A GIS-based approach for accident hotspots mapping in mountain roads using seasonal and geometric indicators

Azari, Mehdi; Paydar, Ali; Feizizadeh, Bakhtiar; Hasanlou, Vahid Gara

doi:10.1007/s12518-023-00490-2

Cited by 3 publications

(2 citation statements)

References 56 publications

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“…With the rapid development of urban and commercial sectors, transportation infrastructures have also increased, leading to an upsurge in road traffic accidents. Several geospatial studies showed road traffic accidents to be caused by various factors, such as weather conditions that cause slippery roads [2], the absence of proper road authorities and the management of necessary safety procedures [3,4], and low investment in safety precautions [5]. Additionally, human elements, such as the reckless driving behavior of young drivers and pedestrian negligence, were identified as significant contributors to road traffic accidents [6].…”

Section: Introductionmentioning

confidence: 99%

“…While significant research has explored road traffic accidents [13][14][15][16][17], this study integrates advanced GIS techniques (space-time cube analysis) alongside non-parametric statistical and spatial techniques (Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Kernel Density Estimation (KDE), the Getis-Ord Gi* method) to conduct a spatio-temporal analysis of traffic accidents across the four major Californian cities: Los Angeles, Sacramento, San Diego, and San Jose. Our objectives were as follows: (1) To observe and analyze the spatio-temporal dynamics of road traffic accidents in these developed cities, capturing patterns across different seasons and years; (2) to study the diverse impacts of the traffic density, weather conditions, and population density on accident frequency and severity; and (3) to provide detailed spatio-temporal analyses of accident hotspots and locations. Integrating advanced GIS techniques and statistical analysis in this study provides an understanding of traffic accident dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and Temporal Analysis of Road Traffic Accidents in Major Californian Cities Using a Geographic Information System

Alsahfi

2024

IJGI

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Road traffic accidents have increased globally, which has led to significant challenges to urban safety and public health. This concerning trend is also evident in California, where major cities have seen a rise in accidents. This research conducts a spatio-temporal analysis of traffic accidents across the four major Californian cities—Los Angeles, Sacramento, San Diego, and San Jose—over five years. It achieves this through an integration of Geographic Information System (GIS) functionalities (space–time cube analysis) with non-parametric statistical and spatial techniques (DBSCAN, KDE, and the Getis-Ord Gi* method). Our findings from the temporal analysis showed that the most accidents occurred in Los Angeles over five years, while San Diego and San Jose had the least occurrences. The severity maps showed that the majority of accidents in all cities were level 2. Moreover, spatio-temporal dynamics, captured via the space–time cube analysis, visualized significant accident hotspot locations. The clustering of accidents using DBSCAN verified the temporal and hotspot analysis results by showing areas with high accident rates and different clustering patterns. Additionally, integrating KDE with the population density and the Getis-Ord Gi* method explained the relationship between high-density regions and accident occurrences. The utilization of GIS-based analytical techniques in this study shows the complex interplay between accident occurrences, severity, and demographic factors. The insight gained from this study can be further used to implement effective data-driven road safety strategies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Analysis of Road Traffic Accidents in Major Californian Cities Using a Geographic Information System

Alsahfi

2024

IJGI

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Safety on Jordan's highways: A GIS-Based approach to identifying road accident hotspots

Sababhi,

Aldala’in,

Al Taani

et al. 2024

GeoJournal

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Multiobjective route finding in a multimode transportation network by NSGA-II

Faroqi

2024

J. Eng. Appl. Sci.

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Route finding is an everyday challenge for urban residents. While many route planner applications exist, they cannot find suitable routes based on user preferences. According to user preferences, routing in a multimode urban transportation network can be considered a multiobjective optimization problem. Different objectives and modes for transportation, along with many routes as decision elements, give rise to the complexity of the problem. This study uses an elitism multiobjective evolutionary algorithm and the Pareto front concept to solve the problem. The data of a simulated multimode network consisting of 150 vertexes and 2600 edges are used to test and evaluate the proposed method. Four transport modes are considered: the metro, bus, taxi, and walking. Also, three minimization objective functions are considered: expense, discomfort, and time. The results show the competence of the algorithm in solving such a complex problem in a short run time. The optimal setting for the algorithm parameters is found by considering the algorithm run time, diversity of solutions, and convergence trend by running sensitivity analyses. A repeatability test is applied using the optimal setting of the algorithm, which shows a high level of repeatability. While NSGA-II (Non-dominated Sorting Genetic Algorithm II) may be a well-established algorithm in the literature, its application in multiobjective route finding in multimode transport networks is unique and novel. The outcomes of the proposed method are compared with existing methods in the literature, proving the better performance of the NSGA-II algorithm.

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A GIS-based approach for accident hotspots mapping in mountain roads using seasonal and geometric indicators

Cited by 3 publications

References 56 publications

Spatial and Temporal Analysis of Road Traffic Accidents in Major Californian Cities Using a Geographic Information System

Spatial and Temporal Analysis of Road Traffic Accidents in Major Californian Cities Using a Geographic Information System

Safety on Jordan's highways: A GIS-Based approach to identifying road accident hotspots

Multiobjective route finding in a multimode transportation network by NSGA-II

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