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Development of Roundabout Crash Prediction Models and Methods (2019)

Chapter: Chapter 7 - Conclusions and Suggested Research

« Previous: Chapter 6 - Research Findings
Page 174
Suggested Citation:"Chapter 7 - Conclusions and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 7 - Conclusions and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Page 175
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Suggested Citation:"Chapter 7 - Conclusions and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Page 176

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174 Conclusions and Suggested Research This chapter summarizes the findings from this research project and identifies areas for suggested further research in the future. 7.1 Conclusions This research project collected extensive crash, volume, and geometric data for over 350 roundabouts in the United States. From this database, the research team developed crash prediction models for urban/suburban and rural single-lane and multilane roundabouts. The crash prediction models are organized into three basic types: 1. Planning-level crash prediction models, 2. Intersection-level crash prediction models, and 3. Leg-level crash prediction models. The planning-level models are relatively easy to apply (fewer data needs) and are intended to be used early in the project development process in activities such as network screening or intersection control evaluations where the poten- tial safety performance of one type of control is being com- pared to another (e.g., potential safety performance of a signal versus roundabout at a specific intersection). The intersection-level crash prediction models were devel- oped to inform design decisions at a similar level of detail as to the intersection crash prediction models for signals and two-way stop-controlled intersections in the Highway Safety Manual, 1st edition. The leg-level crash prediction models were developed to inform design decisions at the leg-level and serve as a com- parison to international leg-level models. Through the inter- national literature review conducted (and documented in Chapter 2), it was clear that leg-level crash prediction models for roundabouts are frequently developed abroad. This project also considered the potential effects of driver learning curve on crash frequency and severity at roundabouts. With the data available, it was not possible to quantify or identify with certainty that driver learning curve influences crash frequency and severity. Several consistent themes emerged in developing the crash prediction models; these include the following: • At the same traffic volume, multilane roundabouts exhibit a greater likelihood for crashes than single-lane roundabouts, indicating that designing roundabouts for more capacity than is needed can degrade their safety performance. • Bicycle and pedestrian crashes made up a very small pro- portion of the crashes reported at single-lane and multilane roundabouts. • Posted speed appeared to be related to crash severity with higher posted speeds as a predictor of more severe collisions. • More consistent multimodal volume data collection on major and minor streets would greatly enhance the ability to create robust crash prediction models. • As will be discussed further, additional research into vehicle speeds would be worthwhile to explore as a predictor of crashes. • Calibrating the final models is critical for being able to use them to accurately compare potential roundabout safety performance to other traffic control types (e.g., signals, stop-control). 7.2 Recommendations for Practitioners The three types of crash prediction models in this project were developed to help inform decisions at different stages of a project’s development. Calibration of the models is important to be able to be confident in the predictions they are providing; this is particularly true when comparing the crash predictions to crash predictions from other models (e.g., comparing the roundabout crash prediction to a crash prediction for a traffic signal). C H A P T E R 7

175 Planning-level crash prediction models are to be applied in the early stages of determining if an intersection should be controlled by a roundabout, a stop sign, or a signal. These can also be used as part of network screening to assess the safety performance of several roundabouts. Intersection-level crash prediction models are to be applied in making roundabout-specific design decisions such as the number of entering and circulating lanes. Leg-level crash prediction models are to be applied to inform design decisions at the leg-level. These are not intended to predict the total crashes for a roundabout intersection; that should be done using the intersection-level models. Chapter 6, Research Findings, is provided with the intent of consolidating into one location the specific results of the research for use by practitioners. 7.3 Suggested Research There are two primary areas related to roundabout safety performance that emerged as important for further future research. These are (1) pedestrian and bicycle safety at round- abouts and (2) fastest path predicted vehicle speeds as a key predictor for the frequency and severity of crashes. Through the literature review activities and the practitioner workshop conducted as part of this project, it is clear there is a general perception that roundabouts are more difficult for pedestrians and bicyclists to travel through, and therefore those two modes experience greater risk for crashes at round- abouts. The crash data in this project did not indicate that there was an increased risk for those two modes. However, this project was limited in what could be evaluated and the statements that can be made from the data because the project was not able to collect and analyze pedestrian and bicycle volume data alongside the crash data that was available. As noted in Chapter 6, Section 6.4, bicycle crashes account for approximately 1% of all reported crashes in the project database, and pedestrian crashes represent about 0.4% of all reported crashes in the database. To further understand the crash risk for those two modes, additional research is needed that can focus on collecting pedestrian and bicycle volume data at roundabouts as well as increasing the number the roundabouts and/or years of crash data to have a larger sample size of crash events to analyze. From this project, the event of a bicycle–vehicle crash or a pedestrian–vehicle crash was too rare to evaluate in a manner that could lead to prediction. Relating vehicle speed to crash frequency and severity at roundabouts would be a powerful step forward in helping inform overall design decisions at roundabouts. Much of roundabout design is performance-based in balancing the need to accommodate design vehicles while creating geometry that forces vehicles to slow their speeds on entry to the round- about as well as through the roundabout. NCHRP Report 672: Roundabouts, An Informational Guide, 2nd edition, presents the fastest path methodology for predicting vehicle speeds on entering, circulating, and exiting the roundabout. In this proj- ect, efforts were made to try to relate those predicted speeds to crash occurrence. Due to budget and schedule limitations, this effort was not able to be fully explored; however, the research team believes it would be valuable to invest in evaluating the relationship between the predicted entry speed and crashes for a specific roundabout leg. Such research could result in a better understanding of key drivers for roundabout safety performance.

Development of Roundabout Crash Prediction Models and Methods Get This Book
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TRB’s National Cooperative Highway Research Program (NCHRP) Research Report 888: Development of Roundabout Crash Prediction Models and Methods provides crash prediction models that quantify the expected safety performance of roundabouts for motorized and non-motorized road users. Safety performance factors (SPF) and crash modification factors (CMF) are predictive models that estimate expected crash frequencies. These models are used to identify locations where crash rates are higher than expected, to estimate safety benefits of a proposed project, and to compare the safety benefits of design alternatives. SPF and CMF models may help identify and prioritize locations for safety improvements, compare project alternatives by their expected safety benefits, and guide detailed design decisions to optimize safety. Research indicates that roundabouts provide substantial reductions in crashes, and this report determines SPF and CMF specifications for roundabouts.

The report includes appendices to the contractor's final report and a Powerpoint presentation.

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