Mazen Arafeh

Estimating Path Travel-Time Reliability

The estimation of path or trip travel-time reliability is critical to any advanced traveler information system. The state-of-practice procedures for estimating path travel-time reliability assumes that travel times follow a normal distribution and requires a measure of trip travel-time variance. The study analyzes AVI data from San Antonio and demonstrates through goodness-of-fit tests that the assumption of normality is, from a theoretical standpoint, inconsistent with field travel-time observations and that a lognormal distribution is more representative of roadway travel times. However, visual inspection of the data demonstrates that the normality assumption may be sufficient from a practical standpoint given its computational simplicity. The paper then proposes five methods for the estimation of path travel-time variance from its component segment travel-time variances. The analysis demonstrates that computing the trip travel-time coefficient of variation as the conditional expectation over all realizations of roadway segments provides estimates within 13% of field observations for both uncongested and congested conditions

Inclement Weather Impacts on Freeway Traffic Stream Behavior

The research reported in this paper quantifies the impact of inclement weather (precipitation and visibility) on traffic stream behavior and key traffic stream parameters, including free-flow speed, speed at capacity, capacity, and jam density. The analysis is conducted using weather data (precipitation and visibility) and loop detector data (speed, flow, and density) obtained from the Baltimore, Maryland; Minneapolis–Saint Paul, Minnesota; and Seattle, Washington, areas in the United States. The precipitation data included intensities up to 1.6 and 0.33 cm/h for rain and water equivalent of snow intensity, respectively. The paper demonstrates that the traffic stream jam density is not affected by weather conditions. Snow results in larger reductions in traffic stream free-flow speed and capacity when compared with rain. Reductions in roadway capacity are not affected by the precipitation intensity except in the case of snow. Reductions in free-flow speed and speed at capacity increase as the rain and snow intensities increase. Finally, the paper also develops free-flow speed, speed-at-capacity, and capacity weather adjustment factors that are multiplied by the base clear-condition variables to compute inclement weather parameters. These adjustment factors vary as a function of the precipitation type, precipitation intensity, and visibility level. It is intended that these adjustment factors be incorporated into the Highway Capacity Manual.

Evaluating Alternative Truck Management Strategies Along Interstate 81

The study evaluates lane management strategies along one of the most highly traveled sections of Interstate 81 in the state of Virginia by using the INTEGRATION traffic simulation software. The lane management strategies considered include the separation of heavy-duty trucks from light-duty traffic, the restriction of trucks to specific lanes, and the construction of climbing lanes at strategic locations. Overall, the results demonstrate that a physical separation of heavy-duty trucks from the regular traffic offers the maximum benefits and that restricting trucks from the use of the leftmost lane offers the second-highest benefits in terms of efficiency, energy, and environmental impacts.

Safety Impacts of Access Control Standards on Crossroads in the Vicinity of Highway Interchanges

Adequate spacing and design of access to crossroads in the vicinity of freeway ramps are critical in the safety and traffic operations of the freeway, crossroad, and properties near interchanges. Research attempted to develop a methodology to evaluate the safety impact of different access-road spacing standards. Results clearly demonstrate the shortcomings of the AASHTO standards and the benefits of enhancing these standards. The models developed as part of this research effort were used to compute the crash rate associated with alternative section spacing. The study demonstrates that the models satisfied the statistical requirements and provide reasonable crash estimates. Results demonstrate an eightfold decrease in the crash rate over an access-road spacing ranging from 0 to 300 m. An increase in the minimum spacing from 90 m (300 ft) to 180 m (600 ft) results in a 50% reduction in the crash rate. The developed models provide an excellent tool to evaluate the trade-off of alternative access-road spacing. Furthermore, the economic impacts of alternative access-road spacing can be computed by using a weighted average crash cost. This average crash cost can be multiplied by the expected number of crashes per kilometer to compute the cost associated with different access-spacing scenarios. It is anticipated that this procedure can assist policy makers in quantifying the trade-offs of different access management regulations.

Modeling Inclement Weather Impacts on Traffic Stream Behavior

The research identifies the steady-state car-following model parameters within state-of-the-practice traffic simulation software that require calibration to reflect inclement weather and roadway conditions. The research then develops procedures for calibrating non-steady state car-following models to capture inclement weather impacts and applies the procedures to the INTEGRATION software on a sample network. The results demonstrate that the introduction of rain precipitation results in a 5% reduction in light-duty vehicle speeds and a 3% reduction in heavy-duty vehicle speeds. An increase in the rain intensity further reduces light-duty vehicle and heavy-duty truck speeds resulting in a maximum reduction of 9.5% and 5.5% at the maximum rain intensity of 1.5 cm/h, respectively. The results also demonstrate that the impact of rain on traffic stream speed increases with the level of congestion and is more significant than speed differences attributed to various traffic operational improvements and thus shoul...

Evaluation of Safety Benefits from a Heavy-Vehicle Forward Collision Warning System

Forward collision warning (FCW) systems are designed to alert drivers to an impending rear-end (RE) crash, to allow drivers to respond to a crash threat sooner, and thus to reduce their impact speed or allow them to avoid a crash altogether. This study estimates the safety benefits that may be attained by deploying an FCW system across the national fleet of heavy vehicles. The approach involved identifying RE conflicts within a heavy-vehicle naturalistic driving data set with the use of algorithms that identified potential RE events and removed nonthreatening events. Since the heavy vehicles in this data set were not equipped with FCW systems, the FCW auditory alarm severity and timing were introduced into the data with existing FCW system algorithms. Driver perception–response times and braking levels to the computed FCW alarms were modeled with actual driver alarm response behavior recorded in a previous heavy-vehicle FCW field operational test. Driver RE collision avoidance behavior, both with and without FCW alarm feedback, was then simulated with a Monte Carlo simulation approach. The simulation assumed that drivers selected the optimal braking response in the event that multiple FCW alarms were triggered. The number of conflicts avoided and the additional response time available before a crash were then used to assess the safety benefits. This study estimated that FCW systems may afford a 21% reduction in heavy-vehicle RE crashes, which translates to 4,800 crashes per year on U.S. highways.