Modeling travelers’ perception of service quality is an emerging research area in surface transportation. The first national effort to study automobile drivers’ perceptions is NCHRP Project 3-70. The study was developed in response to agencies’ needs to understand which factors enter into users’ perception of quality of service and the interaction between modes on urban streets. This paper describes the research efforts taken to analyze and model automobile level of service (LOS) from the driver's perspective. A data collection approach using video laboratories and a modeling approach suitable for the discrete and ordered nature of the response variable were selected. The approach enabled the estimation of the distribution of LOS responses, given a set of explanatory variables that describe the geometry and operational effectiveness of the urban street facility. Analysis indicated that participants’ responses tended to be highly variable and that models that characterize the distribution would be preferable to point estimates. A model that uses the number of stops per mile experienced on the facility and the presence of exclusive left-turn lanes at intersections gave the best fit to the data and matched the mean video clip LOS rating 71% of the time. Although direct links between various modes to the automobile users’ perceptions of service quality were not identified, the variable “number of stops” incorporates interruptions experienced by automobile drivers when interacting with buses, bicycles, or pedestrians on urban streets and when encountering traffic signal stops. Although the proposed model was found to improve LOS prediction as compared with the current Highway Capacity Manual method, there are implementation issues that have yet to be addressed.


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    Title :

    Analysis and Modeling of Automobile Users’ Perceptions of Quality of Service on Urban Streets


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2008-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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