Modeling merging behavior at lane drops.

Author(s)
Hallmark, S.L. & Oneyear, N.
Year
Abstract

A large number of lane miles are under construction in the Midwest during the peak summer roadway usage season each year. Coupled with increased seasonal traffic volume, work zones become points of congestion that can lead to driver frustration and aggressive driver behaviour. In work-zone configurations where lane drops are present, merging of traffic at the taper presents an operational concern. In addition, as flow through the work zone is reduced, the relative traffic safety of the work zone is also reduced. Improving work-zone flow-through merge points depends on the behaviour of individual drivers. The goal of this project was to improve work-zone driver-behaviour models, particularly near the merge point. To accomplish this goal, the objectives of this effort were as follows: * Identify work-zone merge countermeasures appropriate for the Midwest; * Develop and calibrate microsimulation models to better incorporate realistic and accurate driving behaviour for merging; *Apply the model for different work-zone plans and countermeasures and determine their impact on driver behaviour. A comprehensive literature review was conducted to summarize information about the effectiveness of work-zone strategies to address merging behaviour leading to increased operations and improved safety. The team also conducted a survey of agencies in the Midwest to determine which countermeasures are regularly used as well as which innovative strategies have been considered. One chapter of the report provides a review of the following strategies, which have been used to encourage desirable lane-merge behaviours to improve traffic flow and safety at work-zone merges: * Variable speed limits; * Temporary rumble strips; *Static late merge; *Dynamic early-merge and late-merge systems For each strategy, the information includes background, application (with a focus on information from the Midwest agency survey), effectiveness, advantages, and disadvantages. Another chapter describes data collection and reduction as well as modelling development and calibration of an urban and an Interstate work-zone microsimulation model in VISSIM. The two Iowa work zones, one on Lincoln Way in Ames and the other on I-35 in Hamilton County, were modelled in VISSIM using real-world speeds, travel times, queue lengths, and merging behaviours. These models were calibrated to reflect real-world queue lengths, speeds, travel times, and percentage of vehicles merging upstream and near the merge point. Once built and calibrated, strategies for the various countermeasures were modelled in the work zones. The models were then used to test and evaluate how the various merging strategies affect safety and operations at the merge areas in these work zones. For the Interstate work zone, the early-merge scenario was found to make speeds more consistent and reduce both queue lengths and queue stops. It made merging smoother than the real-world scenario. It did, however, decrease speeds upstream more and pushed the queue farther away from the merge point. It was modelled based off a perfect scenario where all drivers would merge early, which in real life would most likely not be the case, so results in the real world would not be expected to be as great. The late-merge scenario also improved operations for the Interstate work zone, by decreasing travel time, queue lengths, and queue stops. Speeds at the merge point were lower than with the real-world scenario, which is a potential safety benefit. For the urban work zone, only the late-merge scenario was tested. It was found to decrease operations by slightly increasing travel time, and all queue lengths. The real-world merging behaviour for this work zone greatly resembled the early-merge strategy, which saw improved operations compared to the late-merge strategy for the Interstate scenario. This may help to explain the decrease in operations seen with the late-merge strategy at this work zone. The early-merge strategy was not tested for the urban work zone as the majority of drivers already merged early with none merging within 200 feet of the merge point. Overall, both the early-merge and late-merge strategies were found to improve operations and to smooth flow at the merge points in the work zone. Queue lengths, which pose safety concerns if they extend too far upstream, because they can surprise drivers who are not expecting or aware of the work zone ahead, were decreased in both situations. The early merge was found to be a good option when there was moderate congestion as it smoothed speeds and had shorter queues and travel times than the late-merge or real-world options. If vehicles increased, however, this option could extend queues farther upstream, which could result in longer queues. The late-merge option did improve operations over the real-world scenario and may have been a better option if more vehicles were present. Traffic control plans, work-zone policies, and countermeasures can be better targeted to reinforce desirable lane-closure merging behaviour, leading to both improved safety and work-zone capacity, by better understanding driver behaviour. A better understanding of the merging behaviour of drivers will lead to the development of better lane-drop traffic-control plans and strategies, which will provide better guidance to drivers for safer merging. Results of this research may be useful to the Smart Work Zone Deployment Initiative (SWZDI) departments of transportation (DOTs)–Iowa, Kansas, Missouri, Nebraska, and Wisconsin–as well as counties and cities. Some avenues to pursue in sharing the project results are to work further with the Iowa Local Technical Assistance Program (LTAP), the SWZDI panel, the Federal Highway Administration (FHWA), particularly given SWZDI is an FHWA Pooled Fund Study, and others to conduct further technology transfer of the results. Selection and appropriate application of strategies will result in better output from work-zone traffic analysis tools. In turn, better output will lead to more-robust estimations of the impacts of a particular work-zone configuration. This will allow more effective and efficient traffic control plans to manage traffic around work zones and adjacent routes. Improved evaluation of alternatives will ultimately lead to decreased congestion and improved travel time and mobility through work zones, benefiting agencies, workers, and the travelling public. (Author/publisher)

Publication

Library number
20150561 ST [electronic version only]
Source

Ames, IA, Iowa State University, Institute for Transportation InTrans, Center for Transportation Research and Education (CTRE) / Institute for Transportation InTrans, Smart Work Zone Deployment Initiative (SWZDI), 2015, XI + 37 p., 38 ref.; InTrans Projects 13-466 and 06-277

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