A route-planning method for long-distance commuter express bus service based on OD estimation from mobile phone location data: the case of the Changping Corridor in Beijing

Wang, Zhenbao; Wang, Sicheng; Lian, Haitao

doi:10.1007/s12469-020-00254-w

Cited by 12 publications

(8 citation statements)

References 46 publications

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“…Some scholars obtain the OD matrix of residents' travel between different areas through mobile phone positioning data, then set different distance time thresholds, transfer times, and other constraints, and build a bus route planning model that calculates the bus planning route [23,24], based on the method of dividing travel transportation by the advantage of travel distance and cost. Jia used the map analysis software Transcad to obtain the bus travel matrix and forecast the public transportation demand [25].…”

Section: Background and Related Workmentioning

confidence: 99%

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Planning Urban Internal Transport Based on Cell Phone Data

Zhao

2022

Applied Sciences

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Based on cell phone data, mining residents’ travel characteristics and regional traffic connection characteristics has become an important technology for urban road traffic planning research. Based on cell phone data extracted from Wuxue City, this paper proposes an operability method for mining regional traffic contact intensity information based on cell phone data and an urban road network evaluation method. We analyze the travel characteristics of residents and the current situation of traffic connections between towns by constructing a planning road model of Wuxue city and find that the traffic connection of Wuxue city shows a spatial development pattern with Wuxue street as the intersection, one horizontal and one vertical, and the traffic accessibility gradually decreases from south to north. We analyze the spatial characteristics and problems of the planning of the road network in Wuxue and propose a modification plan. We verify the reasonableness of the modified plan by calculating traffic accessibility and road density. The research provides a new way to obtain spatio-temporal information about passenger flows by applying cell phone data to urban road planning.

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Section: Background and Related Workmentioning

confidence: 99%

“…Focus on the application of mobile phone data to study urban public transportation, and there are fewer comprehensive studies on other modes of urban transportation [23][24][25][26].…”

Section: Research Aspectmentioning

confidence: 99%

Planning Urban Internal Transport Based on Cell Phone Data

Zhao

2022

Applied Sciences

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“…For example, concerning AVL data, in [152], a real-time positioning method, which employs crowdsourced positioning data obtained from smartphone GPS, is developed with the aim of improving vehicle-positioning accuracy. The aim to integrate AVL and smartphone data to estimate the O-D matrix can also be found in [153]. In all these cases, a disclaimer regarding data security seems necessary; see also Section 4.3.3. The studies considered on this data source are summarized in Table 7.…”

Section: Smartphonementioning

confidence: 99%

Review of Transit Data Sources: Potentials, Challenges and Complementarity

Sarhani

Voß

et al. 2021

Sustainability

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Public transport has become one of the major transport options, especially when it comes to reducing motorized individual transport and achieving sustainability while reducing emissions, noise and so on. The use of public transport data has evolved and rapidly improved over the past decades. Indeed, the availability of data from different sources, coupled with advances in analytical and predictive approaches, has contributed to increased attention being paid to the exploitation of available data to improve public transport service. In this paper, we review the current state of the art of public transport data sources. More precisely, we summarize and analyze the potential and challenges of the main data sources. In addition, we show the complementary aspects of these data sources and how to merge them to broaden their contributions and face their challenges. This is complemented by an information management framework to enhance the use of data sources. Specifically, we seek to bridge the gap between traditional data sources and recent ones, present a unified overview of them and show how they can all leverage recent advances in data-driven methods and how they can help achieve a balance between transit service and passenger behavior.

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“…Some scholars [18] explored the decision-making behavior of commuters at a bus station of departure during morning peak hours. Some scholars [19] developed a systematic toolkit for demand estimation and route planning for long-distance commuter bus lines. Some scholars [20] proposed a method for extracting potential CCB passengers from regular bus passengers based on the bus smart card data; the method guides bus operators in designing CCB lines and allocating vehicle capacities on different lines.…”

Section: Introductionmentioning

confidence: 99%

Commuter Bus Operation Rules under Two Traffic Scenarios and Two Weather Conditions: Naturalistic Driving Study on Vehicle Speed and Clearance

Feng

Zhang

Yu³

et al. 2022

Sustainability

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This study provides insights into the building of environmentally and socially sustainable and livable cities by investigating commuter buses’ vehicle speed and clearance, considering two traffic scenarios (working days and weekends) and two weather conditions on urban roads. Thirty participants drove ten different routes during natural driving. The drivers were observed under the following traffic conditions: free flow (Grade I), steady flow (Grades II and III), unsteady flow (Grade IV), working days and weekends, and sunny and heavy snow weather. A method for collecting accurate traffic flow data was developed using a radar sensor to measure the real-time distance between vehicles. The real-time vehicle spacing and speed were detected using a radar sensor and a mobile app, respectively. The results showed that speed decreased obviously from 11.2% to 16.5% on working days compared to a similar situation on weekends, especially in heavy snow weather (from 33.8% to 40.7%). The lowest average speed was obtained in the traffic environment Grade IV. Commuter buses maintained a minimum vehicle clearance during working or heavy snow days in traffic environment Grade IV. Policymakers should consider the insights of this study to develop new, dynamic commuter schedules under diverse conditions.

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A route-planning method for long-distance commuter express bus service based on OD estimation from mobile phone location data: the case of the Changping Corridor in Beijing

Cited by 12 publications

References 46 publications

Planning Urban Internal Transport Based on Cell Phone Data

Planning Urban Internal Transport Based on Cell Phone Data

Review of Transit Data Sources: Potentials, Challenges and Complementarity

Commuter Bus Operation Rules under Two Traffic Scenarios and Two Weather Conditions: Naturalistic Driving Study on Vehicle Speed and Clearance

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