Levi Ewan

Safety Effects of Road Geometry and Roadside Features on Low-Volume Roads in Oregon

Crashes 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.

Prioritization Scheme for Proposed Road Weather Information System Sites: Montana Case Study

Weather presents considerable challenges to highway agencies both in terms of safety and operations. From a safety standpoint, snow, ice and other forms of precipitation may reduce pavement friction, increasing the potential for crashes when vehicles are traveling too fast for the conditions. From an operations standpoint, heavy snow storms may affect the connectivity of the highway network due to closures that need to be cleared in an efficient and timely fashion. Further, travelers should be informed about unusual pavement conditions and road closures on time to minimize the effect of adverse weather on the safety and mobility of the traveling public. For the aforementioned reasons, road weather information has become increasingly important for highway agencies particularly in regions that experience harsh winter weather conditions. Road Weather Information System (RWIS) consists of the hardware, software, and communications interfaces to collect and transfer road weather observations from or near the roadway to a display device at the user’s location (1). Today, most environmental sensor stations (ESS) for RWIS include various atmospheric sensors, some form of pavement sensor, and camera imaging. Additional sensors are also being added to some ESS locations to measure traffic volumes, traffic speeds, and vehicle classifications and weights (2). Road weather information has been used by highway agencies in many applications such as winter maintenance, traveler information, and other weather-related intelligent transportation systems (ITS) applications. Data adequacy, reliability, and geographic coverage are critical attributes to consider for these transportation applications. Highway agencies are often faced with the challenge of selecting a limited number of ESS sites from a larger pool of proposed sites given the limited budgets available. This process has been largely subjective in practice, relying on the expertise and judgement of the agency staff involved. Therefore, there is a need for an objective prioritization scheme for proposed ESS stations, which should guide future RWIS expansion and ensure maximum utility (benefits) from new ESS installations.