Influencing factors and heterogeneity in ridership of traditional and app-based taxi systems

The growth of app-based taxi services has disrupted the urban taxi market. It has seen significant demand shift between the traditional and emerging app-based taxi services. This study explores the influencing factors for determining the ridership distribution of taxi services. Considering the spatial, temporal, and modal heterogeneity, we propose a mixture modeling structure of spatial lag and simultaneous equation model. A case study is designed with 6-month trip records of two traditional taxi services and one app-based taxi service in New York City. The case study provides insights on not only the influencing factors for taxi daily ridership but also the appropriate settings for model estimation. In specific, the hypothesis testing demonstrates a method for determining the spatial weight matrix, estimation strategies for heterogeneous spatial and temporal units, and the minimum sample size required for reliable parameter estimates. Moreover, the study identifies that daily ridership is mainly influenced by number of employees, vehicle ownership, density of developed area, density of transit stations, density of parking space, bike-rack density, day of the week, and gasoline price. The empirical analyses are expected to be useful not only for researchers while developing and estimating models of taxi ridership but also for policy makers while understanding interactions between the traditional and emerging app-based taxi services.

     

RANS simulation of a container ship using a single-phase level-set method with overset grids and the prognosis for extension to a self-propulsion simulator

Steady flow simulations for the Korean Research Institute for Ships and Ocean Engineering (KRISO) container ship (KCS) were performed for towing and self-propulsion. The main focus in the present article is on the evaluation of computational fluid dynamics (CFD) as a tool for hull form design along with application of state-of-the-art technology in the flow simulations. Two Reynolds-averaged Navier-Stokes (RANS) equation solvers were employed, namely CFDShip-Iowa version 4 and Flowpack version 2004e, for the towing and self-propulsion cases, respectively. The new features of CFDShip-Iowa version 4 include a single-phase level-set method to model the free surface and an overset gridding capability to increase resolution in the flow and wave fields. The new features of Flowpack version 2004e are related to a self-propulsion scheme in which the RANS solver is coupled with a propeller performance program based on the infinitely bladed propeller theory. The present work is based on a close interaction between IIHR-Hydroscience and Engineering of the University of Iowa and Osaka Prefecture University. In the following article, overviews are given of the present numerical methods and results are presented and discussed for the KCS in towing and self-propulsion modes, including comparison with available experimental fluid dynamics (EFD) data. Additional evaluation is provided through discussion of the recent CFD Workshop Tokyo 2005, where both methods appeared to yield very promising results.     

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研究印度城市道路上设置公交专用道后小汽车出行向公交转移的可能性. 借助新的混合交通流仿真模型测定设置公交专用道后公交服务水平改善状况. 基于陈述偏好入户调查的抽样数据,本文还引入其他影响出行方式转移的变量,标定出行方式选择二元Logit模型. 根据实际和预测数据,确定了公交服务水平改善条件下小汽车出行向公交转移的一系列主要影响因素. 基于两种方式出行时间差,绘制出行方式转换概率曲线,并为多变量宽值域条件下交通方式转移的预测提供一种易于操作的方法.     

Bees-algorithm-based optimization of component size and control strategy parameters for parallel hybrid electric vehicles

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.     

Counting people in the crowd using social media images for crowd management in city events

Transportation - City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd...     

Dynamic Response of a Six-axle Locomotive to Random Track Inputs

Spectral analysis techniques are employed to analyze the dynamic response of a six-axle locomotive on tangent track to vertical and lateral random track irregularities. The locomotive is represented by a thirty-nine (39) degrees of freedom model. A linear model is employed by considering small displacements, linear suspension elements and a linear theory for the wheel-rail interaction. Power spectral densities of displacements, velocities and accelerations and the statistical average frequencies of the system are obtained for each degree of freedom. Comparison of the calculated dominating frequencies with existing experimental values shows good agreement. The technique of spectral analysis is an effective tool for model validation, and for the determination of rail vehicle response to track irregularities. The probability functions for the response can be used as a measure for the ride quality of rail vehicles and for the study of fatigue damage of components.     

Transport terminal design and passenger orientation

The objective of the internal design of a transport terminal is to minimize the disorientation and confusion of a passenger as he arrives at the terminal and desires to move towards the destination without undue loss of time. The experience of India however shows that most of the rail, bus and air terminals leave much to be desired from the human orientation point of view. To measure the passenger orientation and to enable evaluation of the terminal design an easily tractable quantitative method has recently been evolved. This paper attempts to apply it to two rail terminals in Bombay and to compute some indices to serve as criteria for determining the level of service and suggest directions for improvement.     

Joint modeling of evacuation departure and travel times in hurricanes

Hurricanes are costly natural disasters periodically faced by households in coastal and to some extent, inland areas. A detailed understanding of evacuation behavior is fundamental to the development of efficient emergency plans. Once a household decides to evacuate, a key behavioral issue is the time at which individuals depart to reach their destination. An accurate estimation of evacuation departure time is useful to predict evacuation demand over time and develop effective evacuation strategies. In addition, the time it takes for evacuees to reach their preferred destinations is important. A holistic understanding of the factors that affect travel time is useful to emergency officials in controlling road traffic and helps in preventing adverse conditions like traffic jams. Past studies suggest that departure time and travel time can be related. Hence, an important question arises whether there is an interdependence between evacuation departure time and travel time? Does departing close to the landfall increases the possibility of traveling short distances? Are people more likely to depart early when destined to longer distances? In this study, we present a model to jointly estimate departure and travel times during hurricane evacuations. Empirical results underscore the importance of accommodating an inter-relationship among these dimensions of evacuation behavior. This paper also attempts to empirically investigate the influence of social ties of individuals on joint estimation of evacuation departure and travel times. Survey data from Hurricane Sandy is used for computing empirical results. Results indicate significant role of social networks in addition to other key factors on evacuation departure and travel times during hurricanes.

     

Distributions of travel time variability on urban roads

Reliability is an important factor in route, mode and also departure time choice analysis and is a key performance indicator for transport systems. However, the current metrics used to measure travel time variability may be not sufficient to fully represent reliability. Better understanding of the distributions of travel times is needed for the development of improved metrics for reliability. A comprehensive data analysis involving the assessment of longitudinal travel time data for two urban arterial road corridors in Adelaide, Australia, demonstrates that the observed distributions are more complex than previously assumed. The data sets demonstrate strong positive skew, very long upper tails, and sometimes bimodality. This paper proposes the use of alternative statistical distributions for travel time variability, with the Burr Type XII distribution emerging as an appropriate model for both links and routes. This statistical distribution has some attractive properties that make it suitable for explicit definition of many travel time reliability metrics. Copyright © 2011 John Wiley & Sons, Ltd.     

Implications of Thresholds in Discrete Choice Modelling

Abstract

Individual choices are affected by complex factors and the challenge consists of how to incorporate these factors in order to improve the realism of the modelling work. The presence of limits, cut‐offs or thresholds in the perception and appraisal of both attributes and alternatives is part of the complexity inherent to choice‐making behaviour. The paper considers the existence of thresholds in three contexts: inertia (habit or reluctance to change), minimum perceptible changes in attribute values, and as a mechanism for accepting or rejecting alternatives. It discusses the more relevant approaches in modelling these types of thresholds and analyses their implications in model estimation and forecasting using both synthetic and real databanks. It is clear from the analysis that if thresholds exist but are not considered, the estimated models will be biased and may produce significant errors in prediction. Fortunately, there are practical methods to attack this problem and some are demonstrated.