Research
Traffic Safety
Methodology to Predict the Safety Performance of Rural Multilane Highways
The primary product of this research will be a methodology for estimating the safety performance of rural multilane highways and a toolkit for applying the methodology. The toolkit will be comprised of a suite of crash prediction models for different types of applications, different severities and different entity types, the best available information on crash modification factors for road design applications and detailed illustrations and instructions for applying the methodology. Dr. John N. Ivan, P.I. john.ivan@uconn.edu
Project under subcontract with the Texas Transportation Institute.
Factors Effecting Young Driver Safety
This study reconfirms previous findings indicating that young drivers, especially young males and those of either gender age 16 and 17, are more likely to cause both single and two-vehicle crashes. In terms of miles traveled, teenage drivers are 3 times more likely than other drivers to be involved in a fatal crash. The study also indicates that young driver risk increases: at night; on freeways; and with an increase in number of passengers. The study supports the need to lengthen the Learner Phase of young driver licensure in Connecticut. Dr. Lisa Aultman-Hall, P.I.
Investigation of a New Approach for Representing Traffic Volumes in Highway Crash Analysis and Forecasting
This project is investigating a new approach for modeling the relationship between crashes and traffic volume that will both preserve the possibility of estimating a crash risk per unit exposure and account for the non-linear effect of traffic volume on crash incidence. The model form proposed will predict crashes to account for three distinct effects that volume has on crash incidence: the number of trials (or exposure), the number of crash opportunities (or vehicle interactions), and the traffic flow state, along with a function of the roadway characteristics that will represent the risk of the highway location after controlling for the effects of volume. Dr. John N. Ivan, P.I. john.ivan@uconn.edu
Network-Based Highway Crash Prediction Using Geographic Information Systems
The objectives of this project are to estimate network-based crash prediction models that will predict expected crash experience in any given geographic area as a function of the highway link, intersection and land use features observed in the area. The result will be a system of GIS programs that permit a polygon to be drawn on a map, or a set of links and intersections to be selected, and then predict the number of crashes expected to occur on the selected traffic facilities. Expected values can then be compared with observed values to identify locations that are particularly dangerous and require attention for improving safety. Dr. John N. Ivan, P.I. john.ivan@uconn.edu
Designing Roads that Guide Drivers to Choose Safer Speeds
This project is aimed at learning how roadway geometry and the roadside environment influence actual travel speeds chosen by drivers, and, in turn, how actual travel speeds,
along with these characteristics, influence the incidence of crashes. This research compares crash counts and observed speeds on roads in groups with similar geometric characteristics and roadside environments, controlling for the observed traffic volumes. This project will help to identify appropriate improvements
to the roadway and/or roadside environment features that will reduce the travel speeds where necessary and improve the safety of the road location. P.I.s: Dr. John Ivan john.ivan@uconn.edu and Dr. Norman Garrick norman.garrick@uconn.edu
The Effect of Segment Characteristics on the Severity of Head-on Crashes on Two-Lane Rural Highways
Head-on crashes on two-lane rural highways are more likely to result in fatalities than other crash types. However, as many as 50 percent result in no fatalities.
There is a great deal of literature documenting how characteristics of the vehicle, driver and occupants affect head-on crash severity, but very little about the
characteristics of the road, the one thing, as traffic engineers, we can control. This project investigates how characteristics of two-lane rural highways affect
the severity of head-on crashes, while controlling for characteristics of the vehicle, driver and occupants. The results will provide valuable information for highway
safety engineers. Dr. John N. Ivan, P.I. john.ivan@uconn.edu
Safety of Shared-use Paths in Connecticut
This project involved the design of a shared-use path safety survey and its use on three facilities in Connecticut in the fall of 2002 and the summer of 2003. The objective was to collect self-reported information on
collision and fall events, and travel exposure, so that estimates of crash rates could be developed for these paths. The analysis of the self-reported events and travel patterns provides complementary data that are not available from other sources and are needed to address safety concerns on these facilities. The sample size of 684 was sufficient only to develop aggregate crash rates.
Dr. Lisa Aultman-Hall, P.I.
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