Road Geometric Characteristics Research Articles

Improvements in the Horizontal Alignment and Vertical Profile of Balampur Ghat Section in Bhopal-Vidisha State Highway Road (SH-18) using MXRoad Software

Abstract: Geometric design of highway deals with designing of physical visible features of highway those comprise of horizontal alignment, vertical profile, circular and transition curves, superelevation, Summit and valley curves, cross sectional elements, sight distances and other features. From the safety point of view, road geometric features should be well designed as per the IRC recommendation. In this research work, the horizontal alignment and vertical profile have designed of Balampur Ghat section in the Bhopal-Vidisha Road which is in the Madhya Pradesh State of India. The objective of this research work is “Improvements in the Horizontal alignment and Vertical profile of Balampur Ghat Section in Bhopal-Vidisha State Highway Road (SH-18) using MX Road Software”. The design of horizontal alignment and vertical profile have been done for Balampur ghat section approx. 2.0 km in length of State highway no. 18 (SH-18) of Madhya Pradesh. SH-18 is connected to Vidisha from Bhopal in the state of Madhya Pradesh and having heavy commercial traffic. Balampur ghat section is hilly terrain and have two improper horizontal curves along with 6.5% of vertical gradient and because of this reason that section is not safe for deriving therefore it has become an accident-prone area and the accident-prone area have the human and economical losses so it should be improved and re design of the horizontal and vertical alignment for safe design speed. The proposed methodology is on the basis of inventory survey (preliminary survey), topographic survey and MX Road software. In inventory survey take the data of existing road and find the suitable route of alternative alignment if re-alignment is required in the road. Then the topographic survey done on the existing road and alternative alignment. Import the topographic data of the road in MX Road software for generate existing surface of the road for design of horizontal alignment and vertical profile. As per IRC recommendations, there are two alternative alignments designed of the existing ghat section. As per the outputs of this research work, the length of both improved alignments is short as compare to existing road. There are no improper curves at improved alignment and maximum gradient is 4.2% which is less than the existing gradient (6.5%). The minimum design speed is 40-50 kmph which was 20 kmph in existing road. The both two improved alignments are safer as compare to existing alignment and the design speed of the vehicle has been increased. The improved alignment 2 is straighter than the improved alignment The improved alignment has also reduced the human and economic losses.

Determining Free-Flow Speed on Different Classes of Rural Two-Lane Highways

Current analytical free-flow speed models consider all rural two-lane highways as the same road type despite their different functional significance in the network. The aim of this paper is to develop a prediction model for free-flow speed as a function of speed limit and road geometric characteristics for different classes of rural two-lane highways. The research was conducted on 50 representative sections of the two rural classes of two-lane highways equipped with automatic traffic counters in Serbia. In order to develop the appropriate models, it was necessary to determine the threshold values of vehicle time headway in the free-flow for both classes of rural two-lane highways, based on the total number of 191,720 vehicles. The obtained results show that there are differences in the threshold values of free-flow time headway for different road classes. Namely, it was determined that the values of free-flow time headway for Class I amounted to 6.3 s, and for Class II to 8.4 s. The free-flow speed prediction model for different road classes showed that speed limit had the highest impact on free-flow speed for Class I and II highways, followed by horizontal curve radius and shoulder width.

Estimating operating speed for county road segments – Evidence from Italy

• Operating speed is used to check road design and posted speed limits consistency. • Usually, the 85° percentile of the operating speed (V 85 ) is considered as crucial. • V 85 is estimated as a function of road design and functional features. • New parameters are included to estimate V 85 , compared to the past literature. • Considering the Province of Brescia (Italy), two models are calibrated and tested. Vehicle operating speed is a crucial factor for road safety, as it strictly affects occurrence and severity of crashes. Usually, 85th percentile of the operating speed distributions (i.e., V 85 ) in free-flow traffic condition is widely accepted as a base value of consistency evaluation for homogenous portion of existing roads. Although the computation of V 85 is simple, many road authorities cannot collect speed data for each road. Therefore, providing prediction models could be a useful tool to investigate the relationship between V 85 and road characteristics. The literature proposed several models to account it. However, to the best of our knowledge, the effects of some road geometric characteristics, road markings and signs, traffic data, type of terrain and the simultaneous consideration of different road categories on the V 85 prediction were not completely analyzed. This paper fills this gap by isolating key variables that mostly affect V 85 . In doing so, 60 000+ car spot speed data were collected along the county road network of the province of Brescia (Italy), and then processed by multiple regression models. The main findings show that V 85 increases owing to the presence of a wider or paved shoulder, visible road median markings, a higher number of lanes and a higher percentage of cars with respect to the total traffic flow. Conversely, V 85 decreases as the road axis curvature, the number of accesses and rate of forbidden overtaking increase. In addition, the presence of visible road external markings and the surrounding mountainous terrain contribute to decreasing V 85 . The overall findings may support road authorities to verify roads’ operating conditions and, possibly, adjust the speed limits, especially for existing roads.

Near-term impact of COVID-19 pandemic on seniors’ crash size and severity

Recent research revealed that COVID-19 pandemic was associated with noticeable changes in travel demand, traffic volumes, and traffic safety measures. Despite the reduction of traffic volumes across the US, several recent studies indicated that crash rates increased across different states during COVID-19 pandemic. Although some recent studies have focused on examining the changes in traffic conditions and crash rates before and during the pandemic, not enough research has been conducted to identify risk factors to crash severity. Even the limited research addressing the contributing factors to crash severity were focused on the pool category of drivers and no insight is available regarding older drivers, one of the most vulnerable groups to traffic collision and coronavirus. Moreover, these studies investigated the early impact of the COVID-19 pandemic mostly using up to three months of data. However, near-term and long-term effects of the COVID-19 pandemic are still unknown on traffic collisions. Therefore, this study aims to contribute to the literature by studying the near-term impact of the COVID-19 pandemic on crash size and severity among older drivers. To this end, a relatively large sample of crash data with senior drivers at fault was obtained and analyzed. To identify the main contributing factors affecting crash outcomes, Exploratory Factor Analysis was conducted on a high-dimension data set to identify potential latent factors which were validated through Confirmatory Factor Analysis. After that, Structural Equation Modeling technique was performed to examine the associations among the identified independent latent factors and the dependent variable. Additionally, SEM model identified the impact of the COVID-19 pandemic on seniors’ crash severity. The findings reveal that several latent variables were the significant predictors of crash severity of older drivers including “Driving maneuver & crash location”, “Road features and traffic control devices”, “Driver condition & behavior”, “Road geometric characteristics”, “Crash time and lighting”, and “Road class” latent factors. The binary variable of “Pandemic” was found to be as highly significant as the last four latent factors mentioned above. This means not only were older drivers more likely to be involved in higher crash size with higher severity level during the pandemic period, but also “Pandemic” was a risk factor to seniors as much as “Driver condition & behavior”, “Road geometric characteristics”, “Crash time & lighting”, and “Road class” factors. The results of this study provide useful insights that may improve road safety among senior drivers during pandemic periods like COVID-19.

Road surface and inventory extraction from mobile LiDAR point cloud using iterative piecewise linear model

Roads are one of the main characteristics of cities, and their data should be updated periodically. In this study, a new automatic method is proposed for extracting road surface information and road inventory from a Mobile LiDAR System-based point cloud. The proposed method consists of four steps. First, a three-dimensional point cloud is acquired using the mobile LiDAR scanning raw data. To improve the extraction accuracy, irrelevant points are removed from the point cloud. Piecewise linear models are used in the third step to classify the road surface. Road geometric characteristics such as centerline, profile, cross-section, and cross slope are extracted in the final step. The manually obtained road boundary is compared with the extracted road boundary to assess the classification results. Completeness, correctness, quality, and accuracy measures are range from to . When comparing these measures with previous studies, the proposed method produces one of the highest ones.

Critical impact factors of pedestrians traffic combining multiple data sources in Athens

The aim of the paper is the investigation of the critical factors affecting pedestrian traffic in Athens Downtown, during the pilot implementation of the Athens Great Walk. Two field surveys were carried out, one on pedestrians travel information through questionnaire, and a second one on pedestrian volume through observations. As for the second one, the modal split was also collected. The database was completed with the land use and road geometric characteristics while Covid-19 pandemic data in Greece was also considered. For the analysis, 3 Poisson regression models were developed to define the correlation between pedestrian traffic and the factors affecting it. Results indicate that the factors affecting pedestrian traffic vary. Areas with stores, increased active modes traffic, reduced heavy vehicles traffic are critical factors that affect positively pedestrian traffic in Athens.

Computational intelligence applied to cybersecurity

Computational intelligence applied to cybersecurity

Estimating mountainous freeway crash rate: Application of a spatial model with three-dimensional (3D) alignment parameters

The road alignment is a three-dimensional (3D) curve in nature. In this study, we quantitatively examine the effect of 3D road alignment on traffic safety on mountainous freeways. Geometric parameters of 3D curvature and torsion in mathematics are derived to characterize the 3D road curve. Based on the coordination of different horizontal and vertical elements, 3D road alignment is divided into twelve types of combined alignment. For each alignment combination, the 3D curvature and torsion are calculated according to the differential geometry theory. Regarding crash statistical modeling, the Bayesian spatial Tobit (BST) model is developed to accommodate possible spatial correlation of traffic crashes among adjacent freeway segments. The Bayesian Tobit (BT) model is also built for comparison.A 118-km mountainous freeway associated road geometric features, traffic volume with three years of crash data is used as a case study. The result from the model comparison shows the BST model outperforms the BT model in terms of goodness-of-fit. Parameter estimation result for the BST model shows that the differences of average 3D curvature (and torsion) between adjacent segments have statistically significant effects on the crash rate of the segment, indicating it is necessary to consider three-dimensional alignment parameters in estimating mountainous freeway crash rate. Moreover, by comparing the predicted crash rate calculated by the BST model and the observed crash rate, the result shows the proposed BST model can provide a reliable prediction for freeway crash rates of different combined alignments. This study provides new insight on the effect of road geometric design on traffic safety but also deepens our understanding of spatial correlations in freeway crash modeling.

Modeling and stability analysis of traffic flow considering electronic throttle dynamics on a curved road with slope

To enhance traffic flow stability, the intricacy dynamic of road geometry characteristics on traffic safety is explored in this paper. And an extended macro traffic flow model is proposed coupled with electronic throttle (ET) dynamics effect for a single lane system. Based on the linear stability analysis, we can distinctly find that the stable region will varies due to the change of slope angle when the electronic throttle opening angle is fixed. Characteristics of density wave propagation near the neutral stability lines are described by means of the KdV equation, which is obtain from nonlinear analysis method. The new model also captures the evolution characteristics of shock and rarefaction waves. The simulation example verifies that the road geometric characteristics have a marked impact on the total energy consumption of the transportation system. The traffic congestion can be restrained efficiently by introducing the ET dynamics effect. The numerical simulation shows a good agreement with the analytical result.

Predicting the Segment-Based Effects of Heterogeneous Traffic and Road Geometric Features on Fatal Accidents

Inter-urban roads in Indonesia are characterized mainly by distinct road geometry and heterogeneous traffic features. The accident database from the Republic of Indonesia National Traffic Police recorded a substantial number of fatal accidents and

The Influence Of Traffic Control Devices And Road Geometric Characteristics On Traffic Crushes Of Rular Two Lane Road

Traffic accidents worldwide are among the most alarming phenomena because they cost billions of dollars due to death rates and property damage. In Ethiopia, the accident fatality rate is becoming one of the most serious problems. Specifically, in rural highways where in there are problems with traffic control device enforcement and geometric deficiencies. Gedeo zone faces a similar problem that is considered a hot issue on-road crash. This study focused on the influence of traffic control devices and geometric characteristic related to road crashes. The data collection method was a purposive sampling technique considering both primary and secondary data collection system. Direct field observations were conducted, such as field survey and recording of the existing road geometric elements to figure out which geometric element contributory to traffic crashes. The data collected from the police traffic was categorized by clustering the road into different road segments composed of the same geometric characteristics. The severity of the accident analyzed and identified the hazardous road sections (black spot area). The relationships of accident crash established between the influence of traffic control access devices and geometric elements on the crash reduction at the identified accident-prone areas. Further, the study used ANN modeling through engineering software MATLAB to analyze the weight age of crashes on specified road segments concerning geometric road characteristics. Hence, the gradient carriageway width, super-elevation, cross slope, gradient, sight distance number of the horizontal curve, number of vertical curves, and AADT are the major factors for the occurrence of both fatal and injury at the blackspot segment along the rural highway.

Fuzzy expert system for road type identification and risk assessment of conventional two‐lane roads

AbstractThis paper first presents a fuzzy expert system to identify and classify conventional two‐lane roads based on geometric characteristics. Both fuzzy and neuro‐fuzzy techniques have been used. Fuzzy logic has proved suitable to address this problem, since in this case, there is a variability of input information, and classical rules are not suitable to be used due to the uncertainty introduced by some combinations of the variables. Each road's geometric features were measured by sensors in an equipped vehicle, and are subsequently used to classify the roads according to their real condition. The conventional two‐lane roads used for this research are located in the Madrid Region, in Spain. This intelligent system may be used to update the road database regarding the assigned type to each conventional road, according to their present features and state. Also, a risk identification system has been developed to assess whether a vehicle is driving on a two‐lane road with an inappropriate speed, combining variables such as the former identification model, vehicle type, road longitudinal gradient, the angle covered by each horizontal curve, and the existence or not of an additional traffic lane. A fuzzy risk index is proposed for this approach. This fuzzy model may be useful to detect road sections where safety must be enhanced by revising the speed limit, since less safe situations may arise from travelling at unappropriated speeds.

Impacts of point cloud density reductions on extracting road geometric features from mobile LiDAR data

The variation in point cloud density is driven by many different factors. This variation is expected to affect the quality of the information extracted from the point clouds, however, the extent to which these variations impact the ability to accurately extract and assess geometric features of highways from point cloud data are unknown. This paper investigates the impacts of point density reduction on the extraction and assessment of four critical geometric features. The density of light detection and ranging (LiDAR) data was first reduced and the different features were extracted at varying levels of point density and on a selection of different highway segments in Alberta, Canada. The information obtained at lower point density was then compared to what was obtained at 100% point density. It was found that clearance assessments and sight distance assessments had low sensitivity to reductions in point density (i.e., reducing the point density to as low as 10% of the original data (30 ppm2 on the pavement surface) yielded results comparable to what was obtained at 100% density (300 ppm2) In contrast, for cross section slope estimation and curve attribute estimation higher sensitivity to point density was observed. These findings are critical for transportation agencies considering the adoption of LiDAR technology to manage elements of their infrastructure and for researchers developing data processing tools and algorithms for the semantic segmentation of transportation features from remotely sensed point clouds.

Modelling road traffic congestion at urban merge section under mixed traffic conditions

Identification and evaluation of traffic congestion are critical for better management of urban traffic, especially at merge sections where two different traffic streams converge and generate shockwaves. This study evaluates the travel time reliability measure (travel time index (TTI)) as a reliable congestion measure by analysing the impact of traffic flow parameters such as traffic volume, capacity, road geometrics and conflicting traffic flows at merge sections on TTI under mixed traffic conditions. The data required for congestion analysis were collected through video recording. Statistical models were developed to: (a) evaluate the relationship between road geometric characteristics and capacity of merge sections; (b) estimate traffic density and its evolution with time and compare it against occupancy values; and (c) correlate the relationship between TTI and traffic behaviour at merge sections and determine the variations in TTI for different levels of service of merge sections. The models developed are statistically validated using secondary data sets from the same study section, as well as from data collected from other multi-lane merge sections. The developed model successfully estimated recurring congestion by considering both space and time. This study highlights the potential usage of TTIs in capturing travel time variations more accurately at merge sections under mixed traffic conditions.

Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.

The water film depth is a key variable that affects traffic safety under rainfall conditions. According to the Federal Highway Administration, approximately 5700 people are killed and more than 544 700 people are injured in crashes on wet pavements annually. While several studies have attempted to address water film depth issues by establishing prediction models, a few focused on the relationship among road geometric features, capacity of drainage facilities and water film depth. To ascertain the influence of the geometric features of road and facility drainage capacities on the water film depth, the road geometry features were first classified into four types, and the facility drainage capacities were considered from three aspects in this study. Furthermore, the concept of short-time rainfall grade was proposed according to the results of the field test. Finally, the theoretical prediction model for the water film depth was conceived, based on the geometric features of road and facility drainage capacities with different rainfall intensities. Compared with the traditional regression prediction models, the theoretical prediction model clearly shows the effects of the geometric features of road and facility drainage capacities. When the road drainage facilities have no drainage capacity, the water film depth increases rapidly with the rainfall intensity. This model can be used to predict the water film depth of road surfaces on rainy days, evaluate the effect of rainfall on the driving environment, and provide guidance for determining safety control measures on rainy days.

Transferability analysis of the freeway continuous speed model

Operating speed is often used to evaluate consistency in road geometric design. In the China, the Specifications for Highway Safety Audit includes a spot-based speed model that predicts operating speed by dividing the road into homogeneous segments and observing the speeds at sparsely spaced spots. This paper presents a continuous speed model as a more representative alternative for roads with complex alignments, and can be applied to tunnel sections as one general model. The model considers the road geometric characteristics not only at the vehicle’s current position, but also in its neighborhood by including the effects of adjacent segments. Before such a model can be confidently used, however, its transferability must be confirmed for roads other than those used for the model’s development. This study therefore used data collected at two freeways to demonstrate transferability, as well as the advantages of the continuous speed model over the spot-based model. Results of the spot-based model showed large prediction errors, and changes in the predicted speeds along the road were abrupt and discontinuous. On the other hand, the continuous model’s prediction errors were smaller and the predicted speed profile was, as expected, continuous. The continuous model performed well at estimating operating speed on the studied freeway and, most importantly, it can predict operating speeds for out-of-sample roads of the same type as the studied roads. That is, it passed the transferability test. This finding opens an opportunity for evaluating roads in the design stage while minimizing the number of costly driving simulation experiments. Transferring a continuous speed model is a recommended alternative, particularly when high-priced construction is required for roads with challenging conditions such as mountainous terrain.

Crash model based on integrated design consistency with low traffic volumes (due to health disaster (COVID-19)/movement control order)

Malaysia is listed as one of Asia's developing countries with high-road accidents rate. The accident involves the most between the motorcyclist and other vehicles such as a passenger car which is 17 times safer than the motorcyclist. Current research reveals that the three major forms of incidents in Malaysia are single-motorcycle incidents, passenger car crashes and cars–motorcycles crash. In general, the lack of accuracy of road geometric design, traffic volumes and overlapping movements of vehicles was the main cause of road accidents in Malaysia, which caused drivers to make mistakes and errors due to road geometric characteristics and traffic environments. However, during our recent COVID-19 pandemic, the traffic volumes are relatively low in the whole country as the government announces the movement control order in March 2020. The country was almost completely lockdown (people and vehicles' movements were controlled). In contrast with the reduction of the traffic volumes, the number of crashes shows relatively high numbers. This phenomenon can be derived so that other factors cause vehicle crashes and fatalities should be considered. Several factors related to road geometric such as lane width, shoulder width, access point, curve length and tangent length are considered in developing profiles of operating speed for motorcycles and cars formed of tangents and curves. The analysis of the geometric factors and traffic environments took place at federal road F0050 from 21 to 25 km in Johor, Malaysia. This study was carried out using GPS (DG-200) where the data (vehicles tracked movements) on the continuous speed profiles used a current method of analysis to determine the profiles of road design consistency for motorcycles and cars. The profiles are used to measure the importance index of the integrated design consistency model of the road. The model depends on parameters such as the confine region of speed profiles, average speed, and velocity deviation standard of the profiles. Therefore, a special software of ACAD was used to build the profile of the consistency model. The design accuracy of the speed profile in traffic and safety assessments are affected by the integrated-consistency model. The highest number of accidents has been identified at 24 km at F0050 based on the area design consistency where poor design is the integrated quality consistency model for car and motorcycle. The study shows that crashes and fatalities are not fully affected by traffic volumes but road design performances and driving behaviors.

Accident Prediction based on Integrated Design Consistency with the Lower Number of Vehicles/Traffic Volumes (due to Health Disaster/COVID-19)

Purpose: Malaysia is one of the developing countries that facing high road accident in Asia. The most common accident happens is between motorcyclist and cars. A motorcyclist is 17 times more dangerous than passenger cars. Analysis shows the three main types of accidents in Malaysia is collision with passenger cars, collisions with other motorcycles and single-motorcycle accidents. Road accidents keep rising in Malaysia, because lacks of road geometric design consistency where the drivers make mistakes errors due to the road geometric features. 
 Design/methodology/approach: The study was conducted at F0050 from km 21 until km 25. By using GPS (DG -200), the continuous speed profile data were using new analysis method to develop road design consistency profile of motorcycle and cars and determined the value of the index the integrated road design consistency (IC).
 Findings: The developments of consistency model are based on parameter: the bounded area between the profile and the average speed, standard deviation of speed along a segment. Hence, use ACAD software for develops consistency model’s profile. The integrated-consistency model is the impact of the speed profile on design consistency in traffic and safety evaluations. The highest areas of an accident at km 24 are justified based on the design consistency of the area and integrated design consistency model between of car and motorcycle is poor design. The study shows that crashes and fatalities are fully effected by traffic volumes but road design performances and driving behavior.
 Research limitations/implications: However, the traffic volumes are relatively low in the whole country regarding to the Movement Control Order (MCO) due to the pandemic COVID-19 since March 2020. In contrast to the reduction of the volumes, the number of crashes still shows relatively high. Therefore, it shows that crashes and fatalities are influenced by other factors. Geometric factors such as access point, tangent length, curve length, shoulder width, and lane width are influencing an operating speed profile for developed tangents and curves of motorcycle and cars.
 Practical implications: The result of this study can be used as references to solve accident problems in Malaysia.
 Paper type: This study is categorized as a case study.

Impact of side traffic barrier features on the severity of run-off-road crashes involving horizontal curves on non-interstate roads

Reviewing the literature of run-off-road (ROR) crashes, there is limited knowledge in terms of crashes involving side (longitudinal) traffic barriers on curved segments. For instance, despite the valuable results found in past simulation and field crash tests, no study has been conducted using actual crash data analysis to evaluate the safety performance of side traffic barriers on horizontal curves of non-interstate roads. This paper aims to fill this gap. For this purpose, an actual crash data analysis was conducted to identify factors impacting the severity of crashes involving side traffic barriers on horizontal curves of non-interstate roads in Wyoming. A field inventory was conducted to collect type, height, side-slope rate, lateral offset, and post-spacing of over 105 miles of side traffic barriers located on horizontal curves of non-interstate roads in the state of Wyoming. The data collected includes 25% of all traffic barriers (located on tangent and curved segments) on non-interstate roads in Wyoming. Then, the data was combined with historical crashes, road geometric features, and traffic volume data. For the statistical analysis, random-parameters ordered logit was utilized to model the effect of parameters affecting the crash severity. Post-spacing and height of side barriers were identified to be statistically significant on the crash severity on horizontal curves of non-interstate roads. Side box beam barriers with a post-spacing of 6.1 ft were least likely to result in a fatal or severe injury crash. On the other hand, side box beam barriers with a height shorter than 25 inches showed a high probability of fatalities or severe injuries. It was found that ROR crashes tended to be less severe on side W-beam barriers having a height between 24 and 31 inches. Side traffic barriers with a short height are not recommended to be used on horizontal curves. Based on the results found in this research and past similar studies, it is recommended to consider a height taller than recommendations given by the roadside design guide (AASHTO RDG 2011) on curved segments. Post-spacing of 6.1 ft was found to be recommended to be considered for side box beam barriers.

Mapping road traffic crash hotspots using GIS-based methods: A case study of Muscat Governorate in the Sultanate of Oman

Objective:Road traffic crashes (RTCs) are a major global public health problem and cause substantial burden on national economy and healthcare. There is little systematic understanding of the geography of RTCs and the spatial correlations of RTCs in the Middle-East region, particularly in Oman where RTCs are the leading cause of disability-adjusted life years lost. The overarching goal of this paper is to evaluate the spatial and temporal dimensions, identifying the high risk areas or hot-zones where RTCs are more frequent, using the geocoded data from the Muscat governorate. Data:This study is based on data drawn from the Royal Oman Police (ROP) sample iMAAP database and the National Road Traffic Crash (NRTC) database, managed by the ROP and made available for research use by The Research Council of the Sultanate of Oman. The data covered the period from 1st January 2010 to 2nd November 2014. Only RTCs occurred in Muscat Governorate were included in the study. The study is based on 12,438 registered incidents, however, due to disconnections found on road network, RTCs occurred on disconnected parts were removed and the final analysis considered only 9,357 incidents. Methods:We considered an adjacency network analysis integrating GIS and RTC data using robust estimation techniques including: Kernel Density Estimation (KDE) of both 1-D and 2-D space dimensions, Network-based Nearest Neighbour Distance (Net-NND), Network-based K-Function, Random Forest Algorithm (RF) and spatiotemporal Hot-zone analysis. Findings:The analysis highlight evidence of spatial clustering and recurrence of RTC hot-zones on long roads demarcated by intersections and roundabouts in Muscat. The findings confirm that road intersections elevate the risk of RTCs than other effects attributed to road geometry features. The results from GIS application of NRTC data are validated using the sample data generated by iMAAP database. Conclusion:The findings of this study provide statistical evidence and confirm our research hypothesis that road intersections (roundabouts, crosses and bridges) represent higher risk of causing RTCs than other road geometric features. The results also demonstrate systematic quantitative evidence of spatio-temporal patterns associated with the crash risk over different locations on road networks in Muscat. More importantly, the findings clearly pinpoint the importance and influence of the road and traffic related features in road crash spatial analysis.