Travel using managed lanes: An application of a stated choice model for Houston,Texas

Managed lane (ML) travel adds flexibility, but also complexity, to travel choices. Stated choice models (SCMs) are often used for modeling complex transportation choices such as these in an effort to predict demand for these travel options. The design methods for SCMs have evolved from simple orthogonal designs to more sophisticated designs such as D-efficient design that can increase efficiency in estimation. We used three different survey design strategies to produce the stated preference portion of surveys, which were used to elicit travel choices for a sample of Houston travelers. Apart from the D-efficient design we also used random and adaptive random designs to generate attribute levels. There were observable differences in choice behavior depending on what design strategy was used. These differences appear to influence estimates of the value of travel time savings (VTTS) obtained from the random parameter logit (RPL) models estimated using these data. This, in turn, would greatly impact the percentage of travelers predicted to use the MLs.The adaptive random strategy was superior to the other design methods in several categories, and it had similar efficiency to the D-efficient design. However, the mean of VTTS estimate obtained from a D-efficient design was closer to what is typically found in the literature. The difference was considerable and could greatly influence traffic and revenue estimates for the MLs, illustrating the importance of the survey design strategy.     

Resilience of passenger boarding strategies to priority fares offered by airlines

Increased efficiency of airplane boarding via the jetway is achieved by sequencing passengers at the airport terminal. Various strategies have been developed and implemented at airports. However, even the best strategy can be distorted by the airlines priority fare. Priority passengers board in a random order which destroy the desired boarding sequence. This causes the aircraft aisle to be blocked in different locations. The article analyses the sensitivity of most common boarding strategies to the number of priority passengers. The article gives an example for Airbus A320 with single aisle cabin, configured in 30 rows of 6 seats each. To investigate this issue an original simulation model was developed, which allows to estimate the impact of the number of passengers with priority on the implementation of selected boarding strategies. The results obtained are astonishing. Such distortions have a negative impact on some strategies, while for some strategies better results are obtained. This discrete event based simulation model allows the process manager to choose the appropriate strategy or to abandon the jetway and use the airport stairs to avoid or reduce delaying the aircraft.     

Solving an integrated operational transportation planning problem with forwarding limitations

In integrated operational transportation planning (IOTP) problems, the traditional vehicle routing problem is extended by using external resources for the fulfillment of transportation requests. IOTP is getting more complex when the choice of the fulfillment mode is limited for some requests. In this paper, an existing column generation-based heuristic for IOTP is extended by two strategies for handling forwarding limitations. The computational experiments indicate that one of the extended versions of the heuristic outperforms all previous approaches in literature. Further on, the impact of forwarding limitations on different location structures and on the size of the private fleet is analyzed.     

Co-evolution between etailing and parcel express industry and its geographical imprints: The case of China

This study conceptualizes the relationship between etailing (e-retailing) and the parcel express industry (PEI) and analyzes their co-evolution in China. Four operational models of etailing are discussed in the context of their intertwining relations with different forms of parcel express services. This co-evolution generated compound outcomes because of the late start of PEI and the fast growth of online shopping in China. These four models coexist, with two standing out as major types that suggest future directions. Two major geographical imprints of this process are explained and conceptualized: (1) the zonal delivery strategy by supply-chain-based e-merchants, which is conceptualized into a choice model of order-fulfilling locations to strengthen timely delivery; and (2) the Baoyou strategy advocated by e-market-based retailers and their logistic support for a slower, low-cost market of larger geographical coverage compared to the first strategy. Both strategies demonstrate that co-evolution is not only a path-dependent process but is also associated with place-dependent institutions.     

Recovering costs through price and service differentiation: Accounting for exogenous information on attribute processing strategies in airline choice

The entry of low cost airlines has thrown out a challenge to all airlines to find ways of attracting passengers, through a mix of fare discounting, greater frequency, improved flight times and no-frill's levels of on-board service. These competitive strategies have an impact on cost recovery. As airlines seek business in an increasingly heterogeneous passenger market, a greater understanding of what matters to potential passengers in choosing an airline grows in importance. Traditional studies of passenger airline choice assume that all attributes matter, but some to a lesser extent. What happens to the empirical evidence on willingness to pay when specific attributes are totally ignored by particular passengers? In this paper, we examine the impact of individual-specific attribute processing strategies (APS) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of airline service and fare level choice. Modelling practice assumes that whilst respondents may exhibit preference heterogeneity, they employ a homogenous APS with regards to how they process the presence/absence of attributes of stated choice (SC) experiments. We demonstrate how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute of the SC task may be used in the estimation process, and how such information may be used to provide outputs that are attribute processing strategies segment specific.     

Transportation disruption risk management: business interruption insurance and backup transportation

Business interruption (BI) insurance and backup transportation have been widely used in distribution centers’ daily risk management. If disruption occurs, a firm (distribution center) can exert efforts to resume its transportation, although its unit transportation cost during the recovery process is uncertain. This paper studies how ex ante BI insurance can affect the ex post transportation recovery, and compares BI insurance with the ex post action—backup transportation. We investigate four strategies: basic strategy, BI insurance strategy, backup transportation strategy, and mixed strategy (integration of the last two). The distribution center that seeks the least profit loss prefers the mixed strategy to other three strategies. However, the mixed strategy might in turn require longer transportation recovery time than the BI insurance strategy. The BI insurance and transportation recovery are complementary, but the BI insurance and backup transportation are substitutable, the backup transportation and the transportation recovery are also substitutable. We also find that the choice of BI insurance strategy and the backup transportation strategy depends on transportation market, insurance market and distribution center’s operational environments.     

The implications on willingness to pay of a stochastic treatment of attribute processing in stated choice studies

Individuals processing the information in a stated choice experiment are asked to evaluate a set of attributes offered and to choose their most preferred alternative. It has always been thought that some attributes are not attended to in this process for many reasons, including a coping strategy to handle their perception of the complexity of the choice task. However analysts proceed, with rare exception, to estimate discrete choice models as if all attributes have influenced the outcome to some degree. In this paper we investigate the implications of bounding the attribute processing task by attribute elimination through not attending to one or more attributes. Using a sample of car non-commuters in Sydney we estimate a mixed logit model in which all attributes are assumed to be attended to, and models which assume that certain attribute(s) are not attended to, based on supplementary information provided by respondents. The supplementary information is accounted for in a deterministic and a stochastic way; the latter in recognition of the analyst’s lack of full information on why a specific attribute processing (AP) strategy was adopted by each sampled individual. We compare the value of travel time savings distribution under alternative attribute processing regimes. As expected, there are noticeable variations in the mean and standard deviation willingness to pay (WTP) across the three AP strategies.     

Reducing airplane boarding time by accounting for passengers' individual properties: A simulation based on cellular automaton

The increase of air travel puts tremendous burden on airline companies. A time saving boarding strategy is required to improve the utilization of airplane boarding time and explore flexible time management strategies. Firstly, an improved boarding strategy is introduced by assigning individual passengers to seats based on the number of luggage they carry. Passengers with the most luggage board onto the plane first. To test the behavior of boarding strategies under different conditions, a sophisticated simulation environment based on cellular automata model is designed. Simulation results indicate that the improved boarding strategy shows an excellent efficiency and robustness comparing with other strategies.     

Designing optimal urban transport strategies: The role of individual policy instruments and the impact of financial constraints

This paper presents a methodology for the design of optimal transport strategies and the case study results of the methodology for the City of Edinburgh, using the two multi-modal transport/land-use models MARS and TPM. First, a range of policy instruments are optimised in turn and their relative impacts explored. Second, optimisations with and without financial constraints are performed and compared. Although both models produce similar optimal policies, the relative contribution of the instruments differs between models as does the impact on outcome indicators. It is also shown that by careful design it is possible to identify a strategy which costs no more than the do-minimum but which can generate substantial additional benefits. The optimisation methodology is found to be robust, and is able to be used with different transport models, and with and without financial constraints.     

Reducing the effect of passengers’ non-compliance with aircraft boarding rules

The quest for efficient aircraft boarding strategies continues to generate lots of business and scientific discussions. Boarding strategies define rules and procedures aimed to reduce boarding time and operational cost. Most of the proposed strategies do not account for passengers’ non-compliance with boarding rules. Non-compliance is one of the major non-deterministic problems that can degrade any performance improvement to be expected from adopting a boarding strategy. To that, it is of paramount interest to shed light on this problem and introduce approaches for mitigating any related performance degradation in the boarding process. Although some recent research investigations considered the effect of non-compliance on the overall boarding time under different strategies, there was a lack of remedial actions. This paper dissects the operational characteristics of the non-compliance activity, proposes two different intervention approaches to deal with non-complying passengers, and analyzes the resulting impact under different categories of boarding strategies using a cellular-automaton-based simulation.     

城市轨道交通相邻多车站动态协同限流研究

为应对城市轨道交通车站高峰期客流压力,限流已经成为常态应对措施,而经常采用的限流策略大多针对单个车站,缺少对相邻多个车站的协同考虑。基于客流在车站间的传播效应,以乘客总延误时间最小为目标,以站台及列车能力为约束条件,构建城市轨道交通相邻多车站协同限流决策模型,同时为实现实时动态控制,引入滚动时域控制方法,优化多车站动态协同限流流程。以北京地铁8号线为例,经过相邻若干车站运营数据进行限流策略计算。结果表明,该模型限流可以在不造成车站服务人数损失的同时,将乘客总延误时间降低21%。     

A model for holding strategy in public transit systems with real-time information

Holding strategies are among the most commonly used operation-control strategies in public transit systems. These strategies are most effective when used to control services characterized by high frequency. In this paper, a mathematical model for a holding control strategy is developed. Particularly, this model uses real-time information of locations of buses along a specified route. The objective of the developed model is to minimize the waiting time of passengers at all stops on that route. Furthermore, the model developed in this paper is characterized by the flexibility of adopting situations where bus occupancy could be either high, or low. A heuristic is developed to circumvent the complexity of the solution for the problem described. Numerical examples and computational results are presented and discussed.     

Spatial-modal scenarios of greenhouse gas emissions from commuting in Hong Kong

Transportation is a major source of greenhouse gas emissions in cities. Multiple strategies including green technologies, transport management, urban planning and behavior changes are required to mitigate transport emissions. This paper aims to introduce an analytical framework to investigate the impacts of different spatial-modal strategies on reducing commuting emissions. Based on the optimization approach of excess commuting, the proposed framework incorporates the minimum, maximum and random (unpredictable) travel outcomes to inform planning of an urban form embedded with fewer emissions. This analytical framework is applied to Hong Kong to estimate the emissions ranges (the minimum and maximum amounts) under 42 spatial-modal scenarios - a combination of six spatial strategies (status quo, monocentric, highly polycentric, moderately polycentric, dual-centric and tri-centric) and seven modal strategies (status quo, pro-rail (high), pro-rail (moderate), pro-bus (high), pro-bus (moderate), pro-car (high) and pro-car (moderate)). The findings illustrate the emissions impacts if Hong Kong is further developed following a job concentration or decentralization principle. It also indicates that if Hong Kong is reconstructed to be a city with multiple CBDs, a dual-centric strategy is desirable because both minimum and maximum commuting are shorter than that of a tri-centric strategy. Moreover, the modal strategy to actively promote rail usage shows more impacts on emissions reduction and car usage should be maintained at the current level. If commuter's travl is less predictable, the high rail usage under a dual-centric city form is a more sustainable spatial-modal strategy. The proposed analytical framework of city's commuting emissions affected by structural and modal changes is transferrable to other places and could offer planners different benchmarks of travel pattern to substantiate their sustainable city planning vision.     

Robust accessibility: Measuring accessibility based on travelers' heterogeneous strategies for managing travel time uncertainty

Uncertainties in travel times due to traffic congestion and delay are risks for drivers and public transit users. To avoid undesired consequences such as losing jobs or missing medical appointments, people can manage the risks of missing on-time arrivals to destinations using different strategies, including leaving earlier to create a safety margin and choosing routes that have more reliable rather than fastest travel times. This research develops a general analytical framework for measuring accessibility considering automobile or public transit travelers' heterogeneous strategies for dealing with travel time uncertainty. To represent different safety margin plans, we use effective travel time (expected time + safety margin), given specified on-time arrival probabilities. Heterogeneity in routing strategy is addressed using different Pareto-optimal routes with two main criteria: faster travel time vs. higher reliability. Based on various safety margin and routing strategy combinations, we examine how accessibility changes under varying safety margin plans and routing strategies. Also, we define and measure robust accessibility: geographic regions that are accessible regardless of the safety margin planning and routing strategy. Robust accessibility can provide a conservative and reasonable view of accessibility under travel time uncertainty. To demonstrate the applicability of the methods, we carry out an empirical study on measuring the impacts of new transit service on healthcare accessibility in a deprived neighborhood in Columbus, Ohio, USA.     

Accessibility impacts of China’s high-speed rail network

The large-scale implementation of High-Speed Rail (HSR) network in China not only offers a new option for travelers’ mode choice, but also may influence, or even generate, the redistribution of demographic and economic activities. As has been observed over the past several years in other countries, the impact of HSR spans a wide range. However, few quantitative studies have been conducted to measure this impact. As a new attempt, this study uses accessibility analysis for quantifying the impact of China’s HSR network. Weighted average travel times and travel costs, contour measures, and potential accessibility are employed as indicators of accessibility at the macro or national level. Forty-nine major cities in the HSR network are used in the accessibility analysis. Accessibility quantification and spatial distribution analysis for the study cities are performed on a Geographical Information System (GIS) platform. Accessibilities associated with varying availabilities of HSR, conventional rail, and airline are estimated and compared. The selected indicators and computational methods are found effective in evaluating the accessibility impacts of HSR from different conceptualization strategies and perspectives. They also offer complementary information on accessibility capacity of the study cities created by the HSR network.     

Mitigating the impact of errors in travel time reporting on mode choice modelling

Travel time is a major component in understanding travel demand. However, the quantification of demand and forecasting hinges on understanding how travel time is perceived and reported. Travel time reporting is typically subject to errors and this paper focuses on the mitigation of their impact on choice models. The aim is to explain the origin of these errors by including elements of travel behaviour (e.g., activities during the trip), which have been shown to significantly affect mode choices and commuting satisfaction. Based on responses from a revealed preferences survey, we estimate a mode choice model that treats travel time as a latent variable and incorporates different sources of data along with information on travel activities. Employing these multiple – sometimes incongruent – sources of information in the choice model appears to be beneficial. Results from comparing a logit model assuming error-free inputs and the integrated hybrid model revealed significant impacts on the generated policy scenarios. The model results also contributed to identifying the main travel activity features that affect travel time reporting, providing indications that can assist in understanding and mitigating the impact of imprecise measurements.     

Identifying differences in willingness to pay due to dimensionality in stated choice experiments: a cross country analysis

This paper explores the influence of both cultural and socio-economic characteristics on the perception of complexity and cognitive load associated with stated choice (SC) experiments. Complexity is analysed in terms of five design dimensions which were systematically varied according to a macro experimental design. To study the influence of cross country differences on willingness to pay estimates, we combined datasets collected in Sydney, Santiago de Chile and Taichung city in Taiwan, all of them related to an equivalent route choice experiment. Several mixed logit models were specified and estimated; our results show that design dimensions do have an impact on the behavioural outputs of discrete choice models estimated on SC data. However, these influences seem to be data-specific, suggesting that the impact of design dimensions upon SC outcomes may be local and not necessarily transferable across different countries and cultures.     

Efficient vehicles versus efficient transportation. Comparing transportation energy conservation strategies

This article compares four potential transportation energy conservation strategies using a comprehensive evaluation framework that takes into account how each strategy affects annual vehicle travel, and therefore, mileage-related impacts such as traffic congestion, road and parking facility costs and crash risk. Mileage-related impacts tend to be large in magnitude compared with energy conservation benefits, so even small changes in total vehicle travel can have a large impact on net benefits. Fuel efficiency standards and some alternative fuels cause vehicle travel to increase. Higher fuel taxes cause a combination of increased vehicle fuel economy and reduced mileage. Mobility management strategies cause relatively large mileage reductions and so provide the greatest mileage-related benefits. Conventional evaluation practices often overlook mileage-related impacts and so tend to overvalue strategies that increase vehicle fuel efficiency and undervalue mobility management strategies.     

To bargain or not to bargain: Airlines,legitimacy and nonmarket strategy in a COVID-19 world

Nonmarket strategy – strategic actions directed at influencing the governmental, legalregulatory, and societal environment of business – is a key factor in an airlines' competitive position yet remains relatively under-analyzed in aviation research. The COVID-19 crisis has created a heightened role for nonmarket strategy and our paper argues that in deciding how to respond to a variety of policy measures introduced by governments, airline executives need to take into account the perceived legitimacy from the flying public of their response to governments. Our paper presents an integrative framework to analyze airlines' nonmarket response to COVID-19 governmental policy measures. Using a two-by-two matrix, we identify key conceptual links between industry's nonmarket response, the health impacts of a given policy measure as well as its economic costs for the airlines. Our study concludes that, unless economic stakes in a given policy measure are high, airlines do not risk active bargaining with governments over the content of that measure. Such bargaining could trigger a delegitimation cascade: a self-reinforcing process in which key stakeholders reassess their view of airlines' conduct and the industry's broader societal impact. Bargaining is pursued when economic impacts of policy measures are high, and in that case, the choice between cooperative and adversarial posture towards the government depends on the health impact of a given policy.     

Choice model based analysis of consumer preference for drone delivery service

It is anticipated that drones will soon be utilized for a range of applications, including delivery service. However, there has been a lack of research on consumer preference between drone delivery service and traditional delivery service. This is the first study to analyze the consumer preference for drone delivery based on a discrete choice model between the drone delivery service and traditional delivery services by truck or motorcycle. The discrete choice model is estimated using a stated preference survey, and potential consumers’ preference is analyzed for representative commodities with different price. The results show that the price and type of commodities influence consumer preference, which also depends on socio-demographic characteristics such as gender, age, and household income. Specifically, it was consistently observed in all cases that the younger the age, the higher the preference for drone delivery service. This study contributes to predicting the consumer preference for drone delivery service before real service offerings and to supporting the establishment of business strategies for companies who prepare for the new market of drone-based delivery.