Bus Drivers’ Responses to Real-Time Schedule Adherence and the Effects on Transit Reliability

Ji, Yuxiong; He, Lihang; Zhang, H Michael

doi:10.3141/2417-01

Cited by 13 publications

(4 citation statements)

References 8 publications

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“…Moreover, non-linearity in dwell time and driver behavior patterns could be embedded into the prediction scheme to better capture the complexity of public transport dynamics. There is empirical evidence that drivers adjust their speed in response to RTI on schedule adherence (Cats et al 2012, Ji et al 2014. This driving pattern could be potentially accounted for in future prediction schemes in line with Lin and Bertini (2004).…”

Section: Discussionmentioning

confidence: 99%

Evaluating the added-value of online bus arrival prediction schemes

Cats

Loutos

2016

Transportation Research Part A: Policy and Practice

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Online predictions of bus arrival times have the potential to reduce the uncertainty associated with bus operations. By better anticipating future conditions, online predictions can reduce perceived and actual passenger travel times as well as facilitate more proactive decision making by service providers. Even though considerable research efforts were devoted to the development of computationally expensive bus arrival prediction schemes, real-world real-time information (RTI) systems are typically based on very simple prediction rules. This paper narrows down the gap between the state-of-the-art and the state-of-the-practice in generating RTI for public transport systems by evaluating the added-value of schemes that integrate instantaneous data and dwell time predictions. The evaluation considers static information and a commonly deployed scheme as a benchmark. The RTI generation algorithms were applied and analyzed for a trunk bus network in Stockholm, Sweden. The schemes are assessed and compared based on their accuracy, reliability, robustness and potential waiting time savings. The impact of RTI on passengers waiting times are compared with those attained by service frequency and regularity improvements. A method which incorporates information on downstream travel conditions outperforms the commonly deployed scheme, leading to a 25% reduction in the mean absolute error. Furthermore, the incorporation of instantaneous travel times improves the prediction accuracy and reliability, and contributes to more robust predictions. The potential waiting time gains associated with the prediction scheme are equivalent to the gains expected when introducing a 60% increase in service frequency, and are not attainable by service regularity improvements.

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Section: Discussionmentioning

confidence: 99%

Evaluating the added-value of online bus arrival prediction schemes

Cats

Loutos

2016

Transportation Research Part A: Policy and Practice

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“…Such schedule recovery effort is widely adopted in the context of advanced public transport systems (APTS) (e.g. Yan et al, 2012;Lin and Bertini, 2004;Chen et al, 2005;Ji et al, 2014). However, to simplify the model, in this study we use a continuum approach to develop a closed-form expression to capture such interaction; we describe the approach in the model formulation section.…”

Section: Problem Descriptionmentioning

confidence: 99%

Designing robust schedule coordination scheme for transit networks with safety control margins

Liu

Jin

2016

Transportation Research Part B: Methodological

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We propose a robust schedule coordination scheme which combines timetable planning with a semiflexible departure delayed control strategy in case of disruptions. The flexibility is provided by allowing holding for the late incoming bus within a safety control margin (SCM). In this way, the stochastic travel time is addressed by the integration of real-time control and slacks at the planning phase. The schedule coordination problem then jointly optimises the planning headways and slack times in the timetable subject to SCM. Analytical formulations of costs functions are derived for three types of operating modes: uncoordinated operation, departure punctual control and departure delayed control. The problem is formulated as a stochastic mixed integer programming model and solved by a branch-and-bound algorithm. Numerical results provide an insight into the interaction between SCM and slack times, and demonstrate that the proposed model leads to cost saving and higher efficiency when SCM is considered. Compared to the conventional operating modes, the proposed method also presents advantages in transfer reliability and robustness to delay and demand variation.

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“…The reduction in tram travel time was obtained without sacrificing the mobility of through traffic. Empirical studies have revealed that transit drivers would respond positively to real-time information to keep on schedule [28]. That is, drivers will adjust speeds along the roadways and dwell times at stations to keep on schedule.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Tram-Oriented Traffic Signal Timing Resynchronization

Tang

Wang

et al. 2018

Journal of Advanced Transportation

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Modernized trams usually run on exclusive rail lanes along urban streets, but they share the right of way with general vehicles at intersections and often get interrupted by traffic signals. We developed a mixed integer model to resynchronize traffic signal timings to favor tram movements. The objective is to balance the operational needs between minimizing bidirectional tram travel times and reducing the likelihood of activating the green extensions. The model depicts both tram and vehicle progressions in one signal timing plan, making it possible to control the impact of signal timing resynchronization through traffic. Trams following the tram bands produced by the proposed model are prevented from being stopped by red phases at signalized intersections. The applicability and effectiveness of the proposed model were demonstrated in a real-world case study. Compared with the state-of-the-art practice approach, the developed model reduced tram travel time by 10% with lower negative impacts on traffic on side streets. The reduction in tram travel time was obtained without sacrificing the mobility of through traffic.

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Bus Drivers’ Responses to Real-Time Schedule Adherence and the Effects on Transit Reliability

Cited by 13 publications

References 8 publications

Evaluating the added-value of online bus arrival prediction schemes

Evaluating the added-value of online bus arrival prediction schemes

Designing robust schedule coordination scheme for transit networks with safety control margins

Tram-Oriented Traffic Signal Timing Resynchronization

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