Analysis of Transit Users’ Response Behavior in Case of Unplanned Service Disruptions

2020 ◽  
Vol 2674 (3) ◽  
pp. 258-271 ◽  
Author(s):  
Ehsan Rahimi ◽  
Ali Shamshiripour ◽  
Ramin Shabanpour ◽  
Abolfazl (Kouros) Mohammadian ◽  
Joshua Auld
Keyword(s):  
User Satisfaction ◽  
Recovery Time ◽  
Random Parameter ◽  
Multinomial Logit Model ◽  
Transit System ◽  
Wide Range ◽  
Service Disruption ◽  
Transit Agencies ◽  
Panel Effects ◽  
Demographic Attributes

Public transit disruption is becoming more common across different transit services, and can have a destructive influence on the resiliency of the transportation system. Even though transit agencies have various strategies to mitigate the probability of failure in the transit system by conducting preventative actions, some disruptions cannot be avoided because of their either unpredictable or uncontrollable nature. Utilizing recently collected data of transit users in the Chicago Metropolitan Area, the current study aims to analyze how transit users respond to an unplanned service disruption and disclose the factors that affect their behavior. In this study, a random parameter multinomial logit model is employed to consider heterogeneity across observations as well as panel effects. The results of the analysis reveal that a wide range of factors including socio-demographic attributes, personal attitudes, trip-related information, and built environment are significant in passengers’ behavior in case of unplanned transit disruptions. Moreover, the effect of service recovery time on passengers is not the same among all types of disrupted services; rail users are more sensitive to the recovery time as compared with bus users. The findings of this study provide insights for transportation authorities to improve the transit service quality in relation to user satisfaction and transportation resilience. These insights help transit agencies to implement effective recovery strategies.

scholarly journals Results of the Behavioral Health Readiness Evaluation and Decision-Making Instrument Study

2021 ◽  
Vol 186 (Supplement_1) ◽  
pp. 142-152
Author(s):  
Justin M Curley ◽  
Katie L Nugent ◽  
Kristina M Clarke-Walper ◽  
Elizabeth A Penix ◽  
James B Macdonald ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Health ◽  
User Satisfaction ◽  
Safety Issue ◽  
Walter Reed Army Institute ◽  
End User ◽  
Chi Square ◽  
Proficiency Level ◽  
Wide Range ◽  
Decision Making Support

ABSTRACT Introduction Recent reports have demonstrated behavioral health (BH) system and individual provider challenges to BH readiness success. These pose a risk to winning on the battlefield and present a significant safety issue for the Army. One of the most promising areas for achieving better BH readiness results lies in improving readiness decision-making support for BH providers. The Walter Reed Army Institute of Research (WRAIR) has taken the lead in addressing this challenge by developing and empirically testing such tools. The results of the Behavioral Health Readiness Evaluation and Decision-Making Instrument (B-REDI) field study are herein described. Methods The B-REDI study received WRAIR Institutional Review Board approval, and BH providers across five U.S. Army Forces Command installations completed surveys from September 2018 to March 2019. The B-REDI tools/training were disseminated to 307 providers through random clinic assignments. Of these, 250 (81%) providers consented to participate and 149 (60%) completed both initial and 3-month follow-up surveys. Survey items included a wide range of satisfaction, utilization, and proficiency-level outcome measures. Analyses included examinations of descriptive statistics, McNemar’s tests pre-/post-B-REDI exposure, Z-tests with subgroup populations, and chi-square tests with demographic comparisons. Results The B-REDI resulted in broad, statistically significant improvements across the measured range of provider proficiency-level outcomes. Net gains in each domain ranged from 16.5% to 22.9% for knowledge/awareness (P = .000), from 11.1% to 15.8% for personal confidence (P = .001-.000), and from 6.2% to 15.1% for decision-making/documentation (P = .035-.002) 3 months following B-REDI initiation, and only one (knowledge) failed to maintain a statistically significant improvement in all of its subcategories. The B-REDI also received high favorability ratings (79%-97% positive) across a wide array of end-user satisfaction measures. Conclusions The B-REDI directly addresses several critical Army BH readiness challenges by providing tangible decision-making support solutions for BH providers. Providers reported high degrees of end-user B-REDI satisfaction and significant improvements in all measured provider proficiency-level domains. By effectively addressing the readiness decision-making challenges Army BH providers encounter, B-REDI provides the Army BH health care system with a successful blueprint to set the conditions necessary for providers to make more accurate and timely readiness determinations. This may ultimately reduce safety and mission failure risks enterprise-wide, and policymakers should consider formalizing and integrating the B-REDI model into current Army BH practice.

Usage, Impacts, and Benefits of Innovative Transit Pass Program

1998 ◽  
Vol 1618 (1) ◽  
pp. 131-138 ◽  
Author(s):  
James Meyer ◽  
Edward A. Beimborn
Keyword(s):  
Transit System ◽  
University Of Wisconsin ◽  
Milwaukee County ◽  
Successful Program ◽  
Pass Program ◽  
Transit Agencies ◽  
The University

An evaluation of an innovative transit program, UPASS, is summarized. UPASS provides unlimited use of the Milwaukee County Transit System at any time and any place and for any purpose for all students enrolled at the University of Wisconsin-Milwaukee. The pass program, paid for by a special fee attached to students’ tuition, was implemented in fall 1994 and was extensively evaluated to determine its impact on ridership and other factors and to determine whether the concept has the potential for transfer to other organizations and employers. Benefits and disbenefits to transit users, nonusers, employers, and transit agencies are described. In addition, elements of a successful program are outlined.

Italian millennials' preferences for wine: an exploratory study

2020 ◽  
Vol 122 (8) ◽  
pp. 2403-2423
Author(s):  
Federico Nassivera ◽  
Gianluigi Gallenti ◽  
Stefania Troiano ◽  
Francesco Marangon ◽  
Marta Cosmina ◽  
...  
Keyword(s):  
New Media ◽  
Willingness To Pay ◽  
Carbon Footprint ◽  
Generation Y ◽  
Logit Model ◽  
Random Parameter ◽  
Multinomial Logit Model ◽  
Discrete Choice Models ◽  
Content Type ◽  
Wine Consumption

PurposeThis paper aims to investigate the wine consumption among young people belonging to the so-called millennial generationDesign/methodology/approachThis study uses a questionnaire and a choice experiment (CE) with a multinomial logit model (MNL), implementing a random parameter logit model (RPL), to investigate the attitudes of millennials towards wine consumption, their purchasing behaviours and their willingness to pay for attributes of the products; in particular regarding the follwing: region of origin, “winescape”, certification, carbon footprint claim and price.FindingsMillennials appear to drink wine less frequently; they consume it more often in social on-premise settings, having a slightly higher willingness to pay and preferring carbon-neutral brands when choosing wine.Research limitations/implicationsThe limitation of this research was the analysis of a simulated situation where consumers declared their intention to purchase and not the effective purchase behaviour in the market.Further research should investigate wider millennials groups, also using the new media communication tools that characterise the communication behaviour of Generation Y. In this way, it would be possible to interview a millennial group at the national or international level.Practical implicationsThe research identifies some characteristics of millennials’ habits that can take into account the strategies of wine companies in order to develop a constructive relationship with Generation Y in Italy.Social implicationsThis research contributes to knowledge regarding the wine consumption habits of Italian millennials.Originality/valueThis paper applies discrete choice models to consumption situations in order to analyse millennials' preference and their willingness to pay for some innovative attributes of wine, in particular the carbon footprint.

Understanding Transit Agency Perceptions about Transportation Network Companies, Shared Mobility, and Autonomous Transit: Lessons from the United States

2019 ◽  
Vol 2673 (5) ◽  
pp. 95-108
Author(s):  
Mengjie Han ◽  
Matthew D. Dean ◽  
Pedro Adorno Maldonado ◽  
Parfait Masungi ◽  
Sivaramakrishnan Srinivasan ◽  
...  
Keyword(s):  
United States ◽  
New Technologies ◽  
Transportation Network ◽  
Critical Role ◽  
The United States ◽  
Transit System ◽  
Emergent Technologies ◽  
Shared Mobility ◽  
Transit Agencies ◽  
Transportation Network Companies

Emergent technologies like autonomous/connected vehicles and shared mobility platforms are anticipated to significantly affect various aspects of the transportation network such as safety, mobility, accessibility, environmental effects, and economics. Transit agencies play a critical role in this network by providing mobility to populations unable to drive or afford personal vehicles, and in some localities carry passengers more efficiently than other modes. As transit agencies plan for the future, uncertainty remains with how to best leverage new technologies. A survey completed by 50 transit agencies across the United States revealed similar yet different perceptions and preparations regarding transportation network companies (TNCs) and autonomous transit (AT) systems. Transit agencies believe TNC market share will grow, either minimally or rapidly (72%), within the next 5 years and have either a negative (43%) or positive (35%) impact on their transit system. Only 30% of agency boards instructed the agency to work with TNCs, despite no perceived transit union support. For AT systems, 22% of agencies are studying them, 64% believe the impacts of AT over the next 10–20 years will be positive, but fewer agencies are influenced to consider new technologies because of AT systems (38%) compared with TNCs (72%). Surprisingly, transit administration is mostly unsure about driver and transit unions’ perceptions of these technologies. In addition, a significant number of transit agencies do not believe they should play a role in ensuring TNCs are safe and equitable and that TNCs should not have to adhere to the same regulations (50%, 28% respectively).

Deployment of Fuel Cell Electric Buses in Transit Agencies: Hydrogen Fueling Infrastructure Scenarios

2015 ◽  
Author(s):  
Analy Castillo ◽  
Scott Samuelsen ◽  
Brendan Shaffer
Keyword(s):  
Fuel Cell ◽  
Natural Gas ◽  
Distribution System ◽  
Environmental Benefits ◽  
Pollutant Emissions ◽  
Systematic Evaluation ◽  
Generation Process ◽  
Wide Range ◽  
Hydrogen Infrastructure ◽  
Transit Agencies

For transit agencies looking to implement Zero Emission Vehicles (ZEV), Fuel Cell Electric Buses (FCEBs) represent an opportunity because of the similar range and refueling times compared to conventional buses, but with improved fuel economy. To assure an environmentally sensitive hydrogen infrastructure that can respond to the wide range of needs and limitations of transit agencies, a systematic evaluation of options is essential. This paper illustrates the systematic evaluation of different hydrogen infrastructure scenarios for a transit agency. The Orange County Transportation Authority (OCTA) in California was selected for the study. Three different hydrogen infrastructure configurations are evaluated and compared to the existing paradigm of compressed natural gas buses and diesel buses. One additional scenario is analyzed in order to compare feasibility and environmental benefits of FCEBs with Plug-in Electric Buses. Each scenario represents (1) a specific mix and percentage of contribution from the various hydrogen generation technologies (e.g., on-site electrolysis, central SMR, and on-site SMR), (2) defined paths to obtain the corresponding feedstock for each generation process (e.g., biogas, natural gas, renewable energies), (3) detailed hydrogen distribution system (e.g., mix of gaseous/liquid truck delivery), and (4) the spatial allocation of the generation location and fueling locations (e.g., on-site / off-site refueling station) while also accounting for constraints specific to the OCTA bases. This systematic evaluation provides Well-to-Wheel (WTW) impacts of energy and water consumption, greenhouse gases and criteria pollutant emissions of the processes and infrastructure required to deploy FCEBs and Plug-in Electric Buses at OCTA. In addition, this evaluation includes a detailed analysis of the space requirements and operations modifications that may be necessary, but yet feasible, for the placement of such infrastructure.

scholarly journals A review of Machine Learning (ML) algorithms used for modeling travel mode choice

DYNA ◽  
2019 ◽  
Vol 86 (211) ◽  
pp. 32-41 ◽  
Author(s):  
Juan D. Pineda-Jaramillo
Keyword(s):  
Machine Learning ◽  
Choice Model ◽  
Mode Choice ◽  
Multinomial Logit Model ◽  
Support Vector ◽  
Travel Mode ◽  
Wide Range ◽  
Travel Mode Choice ◽  
And Cluster Analysis ◽  
Transportation Research

In recent decades, transportation planning researchers have used diverse types of machine learning (ML) algorithms to research a wide range of topics. This review paper starts with a brief explanation of some ML algorithms commonly used for transportation research, specifically Artificial Neural Networks (ANN), Decision Trees (DT), Support Vector Machines (SVM) and Cluster Analysis (CA). Then, these different methodologies used by researchers for modeling travel mode choice are collected and compared with the Multinomial Logit Model (MNL) which is the most commonly-used discrete choice model. Finally, the characterization of ML algorithms is discussed and Random Forest (RF), a variant of Decision Tree algorithms, is presented as the best methodology for modeling travel mode choice.

Evaluating Real-Time Bus Arrival Information Systems

2000 ◽  
Vol 1731 (1) ◽  
pp. 81-87 ◽  
Author(s):  
Rabi G. Mishalani ◽  
Sungjoon Lee ◽  
Mark R. McCord
Keyword(s):  
Information Systems ◽  
Real Time ◽  
Evaluation Method ◽  
Time Data ◽  
Transit System ◽  
Arrival Times ◽  
Bus Stops ◽  
Transit Agencies ◽  
Time Systems ◽  
Time Information

Real-time transit passenger information systems are intended to improve the level of service provided by transit agencies. For example, passengers are given real-time information on the expected arrival times of buses on various routes at bus stops. These real-time systems reflect emerging applications in public transit, and methods to evaluate their benefits are limited. An evaluation method is presented that focuses on the potential benefits of bus arrival information systems to passengers waiting at bus stops. Passenger arrivals and transit bus operations are modeled as a stochastic system in which the operator uses real-time bus location data to provide bus arrival-time information that maximizes passengers' utilities. Simulation results reveal the nature of the dependence of system benefits on the type of real-time data available to the operator and the bus operations characteristics. An application to an existing bus transit system demonstrates the feasibility of the developed method and its role in assessing the value of real-time bus arrival information systems to passengers.

Anxiety Control Training

1994 ◽  
Vol 1 (2) ◽  
pp. 57-61 ◽  
Author(s):  
Philip Snaith
Keyword(s):  
Recovery Time ◽  
Diagnostic Procedure ◽  
Somatic Symptoms ◽  
Acute Illness ◽  
Normal Limits ◽  
Muscular Tension ◽  
Anxiety Control ◽  
Wide Range ◽  
Illness Anxiety ◽  
Sedative Drugs

Anxiety pervades every aspect of human activity and experience. It is a normal state and a spur to action, but readily exceeds normal limits in intensity, duration and appropriateness to the stimulus or situation. Anxiety is manifest by the mood of fearfulness, behaviour marked by restlessness and avoidance of situations, increased arousal with insomnia, excessive preoccupation with thoughts on the theme of insecurity, and a wide range of somatic symptoms which are based on muscular tension, hyperventilation leading to paraesthesiae and faintness, and symptoms based on overactivity of the autonomic nervous system. Excessive anxiety and situational avoidance leads to diminution of performance and limitation of endeavour. In the context of physical illness, anxiety increases the distress of symptoms, may confuse diagnostic procedure, prolong recovery time from acute illness, cause failure to comply with effective treatment and promote destructive habits such as reliance on alcohol or excessive use of sedative drugs.

The Hangover: Assessing Impact of Major Service Interruptions on Urban Rail Transit Ridership

2017 ◽  
Vol 2648 (1) ◽  
pp. 79-85
Author(s):  
Julene Paul ◽  
Michael J. Smart
Keyword(s):  
New York ◽  
Urban Areas ◽  
Hurricane Sandy ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit System ◽  
Transit Systems ◽  
Service Interruptions ◽  
Transit Ridership ◽  
Transit Agencies

Driven by several factors, transit ridership has increased dramatically in some major U.S. urban areas over the past several years. Developing accurate econometric models of system ridership growth will help transit agencies plan for future capacity. As major weather events and maintenance issues can affect transit systems and have large impacts on the trajectory of ridership growth, this study examined the effect of major and minor service interruptions on the PATH heavy rail transit system in northern New Jersey and New York City. The study, which used PATH ridership data as well as data on weather, economic conditions, and fares for both PATH and competing services, concluded that Hurricane Sandy likely dampened ridership gains. Other major service interruptions, which lasted only hours or days, had little effect on long-term ridership growth. Suggestions for further study of service interruptions, especially in the face of climate change and resiliency issues in coastal regions, are presented.

Lessons Learned for CBTC Data Communications Subsystems Design and Deployment in a “Brown Field” Environment

2017 ◽  
Author(s):  
Michael Fitzmaurice
Keyword(s):  
Lessons Learned ◽  
Data Communications ◽  
Wireless Data ◽  
Transit System ◽  
Field Environment ◽  
Transit Agencies

The data communications subsystem or DCS is an important element of a CBTC system which supports the wired and wireless data communications between a CBTC equipped train and the wayside elements such as zone controllers and the automatic train supervisory (ATS) system. A “brown field” environment (as opposed to “green field” environment) represents an existing transit system that is already in revenue service and is being re-signaled with a new CBTC system. Such an environment typically represent the most challenging deployment for CBTC a system as it must be installed, tested and integrated in such a manner as to not adversely impact the transit agencies’ ongoing revenue service. Usually, one of the first elements of a CBTC system to be designed and deployed is the DCS. This paper will examine some lessons learned related to the DCS design, deployment, testing and commissioning for CBTC projects in a “brown field” environment with a view to improving future CBTC projects.

Sign in / Sign up

Export Citation Format

Share Document