1,720,986 research outputs found
Rethinking Bus Punctuality by integrating Automatic Vehicle Location Data and Passenger Patterns
No full textThis paper investigates punctuality at bus stops. Although it is typically evaluated from the
point of view of bus operators, it must also account for users, as required in recent service
quality norms. Therefore, evaluating punctuality at bus stops is highly important, but may
also be a complex task, because data on both bus arrivals (or departures) and users must be
taken into account and processed. Data on buses can be collected by Automatic Vehicle
Location (AVL) systems, but several challenges must be addressed in order to use them
effectively. Passengers data at bus stops cannot be derived from AVL, but they can be used
to derive passenger patterns and need to be integrated into processed AVL data. This paper
proposes a new punctuality measure defined as the fraction of passengers who will be
served within an acceptably short interval after they arrive. A method is proposed to determine
this measure: it provides (i) several rules to handle AVL collected data, (ii) a procedure
integrating processed AVL data and potential passengers’ patterns and (iii) a
hierarchical process to perform the punctuality measure on each bus route direction of a
transit network, as well as for every bus stop and time period. The paper illustrates the
experimentation of this method on more than 4,000,000 data of a real bus operator and
represents outcomes by easy-to-read control dashboards
An offline framework for the diagnosis of time reliability by automatic vehicle location data
No full textTime reliability problems are unavoidable, owing to the stochastic context in which bus services are operated. Therefore, characterizing their reliability and understanding possible sources of unreliability provides an opportunity to keep buses on schedule and/or maintain planned headways. Measuring time reliability is technologically feasible by automatic vehicle location (AVL) systems, which can collect disaggregated data on the delivered service and disclose information on its performance. This paper proposes the first offline framework applicable to any bus route in order to accurately characterize the bus stops and the time periods in which reliability is insufficient, and to disclose the systematic unreliability sources from collected AVL data and select preventive strategies, accordingly. The framework is tested on the real case study of a bus route, using about 40 000 AVL data records provided by the bus operator CTM in Cagliari, Italy. The experimentation shows that this framework can be adopted by transit managers for accurate reliability analysis
An offline framework for handling automatic passenger counting raw data
No full textKnowledge of ridership data on bus routes is pivotal for the quality and efficient operational planning of public transport companies. Automatic passenger counting (APC) can represent a powerful resource for supporting this activity, because it can provide a databank of accurate counts. However, relevant challenges, such as the matching of data to the bus stop, data validation, tackling anomalies, and building intelligible performance reports, must be faced in order to make APC data a mainstream source of information. This paper proposes an offline framework for addressing these challenges. In order to illustrate a possible application of the framework, its use for setting bus frequencies is investigated. The results are represented by easy-to-read control dashboards composed of tables and graphs. The methodology is experimentally tested with data records provided by the bus operatorCTMinCagliari,Italy.Finally,wediscusstheimplicationson service rearrangement
Regularity diagnosis by Automatic Vehicle Location raw data
No full textBus regularity is a crucial factor for high frequency public transport systems, because it represents a relevant measure of quality of service for both users and transit agencies. Low regularities for users are associated with bunching phenomena or large gaps between buses, which result in low attractiveness of the service for transit agencies. Therefore, evaluating the regularity is extremely desirable, but may also be a complex task in medium-size cities due to the huge amount of data which must be collected and processed effectively. Automatic Vehicle Location (AVL) technologies, which are particularly used by transit agencies in Western Europe, can address the data collection problem, but they involve several challenges such as correcting anomalies in collected raw data and processing information efficiently. In this paper, we propose a method to automatically handle AVL raw data for measuring the Level of Service (LoS) of bus regularity at each bus stop and time interval of any high frequency route. The results are represented by easy-to-read control dashboards and graphs.We discuss the experimentation of this method in a real case study to provide insights into the detailed characterization of bus regularity. The method is applied to data obtained from the transport agency CTM in Cagliari (Italy), whose vehicles are all equipped with AVL technologies
Regularity analysis on bus networks and route directions by automatic vehicle location raw data
No full textBus regularity is a key element for high-frequency transportation systems: it represents a measure of service quality for
both users and transit agencies. Therefore, evaluating the regularity is highly important, but may also be a complex task in
medium-size cities, because of the huge amount of data, which must be collected and processed effectively. Automatic
vehicle location (AVL) technologies can address the data collection problem, but they involve several challenges such as
correcting anomalies in gathered raw data and processing information efficiently. In this study, the authors propose a
methodology to handle AVL raw data in order to measure the level of service of bus regularity in each route direction of a
transit network, as well as in every bus stop and time period. The results are represented by easy-to-read control dashboards.
The authors discuss the experimentation of this methodology to provide a detailed characterisation of bus regularity. The
methodology is applied to about 800 000 data records of the bus operator CTM in Cagliari (Italy)
A framework to measure transit service quality areas to be managed
No full textThis paper addresses the development of public transportation quality management programmes in Europe, building on the theoretical framework of the EN 13816 standard, and is potentially helpful to transit operators for measuring and diagnosing quality areas concerning service attributes. The ‘new’ framework: 1) provides guidelines for the selection of the attributes and the data collection and processing techniques related to desired, targeted, delivered and perceived quality areas; 2) integrates the perspectives of both operators and users in a unifying manner (e.g., measuring the same quality attribute in objective and subjective ways), evaluating quality from the passenger’s perspective; 3) allows the EN 13816 ‘quality loop’ to be closed through concurrent analysis of four resulting gaps between the quality areas. To our knowledge, these issues have never been addressed in a single study.
Therefore, the study manages to address a relevant weakness in transit literature. Application of the framework is illustrated using data from an Italian
bus operator, collected on a high-frequency route. It provides transit operators with a ready-to-use tool to monitor quality areas in need of improvement and
can be generalised to services other than transit
La qualità del servizio di trasporto collettivo: lo standard 13816 ed un approccio metodologico ad un caso italiano / The quality of public transport service: the 13816 standard and a methodological approach to an Italian case
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