Civil Engineering
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The Department of Civil Engineering has strong affiliation with the Western Transportation Institute (WTI) and the Center for Biofilm Engineering (CBE), a graduated NSF research center. The department is also affiliated with a Montana Department of Transportation Design Unit located on the MSU campus.
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Item Remote Sensing of Weather and Road Surface Conditions(2013-01) Ewan, Levi A.; Al-Kaisy, Ahmed; Veneziano, DavidAdvances in road weather sensing technologies have made noninvasive road weather sensors a valuable component in many intelligent transportation systems (ITS) applications. This study investigates the reliability of using such a sensor for a proposed weather-responsive variable speed limit system. The Vaisala surface state and temperature sensors (DSC-111 and DST-111) were selected for the proposed application. The sensors' ability to provide accurate and reliable data was tested under various conditions in a controlled laboratory environment. Specifically, four outputs of interest from the sensors were tested in this investigation: surface state, snow and ice depth, water depth, and grip level. Testing results showed that the sensors determined the surface state (dry, moist, wet, snowy, and icy) accurately and reliably. The sensors' snow depth readings were found to be inaccurate, while the sensors' ice depth measurements were found to be relatively close to the actual depths. For water depth, only a limited number of readings were close to the actual depths, while other readings were highly inaccurate. In an effort to test the potential of the sensor in providing reliable inputs to the proposed ITS application, a calibration was conducted for the sensor water depth measurements at various water depths and sensor installation angles. Calibration results showed that the water depth could be accurately estimated with the calibrated sensor measurements, regardless of water depth or sensor installation angle. Sensor estimates of grip level were found to be highly correlated to the coefficient of static friction for the conditions considered in this study.Item Safety Effects of Road Geometry and Roadside Features on Low-Volume Roads in Oregon(2016-01) Ewan, Levi A.; Al-Kaisy, Ahmed; Hossain, FahmidCrashes are random events and can occur at any location along a roadway. On roadways with high traffic volumes, the more frequent occurrence of crashes permits the direct identification of high-frequency crash locations with the use of historical data. On low-volume roads, crash occurrence, particularly the occurrence of crashes with fatal and serious injuries, is less frequent. There is a need to understand better the risks associated with geometric and roadside features along low-volume roadways in order to identify locations where preventive countermeasures may be employed. This paper describes the collection and analysis of a large sample of data from low-volume roads in Oregon to quantify the effects of geometric and roadside features on crash occurrence and associated risks. The effects of lane width, shoulder width, grade, side slope, fixed objects near the roadway, and horizontal and vertical curves have been quantified. For the low-volume road sample, roads with lanes less than 12 ft wide have a much higher crash risk than do roads with standard 12-ft lanes. Similarly, roads with narrow or no shoulders tend to have much higher crash rates than roads with shoulders 4 ft or 5 ft wide. Crash risk is shown to be much higher on curves with higher degrees of curvature compared with curves with smaller degrees of curvature.Item Prioritization Scheme for Proposed RWIS Sites: Montana Case Study(2017-08) Al-Kaisy, Ahmed; Ewan, Levi A.A model for prioritization of new proposed environmental sensor station (ESS) sites is developed and presented in this paper. The model assesses the overall merit (OM) of a proposed ESS site as part of a Road Weather Information System (RWIS) using weather, traffic, and safety data among other variables. The purpose of the proposed model is to help in selecting optimum sites for new ESS locations, which is important in guiding RWIS system expansion. Inputs to the OM model include weather index (WI), traffic index (TI), crash index, geographic coverage, and opportunistic factors. The WI at a proposed site is determined using multiple indicators of weather severity and variability. The crash index, another major input to the OM model, incorporates crash rate along the route and the percentage of weather-related crashes over the analysis period. The TI, in turn, reflects the amount of travel on the highway network in the area surrounding the proposed ESS site. The fourth input to the merit model accounts for the ESS existing coverage in the area where the proposed site is located, while the fifth and last input is concerned with the availability and ease of access to power and communications. Model coefficients are represented by weights that reflect the contribution of each input (variable) to the OM of the ESS site. Those weights are user-specified and should be selected to reflect the agency preferences and priorities. The application of the proposed merit model on sample sites in Montana demonstrated the utility of the model in ranking candidate sites using data readily available to highway agencies.Item Economic feasibility of safety improvements on low-volume roads(2017-09) Al-Kaisy, Ahmed; Ewan, Levi A.; Hossain, FahmidThis article presents an investigation into the economic feasibility of safety countermeasures along rural low-volume roads. Although these roads may be associated with higher crash risks as they\'re built to meet lower standards, crash frequencies are notably lower than those on other roadways with higher traffic exposure. Therefore, it is reasonable to expect that some conventional safety countermeasures that are proven to be cost effective on well-travelled roads may turn out to be infeasible on low-volume roads. Twenty-seven safety improvements were examined in this investigation for their economic feasibility along low-volume roads. A roadway sample of 681 miles of Oregon was used in this study. Detailed benefit-cost analyses were performed using countermeasure costs, 10-year crash data, and expected crash reductions using Highway Safety Manual methods. Around half of the countermeasures investigated were found cost-effective for implementation along low-volume roads. Further, most of the countermeasures that were found to have very high benefit-cost ratio are associated with low initial cost and many of them do not require much maintenance cost. At the other end of the spectrum, almost all roadway cross-section safety improvements were found economically infeasible due to higher associated costs relative to the expected crash reduction benefits on low volume roads.