Energy and emissions impacts of a freeway-based dynamic eco-driving system

Surface transportation consumes a vast quantity of fuel and accounts for about a third of the US CO₂ emissions. In addition to the use of more fuel-efficient vehicles and carbon-neutral alternative fuels, fuel consumption and CO₂ emissions can be lowered through a variety of strategies that reduce congestion, smooth traffic flow, and reduce excessive vehicle speeds. Eco-driving is one such strategy. It typically consists of changing a person’s driving behavior by providing general static advice to the driver (e.g. do not accelerate too quickly, reduce speeds, etc.). In this study, we investigate the concept of dynamic eco-driving, where advice is given in real-time to drivers changing traffic conditions in the vehicle’s vicinity. This dynamic strategy takes advantage of real-time traffic sensing and telematics, allowing for a traffic management system to monitor traffic speed, density, and flow, and then communicates advice in real-time back to the vehicles. By providing dynamic advice to drivers, approximately 10–20% in fuel savings and lower CO₂ emissions are possible without a significant increase in travel time. Based on simulations, it was found that in general, higher percentage reductions in fuel consumption and CO₂ emission occur during severe compared to less congested scenarios. Real-world experiments have also been carried out, showing similar reductions but to a slightly smaller degree.     

Joint impact of competition,ownership form and economic regulation on airport performance and pricing

The combined impact of ownership form, economic regulation and competition on airport performance is analyzed using data envelopment analysis to measure cost efficiency in the first stage and regression analysis to measure the impact of the environment in the second stage. The empirical results of an analysis of European and Australian airports over a 10 year timeframe reveal that under relatively non-competitive conditions, public airports operate less cost efficiently than fully private airports. Irrespective of ownership form, regulation is necessary to emulate competitive forces thus pushing airport management towards cost efficiency and reasonable pricing policies. Under potential regional or hub competition, economic regulation inhibits airports of any ownership form from operating and pricing efficiently. Although public and fully private airports operate equally efficiently in a competitive setting, private airports still set higher aeronautical charges. Furthermore, mixed ownership forms with a majority public holding are neither cost efficient nor low price, irrespective of the level of competition.     

Measuring supply chain risk: Predicting motor carriers’ ability to withstand disruptive environmental change using conjoint analysis

Supply chain risk measurement is an expanding research stream that considers the ability of networked firms to anticipate and respond to significant environmental risks, including major disruptions and unexpected events. However measuring and quantifying supply chain risk has proved an enormous challenge and this research contributes to this goal by developing a risk assessment scorecard, using conjoint analysis, for motor carrier firms. The resultant motor-carrier scorecard has been scaled from 300 to 900, to resemble the well-known FICO score for assessing consumer creditworthiness. Our scoring model enables motor carriers – and the firms that depend upon them in intermodal supply chains – to assess carriers’ ability to withstand major disruptive events, which are broadly defined as events which might lead to a significant drop in carriers’ income and profitability (e.g., such as that which occurred on September 11, 2001). Carriers with weaker risk scores (<600, on a 300–900 scale) are more likely to experience financial distress (and as a result possibly exit the industry itself); those with scores above 600 are less likely to depart. The model correctly identified 77 percent of motor carriers that ultimately exited the trucking industry following the significant environmental disruption caused by 9/11. Our computational experience indicates that the model accuracy, quantified in terms of Type I and Type II errors, compares favorably to prior results reported in the credit scoring literature.     

When are subsidies to trans-European network projects justified?

The trans-European transport network (TEN-T) encompasses the major planned transport infrastructure in Europe, ranging from high speed rail to port infrastructure. Projects in this category are considered priority projects and receive European subsidies; but these have been insufficient to get these projects off the ground. This paper addresses two research questions. First, it sketches the basic economics of cross-boundary infrastructure projects: what pricing and investment policies can we expect, what is the role of through traffic and high fixed costs of infrastructure? Second, it examines briefly what lessons the EU could draw from the experience of other existing federal funding institutions like the US and Germany. These ideas are used to propose a new subsidy scheme for the TEN-T projects.     

Post-entry container port capacity expansion

Port capacity development is a critical strategy for the growth of a new port, as well as for the development of existing ones, when both new and existing ports serve the same hinterland but have different competitive conditions. To study this strategy, we develop a two-stage duopoly model that comprises the pricing and capacity decisions of two heterogeneous players serving an increasing market. We identify the necessary condition for a port to increase its profit through capacity expansion, and characterize the condition when preemptive pricing by the dominant player is neither credible nor effective in preventing the smaller player from gaining market share. We also find the pure-strategy Nash equilibrium in the capacity expansion game for two ports that have different price sensitivities, as well as different operation and capacity investment costs. We apply the model results to the container port competition between Hong Kong and Shenzhen after Shenzhen port started its container operation in 1991. Our analysis explains the transition of market power from monopoly to duopoly, the fast development of Shenzhen Port, and the possible market structure changes with the continuing increase in demand.     

Urban freight,parking and pricing policies: An evaluation from a transport providers’ perspective

This paper investigates transport providers’ preferences for alternative loading bays and pricing policies. It estimates the importance of loading bays, the probability of finding them free and offers strategically relevant information to policy makers. The results underline the relevance of both preference heterogeneity and non-linear attribute effects. Three classes of agents are detected with substantially different preferences also characterized by non-linear sensitivity to attribute level variations. The specific freight sector, frequency of accesses and number of employees are all relevant covariates explaining different preferences for alternative transport providers’ categories. The implications of the results obtained are illustrated by simulating alternative policy scenarios. In conclusion, the paper underlines the need for rigorous policy analysis if the correct policy outcomes are to be estimated with an adequate level of accuracy.     

Optimal selection of build-operate-transfer projects on transportation networks

This paper considers the problem of how to select highway projects for the build-operate-transfer (BOT) development with the objective of improving the social benefit while ensuring the marketability of those selected. The problem can be viewed as a tri-level leader-follower game and is formulated as a mixed integer program with equilibrium constraints. Without solving the associated problem, we show that optimal tolls and travel times on selected BOT highways can be determined from their attributes under mild assumptions. This leads to an efficient heuristic algorithm for solving the project selection problem.     

CO2 efficiency in road freight transportation: Status quo, measures and potential

Road freight transport continues to grow in Germany and generates 6% of the country’s CO₂ emissions. In logistics, many decisions influence the energy efficiency of trucks, but causalities are not well understood. Little work has been done on quantifying the potential for further CO₂ reduction and the effect of specific activities, such as introducing computer assisted scheduling systems to trucking firms. A survey was survey out and linked fuel consumption to transport performance parameters in 50 German haulage companies during 2003. Emission efficiency ranged from 0.8 tonne-km to 26 tonne-km for 1 kg CO₂ emissions. The results show potential for improvements given a low level of vehicle usage and load factor levels, scarce use of lightweight vehicle design, poorly selected vehicles and a high proportion of empty runs. IT-based scheduling systems with telematic application for data communication, positioning and navigation show positive effects on efficiency. Fuel use and transport performance was measured before and after the introduction of these systems.     

Airport congestion pricing and passenger types

We consider a public and congested airport served by airlines that may have market power, and two types of travelers with different relative values of time. We find that in the absence of passenger-type-based price discrimination by airlines, it can be useful to increase the airport charge so as to protect passengers with a great relative time value from excessive congestion caused by passengers with a low relative time value. As a result, the socially efficient airport charge can be substantially higher than what we learned from the recent literature on congestion pricing with non-atomistic airlines.     

Integrated operations planning and revenue management for rail freight transportation

In the rail industry, profit maximization relies heavily on the integration of logistics activities with an improved management of revenues. The operational policies chosen by the carrier have an important impact on the network yield and thus on global profitability. This paper bridges the gap between railroad operations planning and revenue management. We propose a new bilevel mathematical formulation which encompasses pricing decisions and network planning policies such as car blocking and routing as well as train make-up and scheduling. An exact solution approach based on a mixed integer formulation adapted to the problem structure is presented, and computational results are reported on randomly generated instances.