Driver Assessment of Service Quality on Urban Streets

Flannery, Aimee; Wochinger, Kathryn; Martin, Angela

doi:10.3141/1920-03

Cited by 16 publications

(13 citation statements)

References 4 publications

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“…Kittelson and Roess (2001) divulged that besides quantitative analysis, LOS should also be based on drivers perception on the quality of service provided by urban street segments depending on several characteristics like travel efficiency, sense of safety and aesthetics. Flannery et al (2005) developed a relationship between quantitative services to qualitative service measuring methods for urban streets. The researchers found that the LOS calculated by "Highway Capacity Manual" methodology envisages 35% of the variance in mean driver rating.…”

Section: Literature Reviewmentioning

confidence: 99%

Self-Organizing Tree Algorithm (SOTA) Clustering for Defining Level of Service (LOS) Criteria of Urban Streets

Das

Bhuyan

2018

Period. Polytech. Transp. Eng.

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Section: Literature Reviewmentioning

confidence: 99%

Self-Organizing Tree Algorithm (SOTA) Clustering for Defining Level of Service (LOS) Criteria of Urban Streets

Das

Bhuyan

2018

Period. Polytech. Transp. Eng.

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“…Flannery et al [12] showed that the LoS calculated as per US-HCM methodology could only explain 35 % of the variance in the mean drivers' rating of an urban street and that there were several non-operational factors such as travel efficiency, sense of safety and aesthetics that exhibited strong and statistically significant correlations with the mean drivers' rating. This latter conclusion was also confirmed by Washburn et al [13] as they found that in addition to traffic density, drivers also considered operational factors such as speed variance and mean speed as a percentage of free-flow speed along with non-traffic related factors such as pavement quality and driver etiquette for determining QoS on rural freeways.…”

Section: User-based Los Definitionmentioning

confidence: 99%

Selection of a Suitable Service Measure and Determination of LOS Criteria for Indian Multilane Interurban Highways: A Methodological Review

Arun

Errampalli

Velmurugan

2016

Transp. in Dev. Econ.

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Any transport facility is essentially a service being provided to the society. Therefore, it is expected of the traffic engineers, transport planners and policy-makers alike to be able to understand and evaluate the quality of service that is being provided by the transport facilities designed by them. The level-of-service (LoS) concept was devised in the US Highway Capacity Manual (US-HCM) precisely for the above consideration. However, direct implementation of the US-HCM methods in India is not possible because of the heterogeneous traffic conditions and vastly unique driver behavior found on Indian highways. Therefore, it becomes imperative to evaluate other competing methodologies that may be more appropriate in defining the LoS being offered to the road users by Indian highways in general and multilane interurban highways in particular. Towards this end, this paper reviews in detail the LoS estimation methodologies that have been demonstrated to be suitable for application in traffic scenarios characterized by high heterogeneity and lane indiscipline. Also, based on an exhaustive review of the literature, the study recommends that three to five categories of LoS in the stable-flow region may be explored for practical application in the Indian scenario as part of the ongoing research on development of an Indian Highway Capacity Manual.

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“…Kittelson and Roess (2001) have noted down that the current HCM methodologies have not been based upon user perception surveys [5]. Flannery et al (2005) while relating quantitative to qualitative service measuring methods for urban streets found that level of service calculated by HCM 2000 methodology, predicted 35% of the variance in mean driver rating. The authors have suggested that LOS does not completely represent drivers' assessments of performance of urban streets because drivers perceive the quality of urban street segments in several dimensions, including travel efficiency, sense of safety, and aesthetics [6].…”

Section: Literature Reviewmentioning

confidence: 99%

Defining Level of Service Criteria of Urban Streets Using Neural Gas Clustering

Das¹

2013

IOSRJEN

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The traffic flow condition in India is highly heterogeneous. This study aims at defining the Level of Service (LOS) categories for highly heterogeneous traffic condition for urban streets in Indian context. Global Positioning System (GPS) is used as a powerful tool for collecting speed data at every one second interval. For this study Free Flow Speed (FFS) data and average travel speed data are collected on five corridors of Mumbai city. These speed data are analyzed using neural gas clustering method. The optimal number of clusters is obtained using six validation parameters. Neural gas is used two times in this study process. First neural gas is applied on FFS data to obtain the speed ranges of different urban street classes. Second time neural gas is used on the average speed data to obtain the speed ranges of different LOS categories. The above study confirms that the FFS ranges for different urban street classes and speed ranges for different LOS categories are found to be lower than that suggested by HCM 2000.

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Driver Assessment of Service Quality on Urban Streets

Cited by 16 publications

References 4 publications

Self-Organizing Tree Algorithm (SOTA) Clustering for Defining Level of Service (LOS) Criteria of Urban Streets

Self-Organizing Tree Algorithm (SOTA) Clustering for Defining Level of Service (LOS) Criteria of Urban Streets

Selection of a Suitable Service Measure and Determination of LOS Criteria for Indian Multilane Interurban Highways: A Methodological Review

Defining Level of Service Criteria of Urban Streets Using Neural Gas Clustering

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