Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Influence of vehicle type and road category on natural resource consumption in road transport

This study calculates the natural resource use of road transport for different road categories and for different vehicle types. Material inputs per service are determined as the life cycle wide consumption of materials by the road and vehicles, and set against person-kilometres and ton-kilometres transported. If the material input of the infrastructure is allocated to the users according to traffic volume, the material input per service values for abiotic resources and for water are much higher for cars than for bus traffic. The material inputs per service unit for air is significantly lower for buses than for cars. For bicycles, abiotic natural resource consumption is between that for cars and buses, while water consumption is in most instances the highest and air consumption the lowest for the modes studied. The material input per service values for the full trailer are significantly lower than for other goods vehicles. The material inputs per service value for air is significantly higher in the case of vans. If the allocation of road infrastructure use is done by gross vehicle weight, the material input per service values for abiotic resources and water of buses and heavy lorries rise.     

Road Pricing models with maintenance cost

According to the Federal Highway Administration of the United States, maintenance expenditure takes up more than 25% of road revenue disbursement and this percentage has been increasing gradually. The reason for the increment in maintenance cost is that there lacks incentives for road users to take this cost component into their driving behavior. That is, different classes of vehicles should be levied different levels of congestion tax due to the different degrees of damage on the highway if a road pricing policy is implemented. This paper intends to incorporate this concept into road pricing literature by introducing two types of vehicles. After the analysis of the problem, we find that different types of vehicles should be charged different tolls. The toll includes not only the travel delay cost of one's own vehicle and the other types of vehicles, but also the marginal maintenance cost that is dependent on the traffic flow. A set of numerical examples is provided to demonstrate the theoretical analyses. The result shows that both the welfare and cost coverage rate will increase when the road pricing mechanism takes the maintenance cost factor into account.     

Use of hybrid vehicles in Japan: An analysis of used car market data

Despite the rapid market penetration of hybrid vehicles (HVs), their usage and contributions to environmental protection have not been examined by vehicle traveling data. In this paper, we analyzed Japan’s used car market data to understand how HVs are used on the street. We find GV drivers with high travel demand switched from GVs to HVs during the transition period. Despite HV owners driving much longer distances than conventional gasoline vehicle (GV) owners, they emit less carbon dioxide (CO₂) emissions, owing to better fuel economy. We also find that HV owners spend roughly the same amount of money annually as GV owners. However, the per-kilometer travel cost of HVs is much lower than that of GVs even if the depreciation cost of the vehicle and vehicle related taxes are included in the analysis.     

Transport policy for London in 2001 The case for an integrated approach

The paper reports the results of a series of studies conducted to enable the London Planning Advisory Committee to provide advice on strategic transport policy for London. The analytical approach combined the use of an area-based, multi-modal strategic model (LAM) and professional judgment. The performance of LAM as a basis for providing rapid advice on complex issues in transport policy is assessed.The resulting policy advice advocated a coherent approach, involving new infrastructure, particularly for rail; improved management of the road and public transport networks; the use of subsidy to enhance public transport service levels; and road user charges to reduce the impact of private vehicles on congestion and the environment. Road user charges emerged as the pivotal issue in the policy; the paper discusses their role, and the questions which still need to be resolved before they can be implemented.The main message of the study is that no one element of transport policy can tackle London's problems alone; an integrated policy in which infrastructure provision, management and pricing are used to complement one another is shown to be far more effective.     

A conceptualization of vehicle platoons and platoon operations

Vehicle platooning, a coordinated movement strategy, has been proposed to address a range of current transport challenges such as traffic congestion, road safety, energy consumption and pollution. But in order to form platoons in an ad-hoc manner the vehicles have to ‘speak the same language’, which is in current practice limited to vehicles of particular manufacturers. There is no standard language yet. Also in research, while the current literature focuses on platoon control strategies, intra-platoon communication, or platooning impacts on traffic, the conceptualization of platooning objects and their operations remained unattended. This paper aims to fill this fundamental gap by developing a formal model of platooning concepts. The paper proposes an ontological model of platooning objects and properties and abstract basic building blocks of platoon operations that can then be aggregated to complex platooning behavior. The presented ontological model provides the logical reasoning to support vital decision-making during platoon lifecycles. The ontological model is implemented and demonstrated.     

Traffic Noise in Europe: A Comparison of Calculation Methods,Noise Indices and Noise Standards for Road and Railroad Traffic in Europe

The demand for inland freight transport in Europe is mainly met by road transport, leading to unsustainable impacts such as air pollution, greenhouse gas emissions and congestion. Since rail transport has lower externalities than road transport, a modal shift from road to rail is an accepted policy goal for achieving a more sustainable and competitive transport system. However, intermodal road–rail transport is mainly competitive for long-distance transport, and as a consequence, the potential for modal shift is limited. The cost efficiency of road–rail intermodal transport is particularly sensitive to pre- and post-haulage (PPH) costs, since this activity typically has a larger cost compared with its share of the total distance in the transport chain. For intermodal transportation over shorter distances, for example, below 300 km and where there are substantial PPH activities at both ends of the chain, the competitiveness of the intermodal transport system compared with that of direct road is low. Improving the efficiency of PPH activities is, therefore, of utmost importance for the competitiveness of the intermodal transport system. This paper looks into the issue of improving the cost efficiency of an intermodal transport chain by implementing an innovative and flexible legal framework regarding the PPH activities in the chain. By extending the legal framework with exemptions for longer vehicles in PPH, the cost efficiency could be greatly improved. The purpose of such a framework is to allow and enable, for PPH exclusively, the use of 2?×?40 foot or even two semi-trailers using only one vehicle in the context of the Swedish regulatory framework. This paper develops a strategic calculation model for assessing and investigating the consequences of such a framework and investigates the framework's potential in terms of cost efficiency. The model in combination with a sensitivity analysis of input variables gives a comprehensive understanding of the effects of PPH under different circumstances. From the results, it is evident that there are substantial positive effects associated with a PPH framework of longer vehicles. Results indicate that a typical shipper may experience cost reductions of about 5–10% of the total costs of the intermodal transport chain. In summary, a more innovative and flexible legal framework regarding vehicle length in the PPH links can contribute to a greater modal shift, improved cost efficiency and more environmentally friendly transportation systems.     

Road pricing — an outsider's view of American experiences

Abstract

Substantial changes in urban transport policy have taken place over the past decade. The concern with expanding infrastructure and the preoccupation with providing sufficient road capacity to meet the increasing demand of unrestricted car use, which characterized transport policy in the 1950s and 1960s, has gradually given way to the idea that there is a need to restrain motor traffic if urban society is to function efficiently. A variety of restrictive physical traffic management, land use planning and economic policies have, in consequence, been pursued. One option which has attracted considerable attention in the academic literature, but which has been received more cooly by policy‐makers, is the possibility of optimizing urban traffic congestion through the imposition of road pricing. The introduction and relative success of the area licensing scheme in Singapore has added fuel to the arguments of the advocates of such a policy. This review is not directly concerned with either the experiment with road pricing in Singapore nor the theoretical debates which have taken place concerning the potential merits and defects of such policies but rather looks at the applied work in the United States which has looked into the practical implications of road pricing for its cities. Further, it seeks to explore, again drawing on American experiences, just why there has been so much opposition to the employment of economic pricing principles in the urban road transport market. The author presents the results of an SSRC sponsored study into the practical problems of introducing road pricing to cities in the United States.     

Optimization of tunnel tolls in land use and transport planning

The task of transport planning is to determine cost-effective methods of providing and improving mobility, which can include minimizing traffic congestion. A cost-effective solution to transport problems should consist of a land use pattern, a transport system an a set of road pricing policies that together bring demand and supply into balance in an efficient and equitable way. The conventional approach aimed to produce comprehensive, long-term plans for land use and transport in considerable detail, but tended to ignore the role of road pricing policy, thus ending up with solutions that might not be efficient or economical. This feature of sub-optimal road pricing policy is accentuated by the overall growth in car use, which has generated problems with the efficient use of road space. This paper presents a computer analysis system (or model) which will enable the analysis of coordinated tunnel toll pricing policies by optimising an “objective function” while satisfying the associated and other constraints. The possibility of integrating the optimal road pricing policies in the land use and transport planning are discussed. A case study based on Hong Kong data demonstrates the efficiency of optimizing tolls on two of the three harbour crossing tunnels in Hong Kong.     

Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility

Interest in vehicle automation has been growing in recent years, especially with the very visible Google car project. Although full automation is not yet a reality there has been significant research on the impacts of self-driving vehicles on traffic flows, mainly on interurban roads. However, little attention has been given to what could happen to urban mobility when all vehicles are automated. In this paper we propose a new method to study how replacing privately owned conventional vehicles with automated ones affects traffic delays and parking demand in a city. The model solves what we designate as the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP), which dynamically assigns family trips in their automated vehicles in an urban road network from a user equilibrium perspective where, in equilibrium, households with similar trips should have similar transport costs. Automation allows a vehicle to travel without passengers to satisfy multiple household trips and, if needed, to park itself in any of the network nodes to benefit from lower parking charges. Nonetheless, the empty trips can also represent added congestion in the network. The model was applied to a case study based on the city of Delft, the Netherlands. Several experiments were done, comparing scenarios where parking policies and value of travel time (VTT) are changed. The model shows good equilibrium convergence with a small difference between the general costs of traveling for similar families. We were able to conclude that vehicle automation reduces generalized transport costs, satisfies more trips by car and is associated with increased traffic congestion because empty vehicles have to be relocated. It is possible for a city to charge for all street parking and create free central parking lots that will keep total transport costs the same, or reduce them. However, this will add to congestion as traffic competes to access those central nodes. In a scenario where a lower VTT is experienced by the travelers, because of the added comfort of vehicle automation, the car mode share increases. Nevertheless this may help to reduce traffic congestion because some vehicles will reroute to satisfy trips which previously were not cost efficient to be done by car. Placing the free parking in the outskirts is less attractive due to the extra kilometers but with a lower VTT the same private vehicle demand would be attended with the advantage of freeing space in the city center.     

Platooning for sustainable freight transportation: an adoptable practice in the near future?

ABSTRACT

Platooning is an emerging transportation practice that has the potential to solve the problems of the burgeoning transportation industry. A platoon is a group of vehicles, with vehicle to vehicle communication, that travel closely behind one another such that the platoon can accelerate, brake and cruise together. Platoons can improve road safety, be energy efficient and reduce costs. Its complete socio-economic benefits include congestion mitigation, smoother traffic flow, better lane usage and throughput, incentives for green logistics and driver safety. The long-term effect of platooning on road transportation, if extensively deployed, would be better organised traffic flow and efficient tracking of vehicles on the road ushering a multilevel positive impact on the industry. In this study, we attempt to answer the critical question of whether platooning is an adoptable practice in the near future and discuss an agenda to take platooning closer to implementation on the ground by highlighting the opportunities for future research. We also present a conceptual framework to help researchers, academicians, policy makers and practitioners for the adoption of platooning into the transportation industry.     

Proactive route guidance to avoid congestion

We propose a proactive route guidance approach that integrates a system perspective: minimizing congestion, and a user perspective: minimizing travel inconvenience. The approach assigns paths to users so as to minimize congestion while not increasing their travel inconvenience too much. A maximum level of travel inconvenience is ensured and a certain level of fairness is maintained by limiting the set of considered paths for each Origin-Destination pair to those whose relative difference with respect to the shortest (least-duration) path, called travel inconvenience, is below a given threshold. The approach hierarchically minimizes the maximum arc utilization and the weighted average experienced travel inconvenience. Minimizing the maximum arc utilization in the network, i.e., the ratio of the number of vehicles entering an arc per time unit and the maximum number of vehicles per time unit at which vehicles can enter the arc and experience no slowdown due to congestion effects, is a system-oriented objective, while minimizing the weighted average experienced travel inconvenience, i.e., the average travel inconvenience over all eligible paths weighted by the number of vehicles per time unit that traverse the path, is a user-oriented objective. By design, to ensure computational efficiency, the approach only solves linear programming models. In a computational study using benchmark instances reflecting a road infrastructure encountered in many cities, we analyze, for different levels of maximum travel inconvenience and, the minimum maximum arc utilization and the weighted average experienced travel inconvenience. We find that accepting relatively small levels of maximum travel inconvenience can result in a significant reduction, or avoiding, of congestion.     

Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors

Microeconomic optimisation of scheduled public transport operations has traditionally focused on finding optimal values for the frequency of service, capacity of vehicles, number of lines and distance between stops. In addition, however, there exist other elements in the system that present a trade-off between the interests of users and operators that have not received attention in the literature, such as the optimal selection of a fare payment system and a designed running speed (i.e., the cruising speed that buses maintain in between two consecutive stops). Alternative fare payment methods (e.g., on-board and off-board, payment by cash, magnetic strip or smart card) have different boarding times and capital costs, with the more efficient systems such as a contactless smart card imposing higher amounts of capital investment. Based on empirical data from several Bus Rapid Transit systems around the world, we also find that there is a positive relationship between infrastructure cost per kilometre and commercial speed (including stops), achieved by the buses, which we further postulate as a linear relationship between infrastructure investment and running speed. Given this context, we develop a microeconomic model for the operation of a bus corridor that minimises total cost (users and operator) and has five decision variables: frequency, capacity of vehicles, station spacing, fare payment system and running speed, thus extending the traditional framework. Congestion, induced by bus frequency, plays an important role in the design of the system, as queues develop behind high demand bus stops when the frequency is high. We show that (i) an off-board fare payment system is the most cost effective in the majority of circumstances; (ii) bus congestion results in decreased frequency while fare and bus capacity increase, and (iii) the optimal running speed grows with the logarithm of demand.     

(Unintended) Transport impacts of an energy-environment policy: The case of CNG conversion of vehicles in Dhaka

Motor vehicles are one of the major sources of air pollution in Dhaka, the capital of Bangladesh. The government took various policies to convert the petroleum vehicles on road to run on compressed natural gas (CNG), which allows both air quality improvements and energy security benefits. One of the market friendly policies to encourage the fuel switch was to increase the price differential between CNG and petrol and diesel. This has allowed a wide-scale adoption of CNG as the fuel of choice. However, several years into the policy, there is now a widespread belief among the policymakers that the CNG conversion may have increased car ownership and car travel due to their lower running costs, resulting in more congestion and a reversal of the strategy is on the cards. It is therefore important to test the hypothesis whether CNG conversion had genuinely increased car ownership and car travel in Dhaka city. This paper presents the results of a questionnaire survey and an econometric intervention analysis to understand the impact of CNG conversion on car ownership and car travel in Dhaka. Attention is also given to disentangle the self-selection and price-induced travel effects of CNG conversion. Results show that ownership did not increase, but travel of on-road vehicles increased due to the CNG policy. However, additional congestion costs are still around one half of the health benefits brought about by the policy.     

Optimal congestion taxes in a time allocation model

The purpose of this paper is to study optimal congestion taxes in a time-allocation framework. This makes it possible to distinguish taxes on inputs in the production of car trips and taxes on transport as an activity. Moreover, the model allows us to consider the implications of treating transport as a demand, derived from other activities. We extend several well known tax rules from the public finance literature and carefully interpret the implications for the optimal tax treatment of passenger transport services. The main findings of the paper are the following. First, if governments are limited to taxing market inputs into transport trip production, the time-allocation framework: (i) provides an argument for taxing congestion below marginal external cost, (ii) implies a favourable tax treatment for time-saving devices such as GPS, and (iii) provides a previously unnoticed argument for public transport subsidies. Second, if the government has access to perfect road pricing that directly taxes transport as an activity, all previous results disappear. Third, in the absence of perfect road pricing, the activity-specific congestion attracted by employment centres, by shopping centres or by large sports and cultural events should be corrected via higher taxes on market inputs in these activities (e.g., entry tickets, parking fees, etc.).     

Congestion and safety: A spatial analysis of London

A disaggregate spatial analysis, using enumeration district data for London was conducted with the aim of examining how congestion may affect traffic safety. It has been hypothesized that while congested traffic conditions may increase the number of vehicle crashes and interactions, their severity is normally lower than crashes under uncongested free flowing conditions. This is primarily due to the slower speeds of vehicles when congestion is present. Our analysis uses negative binomial count models to examine whether factors affecting casualties (fatalities, serious injuries and slight injuries) differed during congested time periods as opposed to uncongested time periods. We also controlled for congestion spatially using a number of proxy variables and estimated pedestrian casualty models since a large proportion of London casualties are pedestrians. Results are not conclusive. Our results suggest that road infrastructure effects may interact with congestion levels such that in London any spatial differences are largely mitigated. Some small differences are seen between the models for congested versus uncongested time periods, but no conclusive trends can be found. Our results lead us to suspect that congestion as a mitigator of crash severity is less likely to occur in urban conditions, but may still be a factor on higher speed roads and motorways.     

Automated vehicles: exploring possible consequences of government (non)intervention for congestion and accessibility

ABSTRACT

Academic research on automated vehicles (AVs) has to date been dominated by the fields of engineering and computer science. Questions of how this potentially transformative technology should be governed remain under-researched and tend to concentrate on governing the technology’s early development. We respond in this paper by exploring the possible longer-term effect of government (lack of) intervention.

The paper tests the hypothesis that a “laissez-faire” governance approach is likely to produce less desirable outcomes in a scenario of mass uptake of AVs than would a well-planned set of government interventions. This is done using two prominent themes in transport policy – traffic flow and accessibility – in a scenario of high market penetration of Level-5 automated vehicles in capitalist market economies. The evidence used is drawn from a literature review and from the findings of a set of workshops with stakeholders.

We suggest that a laissez-faire approach will lead to an increase in traffic volume as a result of a growing population of “drivers” and a probable increase in kilometres driven per passenger. At the same time, the hoped-for increases in network efficiency commonly claimed are not guaranteed to come about without appropriate government intervention. The likely consequence is an increase in congestion. And, with respect to accessibility, it is likely that the benefits of AVs will be enjoyed by wealthier individuals and that the wider impacts of AV use (including sprawl) may lead to a deterioration in accessibility for those who depend on walking, cycling or collective transport.

We consider the range of possible government intervention in five categories: Planning/land-use; Regulation/policy; Infrastructure/technology; Service provision; and Economic instruments. For each category, we set out a series of interventions that might be used by governments (at city, region or state level) to manage congestion or protect accessibility in the AV scenario described. Many of these (e.g. road pricing) are already part of the policy mix but some (e.g. ban empty running of AVs) would be new. We find that all interventions applicable to the management of traffic flow would also be expected to contribute to the management of accessibility; we define a small number of additional interventions aimed at protecting the accessibility of priority groups.

Our general finding is that the adoption of a package of these interventions could be expected to lead to better performance against generic traffic-flow and accessibility objectives than would a laissez-faire approach, though questions of extent of application remain.

In our conclusions, we contrast laissez-faire with both anticipatory governance and “precautionary” governance and acknowledge the political difficulty associated with acting in the context of uncertainty. We point out that AVs do not represent the first emerging technology to offer both opportunities and risks and challenge governments at all levels to acknowledge the extent of their potential influence and, in particular, to examine methodically the options available to them and the potential consequences of pursuing them.     

Assessing the cost-optimal mileage of medium-duty electric vehicles with a numeric simulation approach

Electric freight vehicles have the potential to mitigate local urban road freight transport emissions, but their numbers are still insignificant. Logistics companies often consider electric vehicles as too costly compared to vehicles powered by combustion engines. Research within the body of the current literature suggests that increasing the driven mileage can enhance the competitiveness of electric freight vehicles. In this paper we develop a numeric simulation approach to analyze the cost-optimal balance between a high utilization of medium-duty electric vehicles – which often have low operational costs – and the common requirement that their batteries will need expensive replacements. Our work relies on empirical findings of the real-world energy consumption from a large German field test with medium-duty electric vehicles. Our results suggest that increasing the range to the technical maximum by intermediate (quick) charging and multi-shift usage is not the most cost-efficient strategy in every case. A low daily mileage is more cost-efficient at high energy prices or consumptions, relative to diesel prices or consumptions, or if the battery is not safeguarded by a long warranty. In practical applications our model may help companies to choose the most suitable electric vehicle for the application purpose or the optimal trip length from a given set of options. For policymakers, our analysis provides insights on the relevant parameters that may either reduce the cost gap at lower daily mileages, or increase the utilization of medium-duty electric vehicles, in order to abate the negative impact of urban road freight transport on the environment.     

Rationing and pricing strategies for congestion mitigation: Behavioral theory,econometric model,and application in Beijing

Some travel demand management policies such as road pricing have been widely studied in literature. Rationing policies, including vehicle ownership quota and vehicle usage restrictions, have been implemented in several megaregions to address congestion and other negative transportation externalities, but not well explored in literature. Other strategies such as Vehicle Mileage Fee have not been well accepted by policy makers, but attract growing research interest. As policy makers face an increasing number of policy tools, a theoretical framework is needed to analyze these policies and provide a direct comparison of their welfare implications such as efficiency and equity. However, such a comprehensive framework does not exist in literature. To bridge this gap, this study develops an analytical framework for analyzing and comparing travel demand management policies, which consists of a mathematical model of joint household vehicle ownership and usage decisions and welfare analysis methods based on compensating variation and consumer surplus. Under the assumptions of homogenous users and single time period, this study finds that vehicle usage rationing performs better when relatively small percentages of users (i.e. low rationing ratio) are rationed off the roads and when induced demand elasticity resulting from congestion mitigation is low. When the amount of induced demand exceeds a certain level, it is shown analytically that vehicle usage restrictions will always cause welfare losses. When the policy goal is to reduce vehicle travel by a fixed portion, road pricing provides a larger welfare gain. The performance of different policies is influenced by network congestion and congestibility. This paper further generalizes the model to consider heterogenous users and demonstrates how it can be applied for policy analysis on a real network after careful calibration.     

Why railway passengers are more polluting in the peak than in the off-peak; environmental effects of capacity management by railway companies under conditions of fluctuating demand

Given the difference between peak and off-peak occupancy rates in public transport, the average emission per traveller kilometre is lower in the peak than during the off-peak period. However, in this paper it is argued that it is much more fruitful to analyse environmental effects in marginal than in average terms. The issue appears to depend on capacity management policies of public transport suppliers that are facing increases in demand both during the peak and off-peak period. A detailed analysis of capacity management of the Netherlands Railways reveals that the off-peak capacity supply is mainly dictated by the demand levels during the peak period. Topics that receive attention in the analysis are the effects of frequency increases and size of vehicle increases on environmental effects. Also environmental economies of vehicle size are taken into account in the analysis. The main conclusion is that the marginal environmental burden during the peak is much higher than is usually thought, whereas it is almost zero at the off-peak period. Thus, one arrives at a pattern that is entirely reversed compared with the average environmental burden: peak passengers are more polluting than off-peak passengers. The conclusion is that policies based on average environmental performances would lead to misleading conclusions.