摘要: |
Some of the existing software and hardware used by law enforcement agencies to collect crash data are obsolete for several reasons, ranging from budget constraints to lack of coordination across various groups. The most significant consequence of using obsolete tools are location errors, which preclude the correct use and reliability of the data. In addition, the time required for law enforcement agents to be at the scene could be lengthy, especially to collect data adequately. Accurately locating crashes is key to geographic analyses of crash statistics and patterns as well as for the development of safety recommendations for crash ‘hotspots’. Generally, a complex and involved process is required to locate crashes and collect relevant data on public roads, using text formats and hand drawings. Many crashes are unlocated or misallocated, and the data is hard to register. The main impediments to locate crashes accurately and collect crash data are well known, and include errors in data entry, street name errors by the recording officer, the existence of alias names, and county coding errors as well as many other factors. Crash data can be analyzed to study the incidence of the various factors in crashes; for example, information of events involving drivers under the influence of alcohol (DUI) can be used to support decision making. The methodologies for traffic safety management recommended by the Highway Safety Manual (AASHTO, 2010) require accurate crash and location data (Paz et al., 2015), that currently is collected by law enforcement agencies. This data is needed for performance-based traffic safety programs as well, and must be prepared by state agencies to address requirements from the legislators (NCHRP, 2010; FHWA, 2013). To address data-collection issues and provide better technology for law enforcement agents, the Transportation Research Center (TRC) at the University of Nevada, Las Vegas (UNLV) has developed and implemented a system for the accurate and efficient collection of crash data, including location. The proposed solution uses a Geographic Positioning System (GPS) and a Geographic Information System (GIS) to geolocate crashes and provide a map-based data-collection environment. Compared to existing processes and technology in use, this system greatly reduces the time and resources involved in consistency checking and error correcting during data collection. The proposed system was developed with help from various law enforcement agencies in Nevada. Considering the challenges associated with collecting location information as well as the data needs of various stakeholders, in addition to the geospatial coordinates of the crash, the proposed system includes a scene diagram that captures screenshots of the crash location by using a GIS map as well as screenshots of a map where the crash has been located by the police officer. The development, implementation, and testing of the proposed system included continuous interaction between users and developers in order to take full advantage of field experience and associated needs (Racheva and Daneva, 2010). This ensured that the expectations and needs from law enforcement agencies and data users were fully addressed. |