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.     

Traveler delay costs and value of time with trip chains, flexible activity scheduling and information

The delay costs of traffic disruptions and congestion and the value of travel time reliability are typically evaluated using single trip scheduling models, which treat the trip in isolation of previous and subsequent trips and activities. In practice, however, when activity scheduling to some extent is flexible, the impact of delay on one trip will depend on the actual and predicted travel time on itself as well as other trips, which is important to consider for long-lasting disturbances and when assessing the value of travel information. In this paper we extend the single trip approach into a two trips chain and activity scheduling model. Preferences are represented as marginal activity utility functions that take scheduling flexibility into account. We analytically derive trip timing optimality conditions, the value of travel time and schedule adjustments in response to travel time increases. We show how the single trip models are special cases of the present model and can be generalized to a setting with trip chains and flexible scheduling. We investigate numerically how the delay cost depends on the delay duration and its distribution on different trips during the day, the accuracy of delay prediction and travel information, and the scheduling flexibility of work hours. The extension of the model framework to more complex schedules is discussed.     

Transaction costs and tradable mobility credits

Artificial markets for mobility credits have been proposed as an alternative to conventional congestion pricing schemes. This paper examines the effects of transaction costs on two types of markets: an auction market and a negotiated market. In an auction market, users purchase all of the needed mobility credits through a competitive bidding process. In a negotiated market, the users initially receive certain amount of mobility credits from the government and trade with each other through negotiation to fulfill their needs. We assume that a brokerage service is built in both markets to facilitate transactions and accordingly, the users have to pay a commission fee proportional to the value of trade. The users are also given the option to purchase credits from the government if for some reasons they cannot use or wish to avoid the markets. Our analyses suggest that the auction market can achieve the desired equilibrium allocation of mobility credits as long as the government sets its price properly and the unit transaction cost is lower than the price that the market would reach in absence of transaction costs. However, in the negotiated market, transaction costs could divert the system from the desired equilibrium regardless of their magnitude. More importantly, the initial allocation of mobility credits may affect the final equilibrium even when marginal transaction costs are constant.     

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.     

Low cost carrier competition and route entry in an emerging but regulated aviation market – The case of China

Although China lags behind other liberalized aviation markets in low cost carrier (LCC) development, its largest LCC, Spring Airlines, has achieved rapid growth in traffic volume and revenue, as well as consistent profitability, since its inauguration in 2005. Our empirical study on the Chinese domestic market suggests that Spring adopts a “cream skimming” strategy to enter high-priced routes, allowing the carrier to achieve both a very high load factor and considerable profitability. Spring’s capacity and market share on individual routes are constrained to low levels, likely due to government regulation and/or a “puppy dog” strategy adopted by the carrier. As a result, Spring is able to achieve fast growth without triggering price wars. To incumbent full service carriers, high speed rail (HSR) services impose much more significant competitive pressure than low cost carriers. Similar to LCCs in developed markets, Spring prefers to serve markets with high traffic volumes out of its operational base in Shanghai. Overall, Spring’s entry decision is not significantly affected by competition, either from full service airlines or HSR services. Our investigation suggests that LCCs have potential to introduce more competition but are yet to be a “game changer” in China. Further deregulation of the domestic market is needed.     

An advanced traveler general information system for Fresno,California

This study estimates the effects of an advanced traveler general information system (ATGIS), which includes fuel consumption and health-related emissions cost information on transportation network users’ travel choice behavior for recurrent congestion conditions. The effects are estimated using four different formulations based on four different behavioral assumptions. Incorporating stochastic features in link cost estimation rather than in route choice, we provide a novel modeling approach that enables us to use transportation planning models of major metropolitan areas without a need for major computationally-expensive changes in the existing models. We examined the effects of an ATGIS on the Fresno, CA, road network and found several interesting results. First, the ATGIS impact is closely related to pre-system (prior to the implementation of an ATGIS) perceived fuel and emissions costs. Total travel time in the city can be reduced by 17% (no pre-system perceived costs) to 1% (accurate pre-system perceived costs), and even increased by 1% (higher-than-actual pre-system perceived costs). Second, the addition of emissions costs, although negligible relative to fuel and time costs, can effectively reduce total system-wide travel time by up to 1% and fuel consumption by up to 0.6% during peak hours. Third, the ATGIS can reduce annual social costs by as much as $1053 million (high gas price, no pre-system perception) to $48 million (medium gas price, accurate pre-system perception), which are comparable to social cost savings by a congestion pricing (CP) scheme in the study area.     

Line haul interstation spacing for low cost feeder modes

The choice behaviour of low cost travel (LCT) modes is very sensitive to travel distance. A line haul system designed on the basis of current planning practice of locating widely spaced stations to cater auto and bus feeder modes with the primary objective of gaining travel speed is hostile to non‐motorized and low cost feeder modes. With the revival of interest in promoting the use of walk'n ride and bike'n ride modes, there is a need to develop an appropriate tool to examine the effect of their specific characteristics in establishing the number and location of stations.

A generic normative behavioural hybrid model for locating the cost minimizing number and location of stations is developed for an LCT‐fed line haul system. The model considers the system with many to many two dimensional line haul demand density function in which the density varies in both x‐ and y‐directions. The feeder mode choice behaviour is incorporated in the model by integrating probability‐access/egress distance function with the objective function. Explicit functional relationships among the parameters of these feeder modes such as modal share as a function of access/egress distance with the parameters of line haul systems are developed. Dynamic programming is used to minimize the system cost. The generic model is shown to collapse into several simplified models capable of yielding approximate solutions for several well known special cases. It has been shown that location of stations is sensitive to the through load on board as well as users’ cost that defines the choice behaviour at large. Numerical examples are presented to demonstrate the applicability of the model.     

California’s Low Carbon Fuel Standard: Modeling financial least-cost pathways to compliance in Northwest California

The transition to low-carbon transportation fuels plays a key role in ongoing efforts to combat climate change. This analysis seeks to optimize potential alternative fuel portfolios that would lead to a 10% reduction in fuel carbon intensity by 2020 as required under California’s Low Carbon Fuel Standard (LCFS).We present a novel, probabilistic modeling approach for evaluating alternative fuel portfolios based on their marginal greenhouse gas (GHG) abatement costs. Applied to a case study region in Northwest California, our model enables us to quantify the financial cost of GHG reduction via each fuel pathway, as well as for a portfolio deployed to meet the LCFS target. It also enables us to explore the sensitivity of the alternative fuel portfolio, evaluating the impact of fluctuating prices, fuel carbon intensities, and technology penetrations on the makeup of the portfolio and on the average cost of GHG abatement.We find that battery electric vehicles play a critical role, as they offer the lowest-financial-cost significant abatement in almost all plausible scenarios. However, electric vehicles alone will not be sufficient to reach the target; low-carbon biofuels can be expected to play a role in the achievement of 2020 Low Carbon Fuel Standard targets.