This study identified high-risk locations (hotspots) using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013–2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. The accident concentration analysis was conducted using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran’s I statistics (spatial autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and network spatial weight matrix approaches of the Getis–Ord Gi* statistic were used in the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95–99%. However, hotspots for 2015 and 2016 have a low significance level and the pattern is random. The spatial autocorrelation analysis of the overall accident locations and the Moran’s I statistic showed that the distribution of the accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the northbound and southbound directions of the Abaji–Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.

Conventional highway design approaches have primarily focused on the use of guidelines in the design of highways. These design guidelines provide nominal safety where conservative percentile values of the design inputs are used to account for the uncertainty associated with the inputs. Reliability-based analysis (RBA) been one of the elements of reliability, availability, maintainability, and safety (RAMS) has been identified as an effective method to account for the uncertainty in the design input and to assess the risk related to a particular design. RBA approaches have effectively been used for certain purposes in other disciplines. In highway geometric design literature, these methods were also investigated and showed promise. Given the compelling importance of RBA in highway design, this paper provides a systematic analysis and evaluation of RBA applications for ten highway geometric elements: stopping sight distance, passing sight distance, intersection sight distance, horizontal curve design, vertical curve design, number of freeway lanes, highway grade length, truck escape ramp, and design guide calibration. The review consists of four parts: the concept of RAMS, background on reliability theories, applications in highway geometric design, and guidelines for the use of reliability analysis. The literature review revealed that the application of reliability-based analysis in highway geometric design leads to significant improvements in traffic safety. It is our hope that this paper will serve as a source of information on RBA for highway designers and practitioners, promoting its development and application in highway geometric design.

This study identified high-risk locations (hotspots), using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013-2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. Accident concentration analysis was carried out using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran’s I Statistics (Spatial Autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and Network spatial weight matrix approaches of Getis-Ord Gi* statistic for hotspot analysis were used for the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95% - 99%. However, no hotspots exist for 2014 and 2015 since the pattern is random. The spatial autocorrelation analysis of the overall accident locations with a z-score = 0.0575, p-value = 0.9542, and Moran's I statistic = -0.0089 showed that the distribution of accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the Northbound and Southbound directions of the Abaji-Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.