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Benefits of Real-Time Transit Information and Impacts of Data Accuracy on Rider Experience

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Benefits of Real-Time Transit Information and Impacts of Data Accuracy on Rider Experience

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Abstract

When presented in a practical format, real-time transit information can improve sustainable travel methods by enhancing the transit experience. This paper identifies the positive shift realized by the continued development of the OneBusAway set of real-time transit information tools. In addition, the paper analyzes real-time prediction errors and their effects on the rider experience. In 2012, three years after the development of location-aware mobile applications, a survey of current OneBusAway users was conducted to compare the results with the previous 2009 study. Results show significant positive shifts in satisfaction with transit, perceptions of safety, and ridership frequency as a result of the increased use of real-time arrival information. However, this paper also provides a perspective of the margin of error riders come to expect and the negative effects resulting from inaccuracies with the real-time data. Although riders on average will ride less when they have experienced errors, a robust issue-reporting system as well as the resolution of the error can mitigate the initial negative effects. With this understanding, the paper provides transit agencies and developers with guidance to realize the full potential of real-time information and error-reporting systems.

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... In the first survey, conducted in 2009, 18% of respondents reported feeling ''somewhat safer'' and another 3% felt ''much safer'' as result of using RTI (Ferris et al., 2010). In 2012, a follow-up web-based survey in Seattle found over 32% of RTI users had a positive shift in their perception of personal security (Gooze et al., 2013). ...
... The University of Maryland study found a significant increase in overall satisfaction with shuttle bus service attributable to RTI (Zhang et al., 2008). Additionally, in the 2009 web-based survey of RTI users in Seattle, 92% of respondents stated that they were either ''somewhat more'' satisfied or ''much more'' satisfied with overall transit service, and the follow-up 2012 survey of RTI users found similar results (Ferris et al., 2010;Gooze et al., 2013). ...
... If passengers spend less time waiting and/or are more satisfied with overall transit service, then the provision of RTI may also cause an increase in the frequency of transit trips by existing riders or potentially attract new riders to transit. In Seattle, the two web-based surveys of RTI users previously discussed found that approximately one third of riders reported an increase in the number of non-work/school trips per week made on transit because of RTI (Ferris et al., 2010;Gooze et al., 2013). On the other hand, the University of Maryland study also evaluated frequency of travel on the university shuttle bus system but concluded that RTI did not cause an increase in shuttle bus trips (Zhang et al., 2008). ...
Article
Public transit agencies often struggle with service reliability issues; when a bus does not arrive on time, passengers become frustrated and may be less likely to choose transit for future trips. To address reliability issues, transit authorities have begun to provide real-time information (RTI) to riders via mobile and web-enabled devices. The objective of this research is to quantify the benefits of RTI provided to bus riders. The method used is a behavioral experiment with a before-after control group design in which RTI is only provided to the experimental group. Web-based surveys are used to measure behavior, feeling, and satisfaction changes of bus riders in Tampa, Florida over a study period of approximately three months.
... Riders also can use the information to adjust their own use of the transit system, e.g., by taking a different less-crowded bus, which can benefit other riders as well (Zimmerman et al. 2011). Other benefits identified in surveys include increased walking (i.e., public health benefits) and, for some riders, increased feelings of safety while waiting, particularly at night (Ferris et al. 2010; Gooze et al. 2013). With the number of smartphone users among transit riders being similar to those in the general population, providing app-based real-time information could be a major benefit to a large proportion of riders (Windmiller et al. 2014). ...
... OneBusAway has been used to jump-start several pilot and production deployments of real-time transit information systems (). It also has served as the foundation of several research projects that aim to better understand how real-time information impacts transit riders (Ferris 2010; Ferris et al. 2010; Watkins 2011; Watkins et al. 2011; Gooze et al. 2013; Brakewood 2014). However, until recently, there was a key limitation with the original OneBusAway project—the OneBusAway mobile apps in the respective app stores (i.e., Google Play, Apple App Store, Windows Phone Store, Windows Store) were configured to work only in Puget Sound, where OneBusAway originally was developed. ...
... Windows 8 app use increased by around 3,000 downloads. Studies of the effectiveness of OneBusAway regarding the user experience and impacts on transit riders have been reported in multiple papers (Watkins et al. 2011) (Ferris et al. 2010; Ferris 2011; Watkins 2011), including issues with accuracy and rider perception (Gooze et al. 2013). Although these studies took place in Seattle, additional work is being undertaken in Tampa, New York, and Atlanta (Brakewood 2014) (Brakewood et al. 2014). ...
Article
Full-text available
Real-time transit information offers many benefits to transit riders, including reduced wait times and increased customer satisfaction. However, offering real-time transit services has been challenging for many transit agencies. While mobile applications (apps) have emerged as a preferred dissemination method for real-time information, it is typically cost-prohibitive for transit agencies to fund custom development of native mobile apps for all popular smartphone platforms. Third-party developers can offer services if an agency openly shares real-time data, but these individuals are volunteers whose priorities and deadlines may not be the same as the agency's. As a result, few cities have full app portfolios that cover all smartphone platforms. This paper presents the OneBusAway multi-region project, a collaborative effort that is enabling the rapid expansion of native mobile transit apps to new cities. OneBusAway is an open-source transit information system that has provided real-time transit services to the Puget Sound (Washington) area since 2008. The new OneBusAway multi-region feature expands the coverage of the existing Android, iPhone, Windows Phone, and Windows 8 apps for OneBusAway to new cities, including Tampa and Atlanta. The multi-region system architecture, collaborative design and development process, and lessons learned from this ground-breaking project are discussed. The fundamental shift from proprietary to open-source software in the transit industry that has made this type of project possible also is examined.
... Transit agencies increasingly propose high-amenity transit stops and stations for mitigating the perceived burden of waiting time (Denver Union Station Project Authority, 2004;Metropolitan Council, 2012;Transit Planning Board, 2008). However, beyond the amenity of at-stop realtime arrival information (Brakewood et al., 2014(Brakewood et al., , 2015aDziekan and Kottenhoff, 2007;Gooze et al., 2013;Watkins et al., 2011), existing research does not sufficiently explore how specific station and stop amenities (e.g., benches, shelters) can effectively reduce transit users' perceptions of waiting time. This missing knowledge is problematic for efforts to increase transit use: users' perceptions of transit service play an important role in determining mode choice (Walle and Steenberghen, 2006) and often cannot be determined from common system-level performance measures (Eboli and Mazzulla, 2011). ...
... Watkins et al. (2011) reached nearly identical results for perceived versus measured waiting time for bus passengers in King County, Washington, USA using an at-stop, in person survey. In a 2014 follow-up study of the King County Metro, Gooze et al. (2013) found continued effects of shortened time perceptions, as well as self-reported more frequent transit use due to realtime information availability by nearly 30% of respondents. They also find that inaccurate realtime information increases waiting time estimates. ...
... This research provides direct evidence that the broad provision of basic stop amenities can significantly reduce the perceived burden of transit use. The insignificance of at-stop realtime information signs goes against the established body of literature on the subject (Dziekan and Kottenhoff, 2007;Gooze et al., 2013;Monzon et al., 2013;Watkins et al., 2011). Existing research specifically on realtime information often adopts a pre-test/post-test design, measuring waiting time perceptions at the same set of stops before and after installation of realtime information signs in the interest of minimizing the influence of other factors. ...
Article
Full-text available
Waiting time in transit travel is often perceived negatively and high-amenity stops and stations are becoming increasingly popular as strategies for mitigating transit riders’ aversion to waiting. However, beyond recent evidence that realtime transit arrival information reduces perceived waiting time, there is limited empirical evidence as to which other specific station and stop amenities can effectively influence user perceptions of waiting time. To address this knowledge gap, the authors conducted a passenger survey and video-recorded waiting passengers at different types of transit stops and stations to investigate differences between survey-reported waiting time and video-recorded actual waiting time. Results from the survey and video observations show that the reported wait time on average is about 1.21 times longer than the observed wait time. Regression analysis was employed to explain the variation in riders’ reported waiting time as a function of their objectively observed waiting time, as well as station and stop amenities, weather, time of the day, personal demographics, and trip characteristics. Based on the regression results, most waits at stops with no amenities are perceived at least 1.3 times as long as they actually are. Basic amenities including benches and shelters significantly reduce perceived waiting times. Women waiting for more than 10 min in perceived insecure surroundings report waits as dramatically longer than they really are, and longer than do men in the same situation. The authors recommend a focus on providing basic amenities at stations and stops as broadly as possible in transit systems, and a particular focus on stops on low-frequency routes and in less safe areas for security measures.
... Transit agencies increasingly propose high-amenity transit stops and stations for mitigating the perceived burden of waiting time (Denver Union Station Project Authority, 2004;Metropolitan Council, 2012;Transit Planning Board, 2008). However, beyond the amenity of at-stop realtime arrival information (Brakewood et al., 2014(Brakewood et al., , 2015aDziekan and Kottenhoff, 2007;Gooze et al., 2013;Watkins et al., 2011), existing research does not sufficiently explore how specific station and stop amenities (e.g., benches, shelters) can effectively reduce transit users' perceptions of waiting time. This missing knowledge is problematic for efforts to increase transit use: users' perceptions of transit service play an important role in determining mode choice (Walle and Steenberghen, 2006) and often cannot be determined from common system-level performance measures (Eboli and Mazzulla, 2011). ...
... Watkins et al. (2011) reached nearly identical results for perceived versus measured waiting time for bus passengers in King County, Washington, USA using an at-stop, in person survey. In a 2014 follow-up study of the King County Metro, Gooze et al. (2013) found continued effects of shortened time perceptions, as well as self-reported more frequent transit use due to realtime information availability by nearly 30% of respondents. They also find that inaccurate realtime information increases waiting time estimates. ...
... This research provides direct evidence that the broad provision of basic stop amenities can significantly reduce the perceived burden of transit use. The insignificance of at-stop realtime information signs goes against the established body of literature on the subject (Dziekan and Kottenhoff, 2007;Gooze et al., 2013;Monzon et al., 2013;Watkins et al., 2011). Existing research specifically on realtime information often adopts a pre-test/post-test design, measuring waiting time perceptions at the same set of stops before and after installation of realtime information signs in the interest of minimizing the influence of other factors. ...
Article
Full-text available
This paper discusses the observed evolution of traffic in the Minneapolis-St Paul (Twin Cities) region road network following the unexpected collapse of the I-35W Bridge over the Mississippi River. The observations presented within this paper reveal that traffic dynamics are potentially different when a prolonged and unexpected network disruption occurs rather than a preplanned closure. Following the disruption from the I-35W Bridge's unexpected collapse, we witnessed a unique trend: an avoidance phenomenon after the disruption. More specifically, drivers are observed to drastically avoid areas near the disruption site, but gradually return after a period of time following the collapse. This trend is not observed in preplanned closures studied to date. To model avoidance, it is proposed that the tragedy generated a perceived travel cost that discouraged commuters from using these sections. These perceived costs are estimated for the Twin Cities network and found to be best described as an exponential decay cost curve with respect to time. After reinstituting this calibrated cost curve into a mesoscopic simulator, the simulated traffic into the discouraged areas are found to be within acceptable limits of the observed traffic on a week-by-week basis. The proposed model is applicable to both practitioners and researchers in many traffic-related fields by providing an understanding of how traffic dynamics will evolve after a long-term, unexpected network disruption.
... The second database used for this search was Google Scholar. Google Scholar "provides a simple way to broadly search for scholarly literature" (Google, 2018), and therefore, it was used to broaden the scope of the search beyond transportation-specific databases (i.e. TRID). ...
... TRID). Google Scholar ranks documents by relevance by "weighing the full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in other scholarly literature" (Google, 2018). Because publications are listed in order of relevance to the keywords, a cut-off point was needed. ...
... Second, the previously discussed survey of RTI users conducted in Seattle showed 48% of respondents were "much more satisfied" and 44% of respondents were "somewhat more satisfied" with public transit as a result of using RTI (Ferris et al., 2010). Next is a follow-up survey in Seattle in which 51% of RTI users stated that they were "much more satisfied" with transit and 38% said they were "somewhat more satisfied" (Gooze et al., 2013). Fourth is the formerly cited behavioural experiment in Tampa, Florida, and two satisfaction-related indicators (satisfaction with "how long you have to wait for the bus" and satisfaction with "how often the bus arrives at the stop on time") increased significantly from the before to the after survey between the control group and the experimental group (Brakewood et al., 2014). ...
Article
Recently, it has become common practice for transit operators to provide real-time information (RTI) to passengers about the location or predicted arrival times of transit vehicles. Accompanying this is a growing body of literature that aims to assess the impacts of RTI on transit passenger behaviour and perceptions. The main objective of this research is to compile a literature review of studies that assess the passenger benefits of RTI provision. The results suggest that the primary behavioural changes associated with providing RTI to passengers pertain to decreased wait times, reductions in overall travel time due to changes in path choice, and increased use of transit. RTI may also be associated with increased satisfaction with transit service and increases in the perception of personal security when riding transit. A second objective of this review was to identify areas for future research based on remaining gaps in the literature; two keys areas that were identified are assessing actual behavioural changes of path choice of transit riders and conducting cost–benefit analyses post implementation of RTI systems. The results of this study have immediate implications for public transit operators considering implementation or expansion of RTI systems and researchers seeking topics for future investigation.
... Ferris et al. (2010) [16] conducted a survey of web-based RTI users for the city of Seattle, Washington, and concluded that the use of RTI increased self-reported levels of personal security by 18 percent; these users remarked RTI made transit "somewhat safer" and another three percent expressed "much safer." [17] continued survey in the same city and received positive responses from over 32 percent of the web-based RTI users. The follow-up surveys in the city of Seattle, in the year 2009, by [16] and in 2012, and by [17] revealed that 92 percent of the web-based RTI users expressed being secured. ...
... [17] continued survey in the same city and received positive responses from over 32 percent of the web-based RTI users. The follow-up surveys in the city of Seattle, in the year 2009, by [16] and in 2012, and by [17] revealed that 92 percent of the web-based RTI users expressed being secured. Since then, the use of RTI has increased in designing almost all the urban transit systems around the globe. ...
... In Seattle, Washington, a recent study of bus riders using RTI found that their actual wait times were almost 2 min less than those of non-users, and perceived wait times of RTI users were approximately 30% less than those who did not use RTI (Watkins et al., 2011). Other passenger benefits of RTI include increased perception of personal security and increased satisfaction with transit service (Zhang et al., 2008;Ferris et al., 2010;Gooze et al., 2013). ...
... Approximately 31% of users reported increases in non-commute trips, while a smaller percentage reported increases in commute trips on transit. A follow-up web-based survey of RTI users in 2012 found similar results (Gooze et al., 2013). However, the authors identified two important caveats for these studies: the survey results were all self-reported and did not include a control group of non-RTI users. ...
Article
In the past few years, numerous mobile applications have made it possible for public transit passengers to find routes and/or learn about the expected arrival time of their transit vehicles. Though these services are widely used, their impact on overall transit ridership remains unclear. The objective of this research is to assess the effect of real-time information provided via web-enabled and mobile devices on public transit ridership. An empirical evaluation is conducted for New York City, which is the setting of a natural experiment in which a real-time bus tracking system was gradually launched on a borough-by-borough basis beginning in 2011. Panel regression techniques are used to evaluate bus ridership over a three year period, while controlling for changes in transit service, fares, local socioeconomic conditions, weather, and other factors. A fixed effects model of average weekday unlinked bus trips per month reveals an increase of approximately 118 trips per route per weekday (median increase of 1.7% of weekday route-level ridership) attributable to providing real-time information. Further refinement of the fixed effects model suggests that this ridership increase may only be occurring on larger routes; specifically, the largest quartile of routes defined by revenue miles of service realized approximately 340 additional trips per route per weekday (median increase of 2.3% per route). Although the increase in weekday route-level ridership may appear modest, on aggregate these increases exert a substantial positive effect on farebox revenue. The implications of this research are critical to decision-makers at the country’s transit operators who face pressure to increase ridership under limited budgets, particularly as they seek to prioritize investments in infrastructure, service offerings, and new technologies.
... Previous studies have rarely investigated the impacts of ITS on tourism transport users, while urban commuters' responses to real-time transport information have been extensively observed and analyzed. Transit information users are observed to have a number of important responses, including shortenings in both perceived and actual waiting time with the help of detailed arrival information [12][13][14][15], increased satisfaction with transit services [16][17][18], and increased ridership and transfers [15,[17][18][19]. Long-period observation and corresponding regression analysis can help to investigate the change in commuters' ridership with influence from various factors, and then most of these findings were obtained from longitudinal data [16,19,20]. ...
... Previous studies have rarely investigated the impacts of ITS on tourism transport users, while urban commuters' responses to real-time transport information have been extensively observed and analyzed. Transit information users are observed to have a number of important responses, including shortenings in both perceived and actual waiting time with the help of detailed arrival information [12][13][14][15], increased satisfaction with transit services [16][17][18], and increased ridership and transfers [15,[17][18][19]. Long-period observation and corresponding regression analysis can help to investigate the change in commuters' ridership with influence from various factors, and then most of these findings were obtained from longitudinal data [16,19,20]. ...
Article
Full-text available
One important function of Intelligent Transportation System (ITS) applied in tourist cities is to improve visitors’ mobility by releasing real-time transportation information and then shifting tourists from individual vehicles to intelligent public transit. The objective of this research is to quantify visitors’ psychological and behavioral responses to tourism-related ITS. Designed with a Mixed Ranked Logit Model (MRLM) with random coefficients that was capable of evaluating potential effects from information uncertainty and other relevant factors on tourists’ transport choices, an on-site and a subsequent web-based stated preference survey were conducted in a representative tourist city (Chengde, China). Simulated maximum-likelihood procedure was used to estimate random coefficients. Results indicate that tourists generally perceive longer travel time and longer wait time if real-time information is not available. ITS information is able to reduce tourists’ perceived uncertainty and stimulating transport modal shifts. This novel MRLM contributes a new derivation model to logit model family and for the first time proposes an applicable methodology to assess useful features of ITS for tourists.
... Passengers are not only more willing to wait for transit, but they perceive their wait times as being shorter and the service itself as more reliable (Transportation Research Board 2003a;Watkins et al. 2011). Second, access to real-time transit information has been found to make transit feel safer (Transportation Research Board 2003a;Ferris et al. 2010;Gooze et al. 2013). Third, these systems allow passengers to make more informed choices about their transportation choices (Hickman & Wilson 1995;Maclean & Dailey 2002). ...
... Hence, a better understanding of information accuracy of RTTISs needs to be established. Gooze, Watkins, and Borning (2013) explored the effect of information accuracy in RTTISs in a study in Florida. The researchers distributed an online survey to 5,074 participants to determine, among other things, the margin of error riders were willing to accept in RTTISs. ...
Thesis
Full-text available
The purpose of this project was to evaluate and strategize the implementation of real-time transit information systems (RTTISs) through an examination of information supply and demand.A comparison between the surveys found that the information currently being provided by transit agencies is mostly similar to the information most valued by transit passengers. When there were differences between supply and demand it was generally because agencies were not providing information using the same media preferred by. To address these differences, several strategies were developed to try and improve the implementation of real-time information. These include improving public outreach, improving feedback for commuters, providing different cost tiers for information, utilizing alternative sources for the information, and creating passive income through advertising on smartphone applications and websites. Through these findings and strategies, real-time transit information can be better understood. This information can hopefully be used to better develop and prioritize investment in real-time information systems.
... Zhang et al. (2008) revealed that passengers reported increased levels of perceived personal security at night with the introduction of LBAI on the university shuttle bus. Ferris et al. (2010) and Gooze et al. (2013), through web-based surveys, found that in Seattle, Washington the provision LBAI may increase self-reported levels of personal security. ...
... Impacts on ridership: in their studies, Ferris et al. (2010) and Gooze et al. (2013) also found that approximately one third of passengers reported an increase in the number of non-work/school trips per week made on transit because of the introduction of the LBAI. Tang and Thakuriah (2012), through an empirical evaluation of Chicago bus ridership, found a "modest" increase in overall routelevel ridership (126 rides per route per day, which is 1.8-2.2% of average route-level weekday bus ridership) attributable to LBAI. ...
Article
Full-text available
In the past few years, technological changes have made it possible for bus passengers to learn about the expected arrival time when waiting for buses or even before arrival at the stop. In London, live bus arrival information is provided by Countdown signs at over 2500 bus stops. The bus arrival information is also available through Smartphone or tablet apps, the internet and SMS. Though these services are widely used, their impacts on passengers’ perceived waiting time and passengers’ behaviour remain unclear. The objective of this study is to assess how having real-time bus arrival information impacts on both passenger behaviour and how they value their waiting time at the bus stop. To address these research questions, this study is based on a survey containing a stated preference discrete choice experiment, which is supplemented with some qualitative research questions. 1690 completed interviews were achieved. Respondents were either recruited from bus users at bus stops who were invited to participate in an online or telephone survey, or from bus users supplied by TfL from their Oyster user database who were directed to the online survey. Discrete choice models were estimated and the resulting model coefficients quantify how different forms of real-time information impact on respondents’ value of bus waiting time and how the values varied by different sub-groups of population. This study provides up-to-date, London-specific waiting time relative values (multiplier to the in-vehicle time) and provides critical implications in current appraisal of schemes on public transport services investment.
... About 31% of users replied that there were increases in noncommute trips, while few people reported increases in commute trips. A follow-up survey in 2012 has found similar results [9]. An empirical evaluation of a real-time bus information system in Chicago modeled average weekday route-level bus usage for each month from 2002 to 2010 [10]; results showed that the system did increase bus ridership, although the average increase is modest. ...
... Will you adjust the departure time according to the estimated arrival time or the real-time location? (8) Will you choose another route because the next bus is expected to arrive for a long time or too far away?(9) Will you choose to take a taxi or subway because the next bus is expected to arrive for a long time or too far away?(11) ...
Article
Full-text available
The ubiquitous intelligent transportation infrastructure in metropolitan cities has enabled bus passengers to access comprehensive (even real-time) bus information. However, the impact of different types of information on passenger behavior is still insufficiently understood. Combining with the theory of information processing path, this study partially fills this gap by adopting an elaboration likelihood model (ELM) suitable for explaining how the various types of intelligent bus information influence passengers’ choice behavior. Six types of intelligent bus information (information of bus lines, estimated travel time, estimated time of arrival, congestion inside bus, road congestion, and bus fare) are used as six independent variables, and passengers’ departure time, travel routes, and travel modes as dependent variables. Valid questionnaire assessments were collected from 285 participants at 4 bus stops equipped with intelligent bus system in Harbin, providing quantitative data to verify each hypothesis. The results show that six types of intelligent bus information to different degrees (significant influence, slight influence, and no significant influence) affect three types of passengers’ choice behaviors; the information of estimated travel time and that of road congestion are both significantly effective in all three types of choice behavior while bus fare has no significant influence. Meanwhile, other types of information have a significant or slight effect on certain behavior. The results of this study can be used to design more reasonable intelligent bus information provision strategies to meet passengers’ requirements.
... It was also reported that perceived wait times of real-time information users were nearly 30% less than that of non-users. It was also reported that 32% of real-time information users had a positive shift in their perception of personal security (Gooze et al. 2013). 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. ...
... Further, Brakewood et al. (2014) found a median increase of 1.7% for weekday route-level ridership. Gooze et al. (2013) also observed similar results. The impact of real-time information on ridership has been summarized in detail by Brakewood et al. (2015). ...
Article
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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 real-time 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 both theory and practice. Particularly, they are important for transport modelers and service planners to design or adjust the headway for a desired level of service for a given (or a change in) bus arrival information type.
... This would also have a great impact on their commuting pattern (Shannon et al.,2006) and overall travel time. On the other hand, travel times that do not meet the itinerary will negatively impact the user's perception (Gooze et al., 2013). As for Mass Rapid Transport (MRT), the travel time consists of multiple components such as transit time (Ren and Huang., 2020;Tang and Thakuriah, 2011;Gooze et al., 2013), access time, waiting time and transfer time (Fan et al., 2016). ...
... On the other hand, travel times that do not meet the itinerary will negatively impact the user's perception (Gooze et al., 2013). As for Mass Rapid Transport (MRT), the travel time consists of multiple components such as transit time (Ren and Huang., 2020;Tang and Thakuriah, 2011;Gooze et al., 2013), access time, waiting time and transfer time (Fan et al., 2016). Besides that, perceptions of waiting time may vary depending on circumstances on transit attributes such as the transit time and duration, transit schedule and transit count (Ren and Huang, 2020). ...
Article
Full-text available
The use of various public transport usually benefits consumers. However, user consideration over the type of transportation depends on the time factor and time benefit. This paper investigated how time attributes influence the public's consideration of the use of Mass Rapid Transport (MRT) system in Malaysia. The research data has been collected through questionnaire survey at 10 selected MRT stations and secondary data on MRT ridership from the transportation management system. A total of 910 samples from site survey were analyzed with descriptive analysis to see the respondent's score on time attribute. Then all of these time attributes have been applied with correlation analysis to investigate how all of the time attributes affect the MRT usage among the ridership. The results show seven of time attribute has significance on time-saving among MRT's user (<0.00). This time attributes also contribute high impact level on MRT Ridership.
... [26] Past researches suggested that real-time information provision increased ridership because it improves the travel experience. [27] These studies were mostly conducted on an established and more advanced public transportation system such as rail-based Mass Transit system or Bus Rapid Transit system, which possibly generate different behavior from the user. Nevertheless, it is fair to believe that the major benefit from RTI provision would be an increase in ridership. ...
Article
Full-text available
In many developing cities, like Medan, the state of public transportation is considered inadequate and limited to paratransit, locally known as ‘angkot.’ While advanced mass transit systems are still far in the future, improving the paratransit is arguably the most plausible supporting solution at the moment. Paratransit users in Medan have reported to our study that reliability is one of their sources of disappointment. Technological development nowadays should ease the problem through the quality of real-time information provision. In this preliminary study, we conducted surveys to explore users’ perspective and desire for transit information services. Questionnaire responses from 350 tech-savvy users were collected from several centers of activity and terminals. It is as expected that most respondents experienced uncertainty using the current paratransit, and acknowledged the importance of having information services. Further result shows the user’s high expectancy towards information related to fleet location and arriving time estimation. In general, users were willing to use information services if provided regardless of the additional costs. This preliminary study gives a meaningful view of the opportunity to improve public likeness to this local paratransit service. This research is part of research on perception and preference of paratransit user on real-time information provision.
... Since bus travel times inevitably vary, the provision of real-time bus arrival information is one cost-effective way to reduce the disutility associated with the related uncertainty (Litman, 2008;Rahman et al., 2013). A number of studies examined the impact of real-time information in terms of improved perception regarding wait times and increased ridership (Ferris et al., 2010;Tang and Thakuriah, 2012;Gooze et al., 2013;Brakewood et al., 2014). For example, it was reported that perceived wait time at bus stops decreased by 20% due to the provision of real-time information (Dziekan and Vermeulen, 2006). ...
Article
Given the increasing interest in real-time bus arrival information, producing reliable estimation is essential to maximize the benefits of real-time systems. The primary objectives of this paper are to analyze the changes of bus travel time characteristics as pseudo horizon varies and how such characteristics can be applied to real-time bus arrival estimation. In this study, “horizon” refers to the distance between a real-time bus location and a bus stop, whereas “pseudo horizon” refers to the distance from a GPS point to an upstream GPS point. In contrast to existing methods that provide point estimates of bus arrival times, this study provides interval estimates that take into account the uncertainty of future bus arrival times given that early and late buses have their own respective ramifications. A methodology is developed to analyze the bus travel time distribution systematically based on different pseudo horizons since such distributions are critical to producing reliable bus arrival information. The analysis of real transit GPS data shows a significant change in bus travel time characteristics around a pseudo horizon range of 8 km. The analysis of changes in probability densities with pseudo horizons shows that bus travel time distribution converges from a rightly skewed distribution to a more symmetrical distribution from a shorter to a longer pseudo horizon. Lognormal and normal distributions are found to be the best models for before and after a cut-off horizon of 7–8 km, respectively. Instead of a single distribution, the outcomes of this study suggest a combination of probability distributions based on the estimation horizon to be used to provide better bus arrival time estimations.
... According to Zhou et al., (2014), time has become an important consideration among ridership when choosing public transport. It may refer to travelling time that heavily affects the passengers' decisions (Meng et al., 2018;Zhou et al., 2014;Gooze et al., 2013;Ren and Huang, 2020). Besides, saving time on public transport is a prominent factor when choosing the LRT system (Wang & Liu, 2015). ...
Article
Full-text available
Light Rail Transit (LRT) is one of the public transports that provides a lot of benefits to the Malaysian. Yet this consumption depends on the diverse tastes of potential ridership which are influenced by various factors. However, it is very challenging to predict significant factors influencing ridership preferences. As such, the identification of these factors is very important in ensuring this transportation service really attract ridership attention. Thus, this paper intends to identify the main factors that influence ridership preference in taking LRT transportation. 28 attributes have been identified in this research which expands from four (4) main components. Data were collected from ridership’s survey, site observations and ridership statistical data. Pearson Chi-square has been employed to justify the significant status and the influence level of each LRT attribute and component factors toward ridership preference. The results show that 23 attributes recorded a significant status (<0.00) in two (2) different directions of correlation. Overall, three (3) component factors namely i) Comfortable Service, ii) Economics and iii) Indoor Environment Conditions, have influenced and contributed to the same effect on ridership considerations, as compared to the negative effects displayed by the Site Design Attributes.
... Three core goals of the program development were addressing problem resolution, engaging the community, and improving agency-rider communication. Beginning in the fall of 2011, a number of errors with the real-time transit prediction data surfaced, affecting over 77% of a survey of riders (33). While the OneBusAway mobile application included an error reporting function to allow users to identify errors experienced, the amount and quality of the crowdsourced reports began to overwhelm the One BusAway administrators. ...
Article
The participation of a large and varied group of people in the planning process has long been encouraged to increase the effectiveness and acceptability of plans. However, in practice, participation by affected stakeholders has often been limited to small groups, both because of the lack of reach on the part of planners and because of a sense of little or no ownership of the process on the part of citizens. Overcoming these challenges to stakeholder participation is particularly important for any transportation planning process because the success of the system depends primarily on its ability to cater to the requirements and preferences of the people whom the system serves. Crowdsourcing uses the collective wisdom of a crowd to achieve a solution to a problem that affects the crowd. This paper proposes the use of crowdsourcing as a possible mechanism to involve a large group of stakeholders in transportation planning and operations. Multiple case studies show that crowdsourcing was used to collect data from a wide range of stakeholders in transportation projects. Two distinct crowdsourcing usage types are identified: crowdsourcing for collecting normally sparse data on facilities such as bike routes and crowdsourcing for soliciting feedback on transit quality of service and real-time information quality. A final case study exemplifies the use of data quality auditors for ensuring the usability of crowd-sourced data, one of many potential issues in crowdsourcing presented in the paper. These case studies show that crowdsourcing has immense potential to replace or augment traditional ways of collecting data and feedback from a wider group of a transportation system's users without creating an additional financial burden.
... A panel study conducted of the shuttle bus system on the University of Maryland campus showed increased satisfaction with transit service attributable to RTI (Zhang et al. 2008). Additionally, the results of two surveys of bus riders in Seattle who use mobile RTI revealed increased satisfaction with overall bus service (Ferris et al. 2010;Gooze et al. 2013). ...
Article
Prior studies have assessed the impacts of real-time information (RTI) provided to bus and heavy rail riders but not commuter rail passengers. The objective of this research is to investigate the benefits of providing commuter rail RTI. The method is a three-part statistical analysis using data from an on-board survey on two commuter rail lines in the Boston region. The first analysis assesses overarching adoption, and the results show that one-third of commuter rail riders use RTI. The second part conducts difference of means tests and regression analysis on passenger wait times, which reveals that riders’ use of RTI is correlated with a decrease in self-reported “usual” wait times. The third part analyzes 12 quality-of-service indicators, which have a limited relationship with RTI utilization. The results suggest that the benefits of commuter rail RTI are modest. Despite this, many commuter rail riders choose to use this new information source, which has important implications for transit managers considering deploying RTI systems.
... Supporting this notion, previous research found that riders were significantly more satisfied using transit after trying an RTI application, as well as feeling significantly safer while using transit (1). However, while the availability of RTI has the potential to positively affect a rider's transit experience, inaccurate information can also negatively affect that rider's overall satisfaction (14). ...
Article
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Real-time information (RTI) informing transit riders about transit schedules, next bus or train arrivals, and service alerts is increasingly available, particularly through Internet-enabled smartphone applications. Alternative technologies, such as interactive voice response and mobile-based websites, can also provide this information. Currently, the extent of communication technology use by transit riders is largely unknown. Paired with an investigation of cellular phone use by transit riders and the general American population, an analysis of Saint Louis, Missouri, Metro's onboard survey data was conducted to examine riders' communication technology use and to determine how this use may affect rider experience and ridership-generating potential. Additional analyses identified specific demographic groups that would benefit from supplemental technology methods more conducive to their particular information accessibility. Results showed that communication technology use had risen substantially in recent years and that Metro riders who used smartphones or text messaging reported significantly higher levels of satisfaction with service factors, such as the ability to make transfer connections and personal security at transit centers. Specific demographic groups (e.g., riders older than 40 years of age) were less likely to own smartphones, and therefore computer-based websites and interactive voice responses might be the best supplementary alternatives for those groups. The current study emphasizes the growing need for RTI applications in the transit industry and suggests that development of enhanced communication methodologies can positively affect the rider experience. Furthermore, differences in individual technology accessibility call for RTI application development that mirrors the unique characteristics of its ridership.
... The benefits of RTI may be hindered, fail to materialize or even become counterproductive in case of poor information quality. Gooze et al. (2013) found that RTI accuracy has significant impacts on ridership and satisfaction. Furthermore, 38% of public transport users reported an acceptable error of up to 3 min for RTI provision while additional 37% indicated a tolerance of up to 4-5 min. ...
... Brakewood and Watkins (2019) as well identified that, technology-based transit solutions (such as real time transit information) made transit riders generally more satisfied with transit services. Technology-based transit solutions via cellphone [and other personal devices] also increased frequency of transit use (Brakewood et al., 2015a,b;Ferris et al., 2010;Gooze et al., 2013;Tang and Thakuriah, 2012) and feelings of personal safety (Brakewood et al., 2014), while decreasing actual and perceived wait times of transit services (Brakewood et al., 2014;Brakewood et al., 2015a,b;Ji et al., 2017;Watkins et al., 2011). ...
Article
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In Ghana, minibus taxis (trotros) are an important mode of transport that commute about 60% of the traveling public. In spite of their popularity, minibuses are generally inefficient, disorganized and have low service quality. In an attempt to assess service quality of the service, a modified SERVPERF tool was developed. Differences in perceptions of service quality between male and female respondents were also assessed, and the attractiveness of certain technological features as possible remedies to service quality issues were determined. Using an online Google forms version of the modified SERVPERF, responses from nearly one thousand commuters were collected. The link to the questionnaire was dispersed via social media (Whatsapp and Telegram) since the data was collected during the outbreak of COVID-19 in Ghana. Following a factor reduction, the most important service quality factors determined to affect trotro users were (i) Reliability of the service, (ii) Variability in cost and (iii) Responsiveness. Respondents also identified technologies that could help them (a) book, (b) report driver misbehavior, (c) make safe e-payments and (d) track the location of trotros, as most likely to improve their trotro service quality. The findings suggest that some mobility as a service features could have possible benefit for the trotro. The study is however limited in its ability to determine the exact impact of these technologies since it uses a stated preference approach. Future research could explore the willingness of other stakeholder groups such as operators in adopting these technologies since their participation would be key to the success of any such scheme.
... Many early studies focused on the effects of at-stop signage on transit riders' perceptions and behavior (e.g., Hickman and Wilson 1995;Dziekan and Vermeulen 2006;Dziekan and Kottenhoff 2007;Tang and Thakuriah 2011). More recently, the literature pertains primarily to the passenger and transit agency benefits of providing real-time information via mobile and web-based devices (Zhang et al. 2008;Ferris et al. 2010;Watkins et al. 2011;Tang and Thakuriah 2012;Tang, Ross, and Ha 2012;Carrel et al. 2013;Gooze et al. 2013;Brakewood et al. 2014;Brakewood, Macfarlane, and Watkins 2015). Only two prior references have specifically examined backend data from real-time information transit applications, and these are briefly summarized in the following paragraphs. ...
Article
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Smartphone applications that provide transit information are now very popular. However, there is limited research that examines when and where passengers use mobile transit information. The objective of this research was to perform an exploratory analysis of the use of a smart phone application known as Transit App, which provides real-time transit information and trip planning (schedule) functionality. Backend data from Transit App were examined by time of day and day of week in the New York City metropolitan area. The results show that the pattern of both the trip planning feature and overall real-time information usage follow the typical pattern of transit ridership, which has morning and evening peaks. Additionally, self-reported household locations of Transit App users in the New York City area were compared with household socioeconomic characteristics (specifically, income, ethnicity, and age) from census data using GIS visualizations and the Pearson correlation coefficient, but they do not appear to be correlated. This implies that passengers use Transit App regardless of household income, race, or age trends in their neighborhood. This exploratory study examined a rich new data source—backend data from a transit information smartphone application—that could be used in many future analyses to help transit agencies better understand how transit riders use information and plan their trips.
... Generally speaking, the operation of bus systems is prone to be affected by road traffic, which can lead to a lower level of service reliability compared with rail systems. Upon such an operational characteristic, providing the RTI of bus arrival can effectively contain the uncertainty resulting from lower service reliability (Dziekan and Vermeulen, 2006;Mishalani et al., 2006;Gooze et al., 2013). ...
Article
Smartphones and relevant mobile service have greatly influenced people’s daily lives, and intense smartphone users can be commonly seen at transit stops/stations, playing with their smartphones while waiting for buses/trains. This research presents a holistic perspective for analyzing the effects of smartphone usage on transit passengers, which also considers the effects at a psychological level. Such effects may be manifested as the reduction of perceived waiting time at stops/stations against the negative emotionality induced by long waiting, such as boredom and tediousness, so as to result in improved travel experience. An on-site survey is designed and implemented over the bus system in Taipei, Taiwan, to collect the revealed responses of bus passengers in regard to waiting time perception and smartphone usage, particularly for travel-irrelevant mobile service. The survey data are modeled and analyzed in both numerical and verbal representation of perceived waiting time by using a multiple linear regression model and a cumulative proportional odds logistic model, respectively. A finite mixture model is further employed to investigate the potential heterogeneity of waiting time perception related to using smartphones for travel-irrelevant mobile service. The analysis results highlight that travel-irrelevant smartphone usage may lead to the reduction of perceived waiting, and the effect can be more significant for young passengers and those without receiving bus arrival information, especially when waiting time is prolonged. Such findings can contribute to the comprehensive consideration of passenger behavior in transit system planning and associated information/service provision strategies.
... In addition, some findings from the previous study indicate that providing users with access to real-time transit information results in an increase in overall user satisfaction with the transit service, while increasing the frequency of transit usage, decreasing waiting times, and improving the perception of security and personal safety when using the transit service. A follow-up study found that more than 30% of bus riders who had access to real-time information had an increase in their perceived safety and security [14]. ...
Conference Paper
Mobility and accessibility are crucial indicators of urban development. Public transport in the urban areas came into existence to fulfil transportation needs as well as mobility and accessibility demands. Ridership can be affected by the quality and quantity of transit service. However, technical improvements are needed for such as real-time bus information, controlling run time and headway delay. Thus, this paper is aimed to carry out a preliminary survey to determine the problems of school shuttle bus that faced by the students in a selected educational institution, their perceptions of using shuttle bus tracking and information mobile application and impacts of real-time information of public transits on bus ridership and towards smart mobility solutions. Efficient public transportation system needs further investigation about the role of mobile application for the bus tracking system in supporting smart mobility actions and real-time information. The proposed application also provides a smart solution for the management of public infrastructures and urban facilities in Malaysia in future. Eventually, this study opens an opportunity to improve Malaysian quality of life on the public value that created for the city as a whole.
... In addition, RTI can increase public transport ridership (Brakewood et al., 2014(Brakewood et al., , 2015aTang and Thakuriah, 2012), influence their route and mode choice (Caulfield and O'Mahony, 2007;Liebig et al., 2016) while giving them a sense of coordination and safety (Beecroft and Pangbourne, 2015). Though passengers have a tendency to overestimate time spent at bus stops or stations (Cherrett and Gutteridge, 2014), RTI have the capability to reduce waiting time (Chen, 2012;Gooze et al., 2013;Watkins et al., 2011;Bai et al., 2015) thereby allowing them to invest their time that would have been wasted in other things that are profitable to them (Ferris et al., 2010). Also, RTI can change passengers' displeasure about public transport and increase their satisfaction (Dziekan and Vermeulen, 2006;Eboli and Mazzulla, 2007). ...
... OneBusAway started as a project created by graduate students at the University of Washington, and has since spread to more than 10 cities with approximately 340,000 active users. The open-source nature of OneBusAway differentiates it from all other transit applications (e.g., Transit App, Moovit), as it allows researchers to deploy and evaluate solutions designed to enhance and evaluate both the rider and agency experience (1,3,(8)(9)(10)(11)(12). This research provides decision makers with objective evidence to help evaluate and justify investments in new transit technologies. ...
Article
Offering real-time arrival information to riders via mobile applications has been shown to improve the rider’s perception of transit, and even increase ridership. This direct connection to riders also offers the transit agency an opportunity to collect feedback on how transit service and infrastructure can be improved, including pedestrian and bike access to transit. These improvements will lead to an enhanced customer experience and can potentially help address Title VI access equity concerns. However, managing the sheer volume of this rider feedback can be very challenging, especially when various departments and agencies (e.g., city/county government) are involved (e.g., who owns the bench by the bus stop?). This paper discusses the design and deployment of a pilot project in Tampa, Florida, which focused on the improvement of the feedback loop from riders back to transit agencies, local government, and departments of transportation. This project made enhancements to the open-source OneBusAway mobile app, originally deployed in Tampa in 2013, to include support for the Open311 standard for issue reporting. Open311 support gives agencies the option of selecting a hosted issue management solution such as SeeClickFix.com and PublicStuff.com, or the option to utilize existing open-source Open311-compliant software. Lessons learned from regional collaboration surrounding issue reporting and infrastructure improvements are discussed, as are the technical design and challenges behind implementing such a system. The results of the first 6 months of system deployment covering 677 issue reports are presented, including specific examples of cross-jurisdictional and multimodal issues reported by the public.
... Tang and Thakuriah (2012) also observed a 1.8% to 2.2% growth in weekday route-level ridership on the Chicago bus system after a new RTI tool was implemented. These increases in bus ridership as a result of new RTI services seem to be most noticeable on longer bus routes (Brakewood et al., 2015) and for non-commuter trips (Ferris et al., 2010;Gooze et al., 2013). However, some examples in the literature suggest that current transit-dependent passengers do not make any additional bus trips because of new RTI systems (Brakewood et al., 2014;Zhang et al., 2008). ...
Article
Mobility in metropolitan rings is often more car-dependent than in urban cores. Buses are emerging as an efficient option to promote sustainable mobility in metropolitan corridors, although they are perceived as being less reliable than rail or the car. The adoption of real-time information (RTI) tools for passengers can mitigate this issue. This paper aims (i) to explore the potential bus demand in metropolitan corridors, and (ii) to understand how bus passengers use RTI public transport mobile applications. Both aims are oriented to attract more passengers toward public transport. A two-step methodological framework has been established to perform this analysis in the Madrid Region. Data from the 2014 Household Mobility Survey reveal that metropolitan bus potential is three times the current bus ridership, and almost double in transport corridors linked to motorways than in transversal and other metropolitan trips. An ad-hoc survey of bus travelers was conducted in one corridor to capture the use of RTI mobile apps. The results show that multimodal commuters tend to consult several apps, since none of the main apps integrates all the multimodal RTI for their trips. Non-regular bus passengers are more likely to consult a general-purpose app such as Google Maps, while frequent bus commuters prefer to use the official public transport authority app. Improving the multimodal information passengers receive through transit apps could ease their trips and help materialize some of the potential bus demand in metropolitan areas.
... al., 2006) (ii) decreased total travel times (Carrel, et. al, 2013;Cats et al., 2011) (iii) increased transit use Gooze, et al., 2013) (iv) increased satisfaction with transit (Chow, et al., 2012), and (v) increased feelings of safety (Brakewood, et al., 2014;Ferris, et al., 2010). ...
Article
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Mobility-as-a-service (MaaS), is a concept originally developed to enhance transport accessibility through the provision of tailored mobility services that are paid for in one package. Tailored on-demand transport sharing as MaaS proposes, could allow for greater optimization of transportation resources, reduction in congestion, and a shift away from car dependence. In so doing, MaaS can create sustainable consumption and ensure the maximization of otherwise underutilized public transport assets. In the developing world, the concept of MaaS can seem abstract and challenging to implement. This is primarily because the transport forms available in these places are unstructured, informal and often, poorly regulated. Despite this, public transportation options in developing countries stand the chance of benefitting the most from the inclusion of technology in their operations. To implement MaaS in developing countries, there may be a need for a re-envisioning of MaaS itself. Additionally, gaps that can be filled with technology have to be identified, and operator and commuter willingness to adopt technological innovation, determined. This paper explores the opportunities and challenges in implementing MaaS in developing economies and makes recommendations of best-fitting technological solutions for these settings. The paper proposes as well, a conceptual business model for a paratransit-based MaaS, constructed around the current operations of paratransit.
... Bus services, which is one of the most important segments of public transportation, are vulnerable to delays and congestion due to traffic congestion, weather conditions, spe- cial events, etc. Travel and arrival time variation was found to have a substantial impact on commuter satisfaction [4]. Moreover, people's tolerance to errors in bus time predictions is quite low [5]. Providing real-time bus schedules reduces this uncertainty and improves passenger experience and increases ridership. ...
Article
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Public transit is a critical component of a smart and connected community. As such, citizens expect and require accurate information about real-time arrival/departures of transportation assets. As transit agencies enable large-scale integration of real-time sensors and support back-end data-driven decision support systems, the dynamic data-driven applications systems (DDDAS) paradigm becomes a promising approach to make the system smarter by providing online model learning and multi-time scale analytics as part of the decision support system that is used in the DDDAS feedback loop. In this paper, we describe a system in use in Nashville and illustrate the analytic methods developed by our team. These methods use both historical as well as real-time streaming data for online bus arrival prediction. The historical data is used to build classifiers that enable us to create expected performance models as well as identify anomalies. These classifiers can be used to provide schedule adjustment feedback to the metro transit authority. We also show how these analytics services can be packaged into modular, distributed and resilient micro-services that can be deployed on both cloud back ends as well as edge computing resources.
... In addition, RTI can increase public transport ridership (Brakewood et al., 2014(Brakewood et al., , 2015aTang and Thakuriah, 2012), influence their route and mode choice (Caulfield and O'Mahony, 2007;Liebig et al., 2016) while giving them a sense of coordination and safety (Beecroft and Pangbourne, 2015). Though passengers have a tendency to overestimate time spent at bus stops or stations (Cherrett and Gutteridge, 2014), RTI have the capability to reduce waiting time (Chen, 2012;Gooze et al., 2013;Watkins et al., 2011;Bai et al., 2015) thereby allowing them to invest their time that would have been wasted in other things that are profitable to them (Ferris et al., 2010). Also, RTI can change passengers' displeasure about public transport and increase their satisfaction (Dziekan and Vermeulen, 2006;Eboli and Mazzulla, 2007). ...
Article
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The impact of road public transport in urban transportation cannot be ignored, however, the quality of services provided is not high enough. This has made it unattractive to prospective passengers and less competitive to private transport. One of the ways of resolving these challenges with a view to increasing the quality of service is by the provision of platforms that provides travel information in real time to prospective users. This was achieved in this paper using web, mobile, and short messaging service platforms. The developed platforms employed an artificial neural network-based bus arrival time prediction model for predicting bus arrival time. The accuracy of the prediction model was evaluated using mean absolute error and mean absolute percentage error while the performance and impact of the developed platforms were assessed from users' perspective through a survey based on the unified theory of acceptance and use of technology (UTAUT) model.
Book
This book focuses on emerging issues in ergonomics, with a special emphasis on modeling, usability engineering, human computer interaction and innovative design concepts. It presents advanced theories in human factors, cutting-edge applications aimed at understanding and improving human interaction with products and systems, and discusses important usability issues. The book covers a wealth of topics, including devices and user interfaces, virtual reality and digital environments, user and product evaluation, and limits and capabilities of special populations, particularly the elderly population. It presents both new research methods and user-centered evaluation approaches. Based on the AHFE 2016 International Conference on Ergonomics Modeling, Usability and Special Populations, held on July 27-31, 2016, in Walt Disney World®, Florida, USA, the book addresses professionals, researchers, and students dealing with visual and haptic interfaces, user-centered design, and design for special populations, particularly the elderly.
Chapter
Open source mass transit trip planning applications provide real-time transit information for a local community. The application provides local users with an inexpensive and accurate way to predict when their bus will arrive at the bus stop. Researchers and instructors have used the One Bus Away application as an opportunity to form cross-disciplinary development teams similar to the ones that students will experience in professional development environments. The study shares the lessons learned, the guidelines developed, and the best practices for designing transit trip planning interfaces during two implementations. User testing revealed that online mapping applications must support both riders who are familiar with the city (i.e., resident riders), as well as riders who are only visiting (i.e., visiting riders). In both cases, riders must rapidly understand the interface icons and metaphors during significant cognitive stress, environmental stress, and anxiety about missing their bus.
Article
This research explores and attempts to understand transit riders’ behavioural responses towards real-time transit information for two specific situations: the presence of inconsistent information on transit service recovery and the effects of crowded trains during rush hours. A survey was designed and conducted to collect light rail transit (LRT) riders’ behavioural responses in Calgary, Alberta. Multinomial logit models were developed and calibrated to explore the effects of the described scenarios on riders’ responses. The results led to the conclusion that socioeconomic attributes, experience with advanced passenger information system (APIS) system, familiarity with public transit in general and Calgary’s LRT system in particular, and the characteristics of origin LRT stations had strong influences on travellers’ behavioural responses. It was also determined that travellers’ actions vary significantly depending on the purpose of the trip, time of the trip, and weather conditions.
Conference Paper
Smart cities and digital democracy have begun to converge around mobile computing, enabling, web services, and different operational and shared databases to create new opportunities for civic engagement for concerned citizens as well as new efficiencies for public services provided by local government. While many of these projects remain siloed to specific departments of local government, when viewed in aggregate, they begin to fill in a more complex picture of how piecemeal projects are changing the relationship between local government and the public. As an example of this change, we describe our partnership with multiple city and regional agencies in Atlanta. We discuss a pair of projects that together, aim to transform Atlanta’s transportation system by more effectively connecting the public to transportation services and to the processes of infrastructure planning. The projects we present here—Cycle Atlanta and OneBusAway—are part of a larger civic computing agenda where models of digital democracy and smart cities combine to create a data ecosystem where citizens produce and consume different forms of data to enable better infrastructure planning and to enhance alternative modes of transportation.
Article
A two-wave survey of faculty, staff, and students at a large university was conducted to study the perceptions of and attitudes toward several dimensions of the university bus service before and after the implementation of a real-time passenger information system. In this study, community perceptions of the bus service's role in enhancing the environment and reducing traffic were investigated. Results showed that both users and nonusers of the bus service had positive perceptions of the bus service's environmental and traffic reduction roles, that those who noticed the recently implemented real-time information system had more positive attitudes, and that the effect of the information system on the perceptions was as great or greater for those who did not use the bus service as it was for those who used the service. It is hypothesized that these results, especially if confirmed in different communities, could motivate transit agencies to promote environmental and traffic reduction benefits of transit to gain public support of nonusers for transit subsidies and to market high-tech and progressive investments to increase support among nonusers.
Article
In 2001, the San Francisco Municipal Transportation Agency (SFMTA) revolutionized the transit riding experience by implementing its first-generation customer information system to predict when its Muni transit vehicles would arrive in real time. Since then, mobile technologies have ushered in on-demand ride-hailing services and raised expectations for transit service quality. Seeking to stabilize and increase ridership, transit operators like SFMTA are working to adapt and innovate in this rapidly changing environment. SFMTA is now embarking on the next generation of real-time customer information. To guide this multi-million dollar investment, SFMTA conducted extensive quantitative and qualitative research to design new system features and uncover how they could shape travel behavior. An in-depth survey of 5,856 Muni customers revealed that income is a primary mode-choice driver, coupled with the relative availability of ride-hailing services. As income rises, the propensity to wait for Muni decreases, particularly when nearby ride-hailing options are plentiful. Applicable to other cities, this research also affirmed that better real-time information such as alternative routes and transfer connections could increase ridership overall, potentially reducing demographic influences on mode choice and fostering a more equitable and sustainable transportation system. Informed by this research, SFMTA’s new system will focus on improving prediction accuracy, keeping customers informed throughout their journey, and developing a transit-focused mobile app.
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Transit apps are cost-efficient strategies to facilitate transit use. This study is the first systematic review that synthesises the literature on these apps’ end-user benefits. We identified limitations in the existing knowledge in terms of study methods, population, and scopes. This review offers insights to guide researchers and policymakers to unlock the potential of transit apps in promoting the use and experience of public transit. We conducted the literature searches in August 2020, covering studies published between 2010 and 2020 from TRID, Compendex, Business Source Ultimate Ebsco, and Acad Search Ultimate Ebsco. Articles were screened and reviewed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. In total, 13 out of 3,812 articles met our pre-specified eligibility criteria. We identified key user benefits in three domains: perception and psychological changes, time savings on trips, and travel behaviour changes. These studies found that smartphone transit apps may improve the perceived reliability of transit services, increase perceived safety, reduce anxiety while waiting, and build a positive image of transit. Also, transit apps could help users reduce wait time at transit stops. Studies further reported that smartphone transit apps have the potential to boost ridership. After critically assessing the articles, we recommended future studies to improve study designs, adjust study populations, and expand study scopes. First, future studies about travel behaviour impacts would need to adopt more rigorous study designs and methods. Second, more studies about infrequent riders and non-riders are needed. Third, current studies have not paid enough attention to the important subgroup of captive riders, such as riders in rural areas who rely on infrequent and unreliable transit services. Fourth, more empirical evidence is needed to quantify the impacts of public sector transit apps. Trip planning and mobile ticketing functions of transit apps are overlooked. Fifth, the established theoretical framework about travel behaviours and emerging technologies could serve as solid theoretical bases and would need to be integrated into future research designs.
Chapter
Nepal is rapidly urbanizing. Until 2014, only 20% of the total population lived in urban areas, but in 2015, over 65% of people were classified as urban dwellers with the promulgation of the constitution of the Federal Republic of Nepal (FRN). Many rural areas are annexed together to meet the population thresholds of some territories in order to classify them as municipals. As of 2017, many of the existing local level political units (which were over 3700) have been combined together reducing the local political units to 753 in total. Until 2014, there were only 105 urban units, but when local political units were decreased to 753 as per the FRN, the number of urban units jumped from 105 to 293 with 276 municipalities, 11 sub-metropolises, and 6 metropolises. However, many of these so classified urban areas are characterized by ruralopolises where people living in rural settings within the legally defined urban areas are competing for the limited facilities of the urban cores. Despite such competition for limited resources/facilities, many of the ruralopolises are aspiring to becoming “smart cities.” However, political leaders and urban planners responsible for the planning of these ruralopolises have been struggling to have real-time geospatial data, one of the essential components of “smart cities.” A “smart city” is an integrated system in which human and social capitals interact, using technology-based solutions. It efficiently achieves sustainable and resilient development and helps maintain a high urban life quality based on a multi-stakeholders’ partnership. The “smart city” initiatives need real-time data that uses auto-sensor state-of-the-art technology. The economic outcomes of a “smart city” initiative results in the simplification of daily working schedules such as bus routing, waste disposal, creation of businesses, jobs, and infrastructure. The brain of a “smart city” includes the virtual real-time data center-fed by an automated sensor network that regulates kiosks, parking meters, cameras, smart phones, medical devices, social networks, and bus routings.
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The bus services in most of the cities in emerging countries are facing challenges in terms of financial viability and ridership. On the other hand, the increasing usage of private vehicle is aggravating the congestion and pollution in the urban areas. Therefore, there is a need for improving the bus service in accordance to the requirement of commuters in order to make it an attractive mode of transport. The paper presents an investigation on trip makers’ preference heterogeneity towards various attributes of bus service using stated preference choices, identify the differences in trip makers’ requirements based on trip, socioeconomic, and demographic characteristics, and accordingly suggest suitable policy measures for improving bus service. The stated preference data were analyzed by developing random parameter logit (RPL) models accounting for heterogeneity, and trip makers’ Willingness-to-pay (WTP) for improving bus service attributes were calculated. The study reveals existence of significant heterogeneity in commuters’ perceptions towards improving different attributes of bus service with respect to trip purpose, age, gender, and frequency of using bus. Trip makers’ WTP for time savings was found higher for work trips indicating the need for adopting efficient traffic management measures during peak hours. Female commuters were found to value comfort during travel much higher as compared to male commuters which justifies the existing ‘female only’ seat reservation policy in Kolkata and emphasizes the need for further initiatives such as women special services, especially during peak hours.
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The report explores the underlying technology required to generate the information to be disseminated, the mobile technology used for dissemination, the characteristics of the information, the resources required to successfully deploy information on mobile devices, and the contribution of mobile messaging to an overall agency communications strategy, including “information equity.”
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In this article a tool for measuring customer satisfaction in public transport is proposed. Specifically, a structural equation model is formulated to explore the impact of the relationship between global customer satisfaction and service quality attributes. The public transport service analyzed is the bus service habitually used by University of Calabria students to reach the campus from the urban area of Cosenza (southern Italy). To calibrate the model, some data collected in a survey addressed to a sample of students were used. The proposed model can be useful both to transport agencies and planners to analyze the correlation between service quality attributes and identify the more convenient attributes for improving the supplied service.
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In this paper, using longitudinal data on route level monthly average weekday ridership in the entire Chicago Transit Authority (CTA) bus system from January 2002 through December 2010, we evaluate the ridership effects of the CTA real-time bus information system. This bus information system is called CTA Bus Tracker and was incrementally implemented on different CTA bus routes from August 2006 to May 2009. To take account of other factors that might affect bus ridership, we also include data on unemployment levels, gas prices, local weather conditions, transit service attributes, and socioeconomic characteristics during the study period. This combined longitudinal data source enables us to implement a quasi-experimental design with statistical controls to examine changes in monthly average weekday ridership, before and after the Bus Tracker system was implemented, on each bus route. Based on a linear mixed model, we found that the provision of Bus Tracker service does increase CTA bus ridership, although the average increase is modest. Further, the study findings suggest that there are temporal variations of the ridership effects among the routes, with the “winning” routes more likely to have the technology implemented in the later phases of the overall “roll-out” period. However, the results are less conclusive regarding geographical variations in the effects of Bus Tracker.
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Information about bus travel time and its variability is a key indicator of service performance, and it is valued by passengers and operators. Despite the important effect of traffic flow on bus travel time, previous predictive approaches have not fully considered a traffic measure making their predictions unresponsive to the dynamic changes in traffic congestion. In addition, existing methodologies have primarily concerned predicting average travel time given a certain set of input values. However, predicting travel-time variability has not received sufficient attention in previous research. This article proposes an integrated framework to predict bus average travel time and its variability on the basis of a range of input variables including traffic flow data. The framework is applied using GPS-based travel-time data for a bus route in Melbourne, Australia, in conjunction with dynamic traffic flow data collected by the Sydney Coordinated Adaptive Traffic Systems loop detectors and a measure of schedule adherence. Central to the framework are two artificial neural networks that are used to predict the average and variance of travel times for a certain set of input values. The outcomes are then used to construct a prediction interval corresponding to each input value set. The article demonstrates the ability of the proposed framework to provide robust prediction intervals. The article also explores the value that traffic flow data can provide to the accuracy of travel-time predictions compared with when either temporal variables or scheduled travel times are the base for prediction. While the use of scheduled travel times results in the poorest prediction performance, incorporating traffic flow data yields minor improvements in prediction accuracy compared with when temporal variables are used.
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Many large cities in Korea have either implemented or are planning to install a bus information system (BIS) in order to improve the quality of service for bus passengers. This is mainly being conducted by providing bus arrival times at bus stops. In these systems, similar systematic errors occur in the estimation of bus arrival times, which are influenced by the information updating time (cycle length) taken to identify each bus location, the information processing time, and the cycle length required to update the bus arrival information on each terminal. The systematic errors can occur in the collection of data, information processing, and in the passenger waiting time. This study investigated these systematic errors and developed a statistical method for correcting these errors in order to improve the accuracy of the BIS information. The proposed method is based on probability density functions and the random incidence concept. The developed method was then applied to the BIS of a city in Korea in order to verify the efficacy of the method. Through the verification results, there was a 23% error reduction after applying the error correction method to the BIS. Copyright © 2010 John Wiley & Sons, Ltd.
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A major component of ATIS is travel time information. The provision of timely and accurate transit travel time information is important because it attracts additional ridership and increases the satisfaction of transit users. The objectives of this research are to develop and apply a model to predict bus arrival time using automatic vehicle location (AVL) data. In this research, the travel time prediction model considered schedule adherence and dwell times. Actual AVL data from a bus route located in Houston, Texas was used as a test bed. A historical data based model, regression models, and artificial neural network (ANN) models were used to predict bus arrival time. It was found that ANN models outperformed the historical data based model and the regression models in terms of prediction accuracy.
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In this paper we present a general prescription for the prediction of transit vehicle arrival/departure. The prescription identifies the set of activities that are necessary to preform the prediction task, and describes each activity in a component based framework. We identify the three components, a Tracker, a Filter, and a Predictor, necessary to use automatic vehicle location (AVL) data to position a vehicle in space and time and then predict the arrival/departure at a selected location. Data, starting as an AVL stream, flows through the three components, each component transforms the data, and the end result is a prediction of arrival/departure. The utility of this prescription is that it provides a framework that can be used to describe the steps in any prediction scheme. We describe a Kalman filter for the Filter component, and we present two examples of algorithms that are implemented in the Predictor component. We use these implementations with AVL data to create two examples of transit vehicle prediction systems for the cities of Seattle and Portland.
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Public subsidy of transit services has increased dramatically in recent years, with little effect on overall ridership. Quite obviously, a clear understanding of the factors influencing transit ridership is central to decisions on investments in and the pricing and deployment of transit services. Yet the literature about the causes of transit use is quite spotty; most previous aggregate analyses of transit ridership have examined just one or a few systems, have not included many of the external, control variables thought to influence transit use, and have not addressed the simultaneous relationship between transit service supply and consumption. This study addresses each of these shortcomings by (1) conducting a cross-sectional analysis of transit use in 265 US urbanized areas, (2) testing dozens of variables measuring regional geography, metropolitan economy, population characteristics, auto/highway system characteristics, and transit system characteristics, and (3) constructing two-stage simultaneous equation regression models to account for simultaneity between transit service supply and consumption. We find that most of the variation in transit ridership among urbanized areas – in both absolute and relative terms – can be explained by factors outside of the control of public transit systems: (1) regional geography (specifically, area of urbanization, population, population density, and regional location in the US), (2) metropolitan economy (specifically, personal/household income), (3) population characteristics (specifically, the percent college students, recent immigrants, and Democratic voters in the population), and (4) auto/highway system characteristics (specifically, the percent carless households and non-transit/non-SOV trips, including commuting via carpools, walking, biking, etc.). While these external factors clearly go a long way toward determining the overall level of transit use in an urbanized area, we find that transit policies do make a significant difference. The observed range in both fares and service frequency in our sample could account for at least a doubling (or halving) of transit use in a given urbanized area. Controlling for the fact that public transit use is strongly correlated with urbanized area size, about 26% of the observed variance in per capita transit patronage across US urbanized areas is explained in the models presented here by service frequency and fare levels. The observed influence of these two factors is consistent with both the literature and intuition: frequent service draws passengers, and high fares drive them away.
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This paper reports a conjoint analysis study that tested the hypothesis that the burden of waiting for transit will decrease as traveler certainty with respect to wait duration increases, i.e., with provision of real-time transit schedule information. Conjoint analysis has been used extensively as a means to evaluate individual preference or utility. The target audience for the conjoint study, which was carried out through the US mail in the Spring of 1994, consisted of 1000 randomly sampled employees on the University of Michigan Medical Campus. The conjoint data and the model developed through the study show that real-time transit schedule information is of potentially significant value to transit customers in that the burden of a given wait decreases as the degree of certainty about the duration of the wait increases. This result should further motivate transit system designers to redouble efforts to provide real-time transit schedule information. This is especially true since such information could also reduce the duration of the wait. Moreover, the conjoint model developed acts as an inferential tool for further investigating the relationship between information, reliability, and travel time and should be of significant value in transit system design
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The Seattle model deployment initiative has created a new technology for data sharing in an ITS environment. This technology, the ITS Backbone that uses Self Describing Data (http:/ /www.its.washington.edu/bbone/), creates a framework in which to build applications. These applications use Self Describing Data (SDD) to obtain real-time data over the Internet to perform functions ranging from ATMS to ATIS. Since the applications depend only on knowledge of SDD, they are portable to any jurisdiction where SDD is employed as the data transfer support. (SDD information and software are available for download from the ITS Backbone page noted above.) This paper describes the implementation of two such portable applications. INTRODUCTION As part of the Seattle Smart Trek model deployment, two new applications where created to provide real-time transit information. The two venues where transit riders need information are (1) on the desktop and (2) at the transit center. The first project, Busv...
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