Modeling Freeway Level-of-Service based on Travel Time and Travel Time Reliability
Analytics
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Abstract
The assessment of operational performance is a challenge for the local transportation agencies and Metropolitan Planning Organizations (MPOs) due to the dynamic nature in traffic movement. As demand approaches to the capacity of a roadway (or of the intersections along the road), extreme traffic congestion sets in. When vehicles are fully stopped for periods of time, this is colloquially known as a traffic jam or traffic snarl-up. A qualitative classification of traffic is often done in the form of a six letter A–F level-of-service (LOS) scale defined in the Highway Capacity Manual (HCM), a document widely used by engineers and planners in the U.S. (or used as a basis for national guidelines worldwide). LOS is the chief measure of "quality of service" which describes operational conditions within a traffic stream and is different for different facilities. These levels are used by transportation engineers and planners as shorthand to describe traffic levels to the lay public.However, the current LOS criteria is based on density parameters along with some speed information for freeway sections, and service flow rate with speed information for highways, which do not always convey message to the general road users. In addition, unlike flow rate and speed information, density is not directly collected or readily available from field.Travel time is one of the most important metrics used by the practitioners for decision making processes. It is also easily understood by road users and helps them choose their routes to reach their destinations quickly. Real time continuous data collection is possible through the use of roadside Bluetooth detectors, on-road sensors, traffic cameras, or other technologies. Hence, if travel time related parameters can be established to denote the service level of freeways, the LOS would be readily available and the variation can easily be recorded over time. Further, travel time reliability has become an important concept for modern and urban transportation system managers. It is defined as "the consistency or dependability in travel times, as measured from day to day and/or across different times of the day" and a measure of the service provided by a transportation network.This dissertation correlates the travel time and travel time reliability with density based LOS thresholds and identifies a more convenient and easily understood and usable LOS criteria based on such measures. A microscopic simulation model is developed, calibrated, and validated using the real world data. The calibrated parameters are used in several hypothetical microscopic simulation models representing different sections of freeway section types (i.e., basic freeway section, weaving section, and merging/diverging area) in order to develop a meaningful density – travel time and density – travel time reliability relationships and corresponding LOS criteria. Prior to developing the relationships and LOS criteria, the microscopic simulation based density values are compared with the HCM based densities in order to indicate the validity of the models.The dissertation finds a strong correlation between HCM based densities and densities from VISSIM, which further validates the notion that a calibrated microscopic simulation model can be effectively used to represent general traffic behavior. The density – travel time per mile relationship shows a non-linear (exponential) relationship for all the freeway section types, which further questions the generic speed assumptions made by HCM for different LOS profiles. A polynomial relationship was observed between density – travel time reliability indices. It was found that average travel time per mile threshold values for respective LOS letters increase as the speed limit decreases until the condition comes close to saturation where the speed limit on the freeway does not have any influence on the operation. It can also be noted that as the posted limit decreases, the percent difference between the two respective adjacent travel time per mile threshold values also decreases.The dissertation also finds that the average travel time reliability LOS threshold values for their respective LOS letters decrease for all freeway section types as the speed limit decreases. For PTI based thresholds, the 95th percentile travel time decreases as the speed limit decreases but the 5th percentile travel times remain relatively similar. In case of BTI based thresholds, the 95th and 50th percentile travel time values become closer as the speed limit decreases. For all freeway section types, the percent difference between two respective adjacent PTI LOS threshold values remains relatively similar with slight increase or decrease as the speed limit decreases. However the percent difference between two adjacent BTI threshold values tends to increase as the speed limit decreases. The dissertation also showed that based on the observation period (number of data points), the LOS estimation can differ significantly.Overall, this dissertation provides important insights on a more convenient and easily understandable approach to define freeway LOS and provides baselines for future researchers to investigate and develop the method further.