Level of Service for Bicycle Through Movement at Signalized Intersections Operating Under Heterogeneous Traffic Flow Conditions

Beura, Sambit Kumar; Kumar, Naresh; Bhuyan, Prasanta Kumar

doi:10.1007/s40890-017-0051-z

Cited by 14 publications

(4 citation statements)

References 18 publications

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“…This issue is associated with the need for research assessing which assumptions can be adopted for e-bikes from those related to bicycle-pedestrians interactions. Research in respect to BLOS studies is mostly based on transport components, including segments [91,[167][168][169][170][171][172], nodes [63,[173][174][175] and networks [5,[176][177][178][179]. However, network-based BLOS studies compared to link and node studies require more extensive research [180][181][182][183][184].…”

Section: Discussionmentioning

confidence: 99%

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

et al. 2020

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Research into the bicycle level-of-service (BLOS) has been extensively conducted over the last three decades. This research has mostly focused on user perceptions of comfort to provide guidance for decision-makers and planners. Segments and nodes were studied first, followed by a network evaluation. Besides these investigations, several variables have also been utilized to depict the users’ perspectives within the BLOS field, along with other cycling research domains that simultaneously scrutinized the users’ preferences. This review investigates the variables and indices employed in the BLOS area in relation to the field of bicycle flow and comfort research. Despite general agreement among existing BLOS variables and the adopted indices, several important research gaps remain to be filled. First, BLOS indices are often categorized based on transport components, while scarce attention has been paid to BLOS studies in trip-end facilities such as bicycle parking facilities. The importance of these facilities has been highlighted instead within research related to comfort. Second, the advantages of separated bike facilities have been proven in many studies; however, scarce research has addressed the challenges associated with them (e.g., the heterogeneity within those facilities due to the presence of electric bikes and electric scooters). This issue is clearly noticeable within the research regarding flow studies. Furthermore, network evaluation (in comparison to segment and node indices) has been studied to a lesser extent, whereas issues such as connectivity can be evaluated mainly through a holistic approach to the system. This study takes one step toward demonstrating the importance of the integration of similar research domains in the BLOS field to eliminate the aforementioned shortcomings.

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Section: Discussionmentioning

confidence: 99%

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

et al. 2020

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“…Liu, Homma, and Iki (2019) [14] introduced and compared two methods for evaluating the quality of bicycle facilities, bicycle compatibility index (BCI) and bicycle level of service (BLOS). Beura, Kumar, and Bhuyan (2017) [15] modeled the quality of services offered to bicycles through movement at urban signalized intersections carrying heterogeneous traffic. A total of six attributes of intersection approaches having significant influences on bicycle service quality were identified with the help of Pearson's correlation analysis and stepwise regression analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Level of Service Model of the Non-Motorized Vehicle Crossing the Signalized Intersection Based on Riders’ Perception Data

Zhu

Wang

et al. 2022

IJERPH

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This article aims to analyze the factors affecting the LOS (level of service) of non-motorized vehicles crossing the signalized intersection and to construct an appropriate method to evaluate the LOS. Aiming at the mixed non-motorized traffic flow of electric vehicles and bicycles in the Chinese metropolis, the delay model in the highway capacity manual (HCM) was modified by taking two new factors into account: the pedestrian traffic rule compliance rate and the fuzzy perception of arrival rate in reality. The results show that the data obtained by the modified model are more consistent with the actual one. Next, a comparison was established between the linear regression method and cumulative logistic regression to determine the variables that affect the LOS, and finally, a LOS evaluation index system based on threshold schemes was defined. The recommended LOS model can provide corresponding references for traffic engineers who seek to improve the level of service in urban intersections.

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“…Recent investigations on bicycle operations under heterogeneous traffic flow conditions have concluded that the quality of bicycling is largely influenced by vehicular traffic volume [17,18]. On-road bicyclists under such conditions encounter a very complex interaction with several small to big vehicles and subsequently have their quality of riding to be largely influenced by the same.…”

Section: Review Of Literaturementioning

confidence: 99%

Urban road segment level of service based on bicycle users’ perception under mixed traffic conditions

2017

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During the past two decades, several methodologies are endorsed to assess the compatibility of roadways for bicycle use under homogeneous traffic conditions. However, these methodologies cannot be adopted under heterogeneous traffic where on-street bicyclists encounter a complex interaction with various types of vehicles and show divergent operational characteristics. Thus, the present study proposes an initial model suitable for urban road segments in mid-sized cities under such complex situations. For analysis purpose, various operational and physical factors along with user perception data sets (13,624 effective ratings in total) were collected from 74 road segments. Eight important road attributes affecting the bicycle service quality were identified using the most recent and most promising machine learning technique namely, random forest. The identified variables are namely, effective width of outside through lane, pavement condition index, traffic volume, traffic speed, roadside commercial activities, interruptions by unauthorized stoppages of intermittent public transits, vehicular ingress-egress to on-street parking area, and frequency of driveways carrying a high volume of traffic. Service prediction models were developed using ordered probit and ordered logit modeling structures which meet a confidence level of 95%. Prediction performances of developed models were assessed in terms of several statistical parameters and the ordered probit model outperformed the ordered logit model. Incorporating outputs of the probit model, a predictive equation is presented that can identify under what level a segment is offering services for bicycle use. The service levels offered by roadways were classified into six categories varying from 'excellent' to 'worst' (A-F).

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Level of Service for Bicycle Through Movement at Signalized Intersections Operating Under Heterogeneous Traffic Flow Conditions

Cited by 14 publications

References 18 publications

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

Level of Service Model of the Non-Motorized Vehicle Crossing the Signalized Intersection Based on Riders’ Perception Data

Urban road segment level of service based on bicycle users’ perception under mixed traffic conditions

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