University Traveler Value of Potential Real-Time Transit Information

Fries, Ryan; Dunning, Anne E; Chowdhury, Mashrur

doi:10.5038/2375-0901.14.2.2

Cited by 9 publications

(5 citation statements)

References 27 publications

(26 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, the practice of providing RTI to transit riders via web-enabled and mobile devices has become increasingly ubiquitous (Schweiger, 2011), and a growing body of literature aims to understand the rider impacts of RTI provided via personal devices. Some of these studies have utilized simulation modeling techniques (Fries et al, 2011) and others have employed stated preference techniques (Tang and Thakuriah, 2010), in which researchers pose hypothetical scenarios to survey participants as opposed to directly observing their behavior. The following brief literature review focuses on research that evaluates actual transit rider behavior (as opposed to simulation or stated preference methods) because these studies are most likely to provide the concrete conclusions needed for decision-makers at transit agencies.…”

Section: Prior Researchmentioning

confidence: 99%

The impact of real-time information on bus ridership in New York City

Brakewood

Macfarlane

Watkins

2015

Transportation Research Part C: Emerging Technologies

111

View full text Add to dashboard Cite

Section: Prior Researchmentioning

confidence: 99%

The impact of real-time information on bus ridership in New York City

Brakewood

Macfarlane

Watkins

2015

Transportation Research Part C: Emerging Technologies

111

View full text Add to dashboard Cite

“…Brakewood et al (2015) found that wait times at bus stops significantly decreased and users showed a significant reduction in their levels of anxiety and frustration when waiting for a bus due to real-time information. Several prior studies also aimed to understand the impacts of real-time information on ridership (Fries et al 2011;Tang and Thakuriah 2012;Brakewood et al 2014;Ferris et al 2010). Tang and Thakuriah (2012) observed an increase of 1.8-2.2% in average weekday trips due to real-time information.…”

Section: Prior Work and Deduced Research Needs 21 Prior Researchmentioning

confidence: 99%

Trade-offs between headway, fare, and real-time bus information under different weather conditions

2018

View full text Add to dashboard Cite

Given the increasing interest in real-time bus information, quantifying the value of such information from a user's perspective is useful for transport modelers and service planners. Although a number of studies have investigated several other aspects of real-time bus information systems, there is a lack of studies that compare the disutility associated with the bus headway of a scheduled arrival information system and that of a real-time information system from a user's perspective. In addition, no analyses in the literature examined the value of real-time information as affected by trip purpose and weather, which is important especially for the cities in which the weather remains below zero degrees during winter. The primary objectives of this research are to elucidate these issues. A stated preference survey describing the choice between scheduled and real-time information systems was conducted in Calgary, Canada. A total of 426 people participated in the survey, and each person was presented with three randomly selected choice situations. This data set was utilized to estimate the coefficients in different utility functions using a mixed logit model, which avoided several major limitations of a standard multinomial logit model. It was found that the disutility of the headway of a realtime information system was about half of the disutility of a scheduled information system. The analysis also showed that there was a nonlinear trend for the real-time information system, in which people found a higher disutility rate for a longer headway. Further, the value of real-time information availability was normally distributed in the population, with a mean of $0.50 and a standard deviation of $0.40. The results also revealed that the value of real-time information was significantly different when the weather was below and above 0 °C, those values were $0.59 and $0.41, respectively. Many of the findings obtained here are novel and have implications for

show abstract

“…This walking time was determined through field trials where researchers timed their trip from the center of each on-street parking strip or parking lot to the center of campus, determined through a weighted average of contact hours in each campus building. 40 During these trials, researchers paced with other representative walkers. The findings indicated that if only half of the motorists that would have parked in the core campus make one trip from campus during the day (using their vehicle), the relocated parking is no longer saving Clemson motorists time.…”

Section: Simulation Scenario Findingsmentioning

confidence: 99%

Applying dynamic traffic assignment in modeling permit-restricted parking utilizing microscopic traffic simulation

2011

Self Cite

View full text Add to dashboard Cite

Many universities are evaluating ways to improve mobility while dealing with increased demand for parking within the campus. Different types of parking strategies are considered as potential tools for improving campus mobility and meeting increased parking demand. Limited information is available on how removing on-street parking from the center of a university campus, relocating motorists to park on the periphery of campus, will impact the neighboring transportation system. Although dynamic traffic assignment (DTA) is a valuable tool for evaluating such impacts, most previous studies have used DTA with mesoscopic models. Thus, there is also limited guidance on the application of DTA within microscopic simulation models. The purpose of this study was to test a novel methodology for evaluating the mobility impact of relocating parking. The authors developed a method of utilizing DTA within a microscopic traffic simulation model. This model was applied to a case study capturing the changes in traffic patterns and volumes as a result of university parking changes. The authors found the methodology efficient and repeatable, and identified several simulator challenges with this new application. The case study findings suggest that, due to the significant number of motorists searching for the high-demand parking in the core of campus, relocating this parking to periphery lots will reduce the average travel time, even when accounting for the increased walking time.

show abstract

University Traveler Value of Potential Real-Time Transit Information

Abstract: Intelligent transportation systems (ITS) have become common in public transit

Cited by 9 publications

References 27 publications

The impact of real-time information on bus ridership in New York City

The impact of real-time information on bus ridership in New York City

Trade-offs between headway, fare, and real-time bus information under different weather conditions

Applying dynamic traffic assignment in modeling permit-restricted parking utilizing microscopic traffic simulation

Contact Info

Product

Resources

About