Quantifying travel time variability at a single bottleneck based on stochastic capacity and demand distributions

Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability.     

Estimating flight-level price elasticities using online airline data: A first step toward integrating pricing,demand, and revenue optimization

We estimate flight-level price elasticities using a database of online prices and seat map displays. In contrast to market-level and route-level elasticities reported in the literature, flight-level elasticities can forecast responses in demand due to day-to-day price fluctuations. Knowing how elasticities vary by flight and booking characteristics and in response to competitors’ pricing actions allows airlines to design better promotions. It also allows policy makers the ability to evaluate the impacts of proposed tax increases or time-of-day congestion pricing policies. Our elasticity results show how airlines can design optimal promotions by considering not only which departure dates should be targeted, but also which days of the week customers should be allowed to purchase. Additionally, we show how elasticities can be used by carriers to strategically match a subset of their competitors’ sale fares. Methodologically, we use an approach that corrects for price endogeneity; failure to do so results in biased estimates and incorrect pricing recommendations. Using an instrumental variable approach to address this problem we find a set of valid instruments that can be used in future studies of air travel demand. We conclude by describing how our approach contributes to the literature, by offering an approach to estimate flight-level demand elasticities that the research community needs as an input to more advanced optimization models that integrate demand forecasting, price optimization, and revenue optimization models.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

Non‐compatible chemicals as cargoes in industry,on road,rail, and water

Toronto is to have an urban transit system with a passenger carrying capacity which fills the gap between the capacity of the subway and the capacity of the car and bus. Correspondingly, in the words of the Premier of Ontario, the system will “make possible an attractive alternative to high‐rise, high‐density living and urban sprawl. . . .” Furthermore, the new system is sufficiently economical to provide “. . . an encouragement to growth in appropriate areas, rather than merely responding to growth as it occurs . . .”

The decision to have such a system is the culmination of some years of major transportation activities in the Province, which included the Metropolitan Toronto and Region Transportation Study (MTARTS) of 1962. This study pursued both urban expressways and public transport solutions to the movement of people in Metropolitan Toronto.

The urban expressways programmes ran into difficulties, on environmental terms, when strong opposition from community groups was met on proposed routes. A climax came when the Ontario Government halted the construction of the controversial Spadina expressway in June 1971. However, the programmes of public transport solutions met with great success. The Toronto subway and its extensions, together with the change in land values along the route, has become a classic success story. So, too, has the introduction of the GO Train Service (Government of Ontario train service). This pioneered a combination of commuter rail service and integrated feeder buses and today replaces some 14,000 cars each day along the lakeshore highways.

The success of the subway and the GO train coupled with the difficulties experienced by the urban expressways programme, gave rise to the realisation that a better city through public transport rather than the car, was practicable. However, subways were too expensive and they needed a large patronage in a narrow corridor. Accordingly, an intermediate capacity transit system was sought.

The paper describes the programme of activities involved in the choice of the system and describes the technical specification which the system will enjoy. In particular, the demonstration installation which is to be set‐up in Toronto is described in detail, together with the plans to instal some 56 miles over five routes in Metropolitan Toronto.     

Women’s mode and trip structure choices in daily activity-travel: a developing country perspective

ABSTRACT

In this paper, we analyze the travel patterns of Iranian women, where typical patriarchal views and specific social and cultural norms may differ from the patterns of those in western societies. In addition to inherent psycho-physical gender differences, women in Iran can face special constraints forcing them not to be involved in all activity-travel patterns that people in developed countries usually undertake. We pay special attention to the role of marital and employment status on women’s activity-travel patterns. To this end, we develop a joint mode and daily activity pattern (DAP) discrete choice model, which is a two-level mixed nested Logit. The upper nest of the proposed model embodies women’s DAP choices, and the lower nest belongs to the mode choices. In this paper, we try to show how different factors in a patriarchal Muslim society like Iran affect or restrict women’s type and structure of activity-travel patterns.     

降雨量对OD 行程时间可靠性影响分析

为详细研究降雨量对OD行程时间可靠性的影响，基于Uber 出行共享的3 年美国波士顿10 对OD行程时间数据及WeatherUnderground 网站提供的小时历史天气，构建了OD行程时间高斯混合模型(GMM). 模型参数利用EM法进行求解，K 值根据K-S 检验后的P 值 (大于0.500 0)进行确定，模型分位数利用二分法进行求解. 提出一种基于缓冲指数(BI)的新指标——缓冲指数变化率(BIVR)作为定量评估指标. 结果表明：降雨会降低总体OD行程时间可靠性，降低效果随降雨量提高而增强，但增强效果并不明显；尽管可能性较低，但当降雨处于次要影响因素时可能提高可靠性；小雨天气可视为正常天气；雨天可靠性显著低于正常天气，居民在雨天(除小雨外)出行应预留更多时间.     

A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area

Airport choice is an important air travel-related decision in multiple airport regions. This paper proposes the use of a probabilistic choice set multinomial logit (PCMNL) model for airport choice that generalizes the multinomial logit model used in all earlier airport choice studies. The paper discusses the properties of the PCMNL model, and applies it to examine airport choice of business travelers residing in the San Francisco Bay Area. Substantive policy implications of the results are discussed. Overall, the results indicate that it is important to analyze the choice (consideration) set formation of travelers. Failure to recognize consideration effects of air travelers can lead to biased model parameters, misleading evaluation of the effects of policy action, and a diminished data fit.     

The quality of survey data: Telephone versus face-to-face interviews

Those designing surveys and producing data have always been concerned about its quality. The increasing stringency of the financial constraints which affect public authorities and the increased scope of involvement in the regulation of urban travel has led us to pay even greater attention to the quality of data. This issue is frequently covered in the literature on survey methods. However, comparisons between different survey methods are more rarely conducted. The decision to conduct such an analysis is partly the result of the development of telephone use to the detriment of other survey modes in many countries and also the development of Computer-Aided Telephone Interviewing (CATI) which facilitates the running and monitoring of the survey.This paper examines several aspects of this question in order to compare the performance of telephone and face-to-face interviews. The first aspect is the representativeness of the sample, and therefore relates mainly to the issue of nonresponses and the choice of a sample base. The second concerns the accuracy of the information and involves the choice of a survey area and the recording of all trips, including short-distance travel. Finally, the quality of data is obviously determined by the quality of the responses given by those interviewed.The answers we give frequently depend on the objective of the surveys, which leads us to put forward a table which summarizes the performance of telephone and face-to-face interviews on the basis of the main objective of the survey. Broadly, the telephone seems to be the favoured tool for surveys in the area of transport planning and surveys which aim to provide data for forecasting models, mostly on the grounds of cost. However, face-to-face techniques are often preferred for surveys which aim to discover and analyze the factors which explain individual travel behaviour.