Fine-Tuning (AFT), achieves to improve the performance of the system and compensate the effect of the continuous changes of its behavior that may be due to either internal or external factors. In this paper, we report results of implementing AFT to a real-life ITS MCS. More precisely, this paper reports and analyzes the results from implementing AFT to an urban traffic signal control application. The results from AFT real-life application demonstrate that it is capable of significantly improving the performance of the system in a safe and robust manner. Moreover, the real-life results exhibit the capability of AFT to efficiently adapt and compensate in cases of changes in the system behavior, even if these changes are significant.     

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.     

Optimization of traffic demand management policy in China: towards a sustainable mode split

The rapid increase in private car use in large metropolitan areas has led to irrational travel mode splits and severe traffic problems. Traffic demand management (TDM) is an effective policy to achieve a more sustainable development of traffic systems. This study analyzes the relationships between TDM policy, mode split, and travel mode choice using Stackelberg game theory. Then, using 0–1 programming, it establishes a combination of TDM policy instruments that can achieve a more sustainable mode split in a city and provides a case study in China. The method presented in this research has strong theoretical implications for TDM policymakers.     

Influence of avenue trees on traffic pollutant dispersion in asymmetric street canyons: Numerical modeling with empirical analysis

The dispersion of traffic-related pollutants in urban street canyons is of importance for the health and quality of lives. To reveal the inherent principle, researchers have performed a lot of investigations; many dispersion phenomena have also been assessed during recent years. However, the presence of avenue trees in street canyons and their capacity for pollutant dispersion remains partly addressed. In this study, we investigated the effects of avenue trees in urban street canyons on traffic pollutant dispersion. The dispersion of CO concentration in asymmetric street canyons was simulated under varied situations. The computational results showed a good agreement with the experimental data, and the numerical model was validated to be adequate for investigating the pollutant dispersion in street canyons. Then, the numerical simulations were extended to explore the impacts of the effects of avenue trees on CO dispersion; the results indicated that avenue trees generally increase CO concentrations in asymmetric street canyons. When the wind direction is perpendicular to the street axis, a terraced building raises pollutant concentrations at the windward wall and reduces concentration at the leeward wall on the pedestrian levels. Findings of this study are expected to provide significant insight into urban road design and strategy making for avenue tree planting, particularly under the existing worldwide sustainable low-carbon urban development.     

Managing transportation during highway reconstruction: A recommended process

Major highway reconstruction can cause significant disruptions to existing travel patterns and economic activity. Reducing these impacts on travelers, shippers, businesses and residents requires that innovative and effective transportation management actions be developed and implemented. This paper reports the major findings and recommendations of a research study on managing transportation during highway, reconstruction. The primary objectives of the study were