An agent-based model for real-time bus stop-skipping and holding schemes

Zhang, Lele; Huang, Jiangyan; Liu, Zhiyuan; Vu, Hai L.

doi:10.1080/23249935.2020.1802363

Cited by 12 publications

(3 citation statements)

References 49 publications

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“…The aforementioned works do not exploit the real-time information from telematics systems and automated passenger counts and are not in-line with the objectives of our work that needs to make well-informed decisions using up-to-date information to avoid vehicle overcrowding. Therefore, offline approaches that determine service patterns or combine service patterns with offline timetabling and offline vehicle scheduling (e.g., Li et (12,17,27,28,29) or the recent work of Zhang et al (30)). However, such works have different objectives compared to the objectives of our model, such as improving the service regularity by implementing vehicle holding or reducing the in-vehicle travel times, which might be counterproductive when trying to maintain a pandemic-imposed capacity (e.g., when a vehicle is held more passengers will arrive at the stop and will be willing to board the vehicle leading to higher crowding levels).…”

Section: Literature Review and Contributionmentioning

confidence: 99%

Modifying the service patterns of public transport vehicles to account for the COVID-19 capacity

Gkiotsalitis

2021

Preprint

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As public transport operators try to resume their services, they have to operate under reduced capacities due to COVID-19. Because demand can exceed capacity at different areas and across different times of the day, drivers have to refuse passenger boardings at specific stops. Towards this goal, many public transport operators have modified their service routes by avoiding to serve stops with high passenger demand at specific times of the day. Given the urgent need to develop decision support tools that can prevent the overcrowding of vehicles, this study introduces a dynamic integer nonlinear program that proposes service patterns to individual vehicles that are ready to be dispatched. In addition to the objective of satisfying the imposed vehicle capacity due to COVID-19, the proposed service pattern model caters for the waiting time of passengers. Our model is tested in a bus line connecting the university of Twente with its surrounding cities demonstrating the improvement in terms of vehicle overcrowding, and analyzing the potential negative effects related to unserved passenger demand and excessive waiting times.

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Section: Literature Review and Contributionmentioning

confidence: 99%

Modifying the service patterns of public transport vehicles to account for the COVID-19 capacity

Gkiotsalitis

2021

Preprint

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“…Except for designing stop-skipping routes in tactical planning, the stop-skipping strategy can also be used for real-time and emergency bus management. Zhang et al developed a real-time agent-based simulation model to optimize the dynamic bus stop-skipping and holding schemes 26 . The objective was to reduce passenger waiting and on-board time and improve the reliability of bus service.…”

Section: Introductionmentioning

confidence: 99%

An adjustment framework for mitigating the impact of rail transit construction on bus operations

Chen

et al. 2022

Sci Rep

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During the construction of rail transit, some road resources are occupied under construction and hence the capacity of affected road sections is reduced. Due to such temporary impact, the low operational efficiency of bus routes when passing these road sections is following suit, which is inevitably detrimental to the short-term traffic conditions and the urban environment. This paper proposes a three-step adjustment framework to actively mitigate the impact of rail transit construction on bus operations. In Step I, a criterion is developed for selecting bus routes significantly affected due to rail transit construction. In Step II, we design a stop-skipping strategy and truncation strategy, and check whether they are opportune to ameliorate the service of each affected bus route. Yet, these two strategies result in a loss of ridership since some previous stops are not served. In Step III, the feeder bus service is further designed to guarantee spatial coverage nearby the construction area. A mixed-integer linear programming model is developed to determine the optimal configuration of the feeder bus service incorporating two strategies. Finally, a case study based on the Sioux-Falls network is carried out to demonstrate that the proposed adjustment framework is conducive to mitigating negative construction effects and reducing costs.

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“…Since traffic behaves like a complex system in which dynamics depend on all of its actors, agent-based modelling (ABM) imposes itself as a well-suited tool for its simulation. As such, it has been applied to urban transport [4,6,42,43], bus routing [45], car-pooling [5,46], planing of public transport [47], etc. In comparison to aggregated travel models, ABM can explain the causes of global phenomena that emerged by acting at a local level and then investigate the system-level consequences of appropriate local changes [48].…”

Section: Introductionmentioning

confidence: 99%

Combining Telecom Data with Heterogeneous Data Sources for Traffic and Emission Assessments—An Agent-Based Approach

Grujić

Brdar

Osinga

et al. 2022

IJGI

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To create quality decision-making tools that would contribute to transport sustainability, we need to build models relying on accurate, timely, and sufficiently disaggregated data. In spite of today’s ubiquity of big data, practical applications are still limited and have not reached technology readiness. Among them, passively generated telecom data are promising for studying travel-pattern generation. The objective of this study is twofold. First, to demonstrate how telecom data can be fused with other data sources and used to feed up a traffic model. Second, to simulate traffic using an agent-based approach and assess the emission produced by the model’s scenario. Taking Novi Sad as a case study, we simulated the traffic composition at 1-s resolution using the GAMA platform and calculated its emission at 1-h resolution. We used telecom data together with population and GIS data to calculate spatial-temporal movement and imported it to the ABM. Traffic flow was calibrated and validated with data from automatic vehicle counters, while air quality data was used to validate emissions. The results demonstrate the value of using diverse data sets for the creation of decision-making tools. We believe that this study is a positive endeavor toward combining big data and ABM in urban studies.

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An agent-based model for real-time bus stop-skipping and holding schemes

Cited by 12 publications

References 49 publications

Modifying the service patterns of public transport vehicles to account for the COVID-19 capacity

Modifying the service patterns of public transport vehicles to account for the COVID-19 capacity

An adjustment framework for mitigating the impact of rail transit construction on bus operations

Combining Telecom Data with Heterogeneous Data Sources for Traffic and Emission Assessments—An Agent-Based Approach

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