Proceedings Article•
A framework for the development of bus service reliability measures
01 Jan 2013-pp 1-15
TL;DR: In this paper, the authors proposed a buffer time concept based reliability measurement framework using AVL data, which can disaggregate service performance to a high level of detail, and developed three example indicators for applications of reliability assessment (operators), journey planning (passenger) and value of time (agencies).
Abstract: Reliability of transit service has been recognized as a significant determinant of quality of service. Numerous indicators have been proposed by individual operational organizations and the research community dependent on specific objectives and resource constraints. Buffer time based indicators are highly desirable since they enable evaluation of the reliability impacts on passengers from an operational approach. However, buffer time indicators can underestimate passengers perceived reliability performance and hide the sources of observed changes in reliability if the buffer time is based on the total travel time distribution. Large samples of disaggregated data, benefiting from Automatic Vehicle Location (AVL) system, provide great potential to measure reliability at very high levels of resolution. The paper proposes a buffer time concept based reliability measurement framework using AVL data, which can disaggregate service performance to a high level of detail. The framework working procedure is illustrated in the case of AVL data from Brisbane. Three example indicators for applications of reliability assessment (operators), journey planning (passenger) and value of time (agencies) are developed to fulfil different stakeholders’ requirements.
Citations
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01 Jan 2012
TL;DR: A systematic review of the current state of research in travel time reliability, and more explicitly in the value oftravel time reliability is presented.
Abstract: Travel time reliability is a fundamental factor in travel behavior. It represents the temporal uncertainty experienced by users in their movement between any two nodes in a network. The importance of the time reliability depends on the penalties incurred by the users. In road networks, travelers consider the existence of a trip travel time uncertainty in different choice situations (departure time, route, mode, and others). In this paper, a systematic review of the current state of research in travel time reliability, and more explicitly in the value of travel time reliability is presented. Moreover, a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.
352 citations
01 Jul 2010
TL;DR: In this paper, the authors proposed the use of alternative statistical distributions for travel time variability, with the Burr Type XII distribution emerging as an appropriate model for both links and routes for both urban arterial road corridors in Adelaide, Australia.
Abstract: Reliability is an important factor in route choice analysis and is a key performance indicator for transport systems. However, the current parameters used to measure travel time variability may be not sufficient to fully represent reliability. Better understanding of the distributions of travel times is needed for the development of improved metrics for reliability. A comprehensive data analysis involving the assessment of longitudinal travel time data for two urban arterial road corridors in Adelaide, Australia demonstrates that the observed distributions are more complex than previously assumed. The data sets demonstrate strong positive skew, very long upper tails, and sometimes bimodality. This paper proposes the use of alternative statistical distributions for travel time variability, with the Burr Type XII distribution emerging as an appropriate model for both links and routes.
26 citations
TL;DR: A detailed review of BRTS implementation in cities of India is attempted to give a systematic effort that could inform readers about the current system and network characteristics of Indian BRTS.
Abstract: Between 2008 and 2015, bus rapid transit system (BRTS) in India increased its implementation from two cities to eight cities with a significant increase in total ridership. This paper attempts to g...
21 citations
Cites background from "A framework for the development of ..."
...As these systems are segregated from other traffic, the peak and off peak periods depends upon the ridership of the system, hence a modified form of PTI is provided in the literature (Ma et al., 2013)....
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...Mahadevia et al. (2012) reports that Jaipur and Indore started as open systems but now are in line to being converted into a closed system....
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TL;DR: The results indicate that O/D-based travel time variability can be characterized and that higher variability occurs during peak hours, and suggest directions for future research and implementation of policies.
12 citations
TL;DR: A four quadrant approach is used to summarize various public transport reliability measures including the factors responsible for causing variability in the travel time using both Intelligent Transportation System (ITS) data and stated preference data to measure reliability.
Abstract: The aim of this paper is to review various public transport reliability measures including the factors responsible for causing variability in the travel time. A four quadrant approach is used to summarize various reliability measures. These indicators use both Intelligent Transportation System (ITS) data and the stated preference data to measure reliability. Further various supply and demand side factors causing uncertainties in travel time are listed and discussed. In the end a brief case study on two routes of Bus Rapid Transit System(BRTS) of Ahmedabad is reported to apply and test the reviewed travel time measures on the ITS data.
9 citations
References
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TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Abstract: The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the MAICE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of AIC defined by AIC = (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAICE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utility of MAICE in time series analysis is demonstrated with some numerical examples.
47,133 citations
"A framework for the development of ..." refers methods in this paper
...The goodnessof-fit Akaike information criterion (AIC) value verified the superiority of mixture model (-542) than Log-normal (-584) in fitting travel time distribution under AM peak WD-IN pattern (Akaike, 1974)....
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01 Jan 2011
TL;DR: In this paper, the authors reviewed the history of statistical hypothesis testing in time series analysis and pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification.
Abstract: The history of the development of statistical hypothesis testing in time series analysis is reviewed briefty and it is pointed out that the hypothesis testing procedure i. not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum informatioD theoretical criterion (AlC) estimate (MAleE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the M.AleE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of Ale defined by Ale ~ (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAleE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utllity of MAIeE in time series analysis is demonstrated with some numerical
4,406 citations
TL;DR: In this article, the authors review progress made towards a general theory of the traveller's valuation of travel time reliability, and give some indication of recent empirical research in this area, bringing together a large number of theoretical and empirical results, many of which are only partly in the public domain.
Abstract: The paper reviews progress made towards a general theory of the traveller's valuation of travel time reliability, and give some indication of recent empirical research in this area. In the progress it brings together a large number of theoretical and empirical results, many of which are only partly in the public domain. Key theoretical results relating to the highway mode are discussed, and expanded to take in the additional complexity of scheduled public transport services. The paper also deals with the problems of collecting empirical data, and describes a recent study carried out by the authors in the context of rail travel, showing how valuations can be derived.
869 citations
"A framework for the development of ..." refers background in this paper
...…(Hollander, 2006; Mazloumi et al., 2008), others related it to maintaining headway regularity (Janos & Furth, 2002; Yu et al., 2010), adherence to the timetable or on-time performance (Bates et al., 2001; Meyer, 2002), and passenger waiting time at stops (Fan & Machemehl, 2009; Furth et al., 2006)....
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..., 2010), adherence to the timetable or on-time performance (Bates et al., 2001; Meyer, 2002), and passenger waiting time at stops (Fan & Machemehl, 2009; Furth et al....
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Book•
04 Jun 2007
TL;DR: In this paper, the authors present an introduction to transit service planning, Data Requirements and Collection Frequency and Headway Determination, Timetable Development, Advanced Timetables I: Maximum Passenger Load, AdvancedTimetables II: Maximum Synchronization, Vehicle Scheduling I: Fixed Schedules, Vehicle Schedule II: Variable Schedules.
Abstract: Preface, Introduction to Transit Service Planning, Data Requirements and Collection Frequency and Headway Determination, Timetable Development, Advanced Timetables I: Maximum Passenger Load, Advanced Timetables II: Maximum Synchronization, Vehicle Scheduling I: Fixed Schedules, Vehicle Scheduling II: Variable Schedules, Vehicle-type and Size Considerations in Vehicle Scheduling, Scheduling, Passenger Demand, Route Choice and Assignment, Service Design and Connectivity, Network (Routes) Design, Designing Short-turn trips, Smart Shuttle and Feeder Service, Service Reliability and control, Future Developments in Transit Operations, Answers to Exercises, Index
444 citations
"A framework for the development of ..." refers background in this paper
...Transfer waiting time usually serves as a transfer time reliability indicator (Ceder, 2007; Goverde, 1999)....
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...Ceder (2007) identified six time-related service attributes concerned by demand-side and supply-side, namely, on-time performance, headway regularity, travel time, waiting time, transfer time and buffer time....
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TL;DR: In this paper, the problem of determining the optimal strategy (dispatch or hold) for a system of m vehicles is formulated as a dynamic programming problem and analyzed in detail for m = 1 and m = 2.
Abstract: Vehicles load passengers at a single service point and, after traversing some route, return for another trip. The travel times of successive trips are independent identically distributed random variables with a known distribution function. After a vehicle returns to the service point, one has the option of holding it, or dispatching it immediately. Passengers arrive at a uniform rate and the objective is to minimize the average wait per passenger. The problem of determining the optimal strategy (dispatch or hold) for a system of m vehicles is formulated as a dynamic programming problem. It is analyzed in detail for m = 1 and m = 2. For m = 1, the optimal strategy will hold a vehicle if it returns within less than about half the mean trip time. For m = 2, and for a small coefficient of variation of trip time C(T), the optimal strategy will control the vehicles so as to retain nearly equally spaced dispatch times, within a range of time proportional to C4/3(T).
410 citations
"A framework for the development of ..." refers background or methods in this paper
...…1999) and percentage regularity deviation mean (van Oort & van Nes, 2004), while others are defined based on headway distribution, such as standard deviation, coefficient of variance, average waiting time (Osuna & Newell, 1972) and probability-based headway regularity measure (Lin & Ruan, 2009)....
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...Under irregular vehicle arrival condition, the AWT is calculated as 2 2AWT 1 2s , where is mean headway and 2s is headway variance (Osuna & Newell, 1972)....
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...In these circumstances, passengers are prone to arrive at stops randomly, and the aggregate waiting time of passengers is minimized when services are evenly spaced (Osuna & Newell, 1972)....
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