Average Traffic Speed Research Articles

A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China

Rapid urban expansion has brought new challenges to firefighting, with the speed of firefighting rescue being crucial for the safety of property and life. Thus, fire prevention and rescuing people in distress have become more challenging for city managers and emergency responders. Unfortunately, existing research does not consider the negative effects of the current spatial distribution of fire-risk areas, land cover, location, and traffic congestion. To address these shortcomings, we use multiple methods (including geographic information system, multi-criterion decision-making, and location–allocation (L-A)) and multi-source geospatial data (including land cover, point-of-interest, drive time, and statistical yearbooks) to identify suitable areas for fire brigades. We propose a method for identifying potential fire-risk areas and to select suitable fire brigade zones. In this method, we first remove exclusion criteria to identify spatially undeveloped zones and use kernel density methods to evaluate the various fire-risk zones. Next, we use analytic hierarchy processes (AHPs) to comprehensively evaluate the undeveloped areas according to the location, orography, and potential fire-risk zones. In addition, based on the multi-time traffic situation, the average traffic speed during rush hour of each road is calculated, a traffic network model is established, and the travel time is calculated. Finally, the L-A model and network analysis are used to map the spatial coverage of the fire brigades, which is optimized by combining various objectives, such as the coverage rate of high-fire-risk zones, the coverage rate of building construction, and the maintenance of a sub-five-minute drive time between the proposed fire brigade and the demand point. The result shows that the top 50% of fire-risk zones in the central part of Wuhan are mainly concentrated to the west of the Yangtze River. Good overall rescue coverage is obtained with existing fire brigades, but the fire brigades in the north, south, southwest, and eastern areas of the study area lack rescue capabilities. The optimized results show that, to cover the high-fire-risk zones and building constructions, nine fire brigades should be added to increase the service coverage rate from 93.28% to 99.01%. The proposed method combines the viewpoint of big data, which provides new ideas and technical methods for the fire brigade site-selection model.

Valuing traffic emissions' effect on historic buildings: environmental assessment to promote historic buildings’ sustainability

PurposeWith increased populations and movement of people worldwide, traffic emissions will lead to an increase in carbon dioxide emissions, which is one of the greenhouse gases. This will increase outdoor air pollution and other environmental risks that will impact people's health and livelihood, crops, as well as the built environment such as architecture, buildings and other structures. Few studies have been devoted to addressing the effect of air pollution on historic buildings. However, there is no specific study on the impact of traffic-related emissions.Design/methodology/approachA thorough analysis has been conducted in selecting eight historic districts (HDs) among all of 31 located within the city of San Antonio. Motor Vehicle Emission Simulator (MOVES) software has been utilized to process the data collected from the average annual daily traffic (AADT) and vehicle operational speeds and evaluate the amounts of emissions for each HD.FindingsMOVES outcomes showed that HDs are under the threat of deterioration caused by traffic emissions. Therefore, transportation and environmental planners need to implement sustainable solutions to reduce the impact of CO2 emissions on HDs and, ultimately, historic buildings.Originality/valueThis study will help policymakers plan a better course of action for the future conditions associated with the increased traffic volumes. It is also beneficial for the developers, preservationists, architects and all other stakeholders willing to preserve the history of a country.

РОЗРОБЛЕННЯ ЗАХОДІВ ПОКРАЩЕННЯ ДОРОЖНІХ УМОВ НА ДІЛЯНКАХ АВТОМОБІЛЬНИХ ДОРІГ НА ОСНОВІ АНАЛІЗУ УМОВ РУХУ

Introduction. The analysis of road capacity is carried out. Problem statement. One of the reasons for the appointment of the road reconstruction or part of it is the deterioration of traffic safety, resulting in an increase in the number of victims and material losses during traffic accidents. Road capacity is an important indicator during highway reconstruction. The analysis of the road section capacity makes it possible to assess the work of the road during its entire life cycle from the moment of its commissioning to the moment of reconstruction. Existing methods for determining the practical traffic lane capacity, the maximum traffic volume on the highway section give ambiguous results that need to be improved. Purpose. The purpose of the work is to study the average speed, which is one of the factors that determine the maximum traffic volume on the road. Materials and methods. Analysis of the results of experimental studies of average speeds of free movement of different type of vehicles on roads of different categories. Results. The general form of equations of dependence of average traffic speed on radii of horizontal curves and speed on a longitudinal slope is established; the impact of road conditions on the traffic speed according to the study of graphs of average speeds before and after the improvement of traffic conditions on road sections was analyzed. Conclusions. Based on the assessment of traffic conditions with the provision of maximum traffic volume on road sections between intersections and junctions, which determine the traffic volume between them, it is possible to address the need for partial or complete reconstruction of the highway. Keywords: road capacity, traffic volume, highway, intersection, junctions, traffic speed, highway reconstruction.

Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey

As in other countries of the world, the Turkish government is implementing many preventive partial and total lockdown practices against the virus’s infectious effect. When the first virus case has been detected, the public authorities have taken some restriction to reduce people and traffic mobility, which has also turned into some positive affect in air quality. To this end, the paper aims to examine how this pandemic affects traffic mobility and air quality in Istanbul. The pandemic does not only have a human health impact. This study also investigates the social and environmental effects. In our analysis, we observe, visualize, compare and discuss the impact of the post- and pre-lockdown on Istanbul’s traffic mobility and air quality. To do so, a geographic information system (GIS)-based approach is proposed. Various spatial analyses are performed in GIS with the statistical data used; thus, the environmental effects of the pandemic can be better observed. We test the hypothesis that this has reduced traffic mobility and improved air quality using traffic density cluster set and air monitoring stations (five air pollutant parameters) data for five months. The results shows that there are positive changes in terms of both traffic mobility and air quality, especially in April–May. PM10, SO2, CO, NO2 and NOx parameter values improved by 21.21%, 16.55%, 18.82%, 28.62% and 39.99%, respectively. In addition, there was a 7% increase in the average traffic speed. In order for the changes to be permanent, it is recommended to integrate e-mobility and sharing systems into the current transportation network.

Determination of passenger car noise equivalent for mid-sized cities in India

The heterogeneity in traffic flow composition increases the complexity of road traffic noise analysis for mid-sized in India. This study aims to determine a passenger car noise equivalent (PCNE) with respect to the average traffic stream speed that represents the number of a particular vehicle category with reference to an identified vehicle based on their noise emission characteristics. In the present study, vehicles are classified as bus, truck, light commercial vehicles (minibus, minitruck), three-wheelers (vikram-rickshaw), two-wheelers (bike/scooter), car, e-rickshaw and auto-rickshaw, and tractor-trailer. Car is taken as a reference vehicle for estimation of PCNE in our study due to its high percentage in traffic stream. Data has been collected on both bituminous and concrete pavement in Kanpur city, India, to analyze the differential effect of pavement on the noise level. As per this study, tractors-trailers, trucks, three-wheelers, and buses had a higher PCNE value, while two-wheelers and cars had almost similar PCNE value. A comparative analysis of PCNE value at concrete pavement is also conducted by considering car running on the bituminous pavement as reference vehicle. The study suggests to employ PCNE value in traffic noise analysis as it converts the divergent traffic volume in terms of the car.

A Model to Evaluate the Effect of Urban Road Pricing on Traffic Speed and Congestion in Madrid City Center and Its Surrounding

Currently, traffic intensity in large cities and their surroundings constitute the main unsustainability factor associated with urban transport, leading to significant traffic speed reduction due to high levels of congestion. Road pricing seems to be a measure of transport policy capable of improving efficiency and sustainability in urban transport, reducing traffic intensity and increasing traffic speed, as reflected in the main road pricing indicators currently in operation (Singapore, London, Stockholm, Milan…). Based on the data obtained through a mobility survey applied to a theoretical design of road pricing for the city of Madrid, we developed a traffic speed forecast model using time series analysis, to which we applied the mobility survey results. The research results show that theoretical urban road pricing could imply very significant positive effects in traffic speed increase and congestion reduction, fundamentally in the city center and metropolitan crown, as well as demonstrating positive effects in the improvement of traffic speed in those municipalities furthest from the urban center. Moreover, our findings reveal that road pricing would allow an average traffic speed increase in the protected area of the city center during the operating hours of between 10% and 32.5%: 15.9% in the metropolitan crown, 10% in M-30, and 32.5% in the case of Madrid’s city center.

The Impact of the COVID-19 Movement Restrictions on the Road Traffic in the Czech Republic during the State of Emergency

The COVID-19 pandemic crisis has impacted numerous areas of people’s work and free-time activities. This article aims to present the main impacts of the COVID-19 movement restrictions on the road traffic in the Czech Republic, measured during the first epidemic wave, i.e., from 12 March to 17 May 2020. The state of emergency was imposed by the Czech government as a de jure measure for coping with the perceived crisis, although the measure eventually resulted only in a quite liberal de facto form of stay-at-home instruction. Unique country-scale traffic data of the first six months of 2020 from 37,002 km of roads, constituting 66% of all roads in the Czech Republic, were collected and analyzed. For the prediction of the prepandemic traffic conditions and their comparison with the measured values in the period of the state of emergency, a long-term traffic speed prediction ensemble model consisting of case-based reasoning, linear regression, and fallback submodels was used. The authors found out that the COVID-19 movement restrictions had a significant impact on the country-wide traffic. Traffic density was reduced considerably in the first three weeks, and the weekly average traffic speed in all road types increased by up to 21%, expectedly due to less crowded roads. The exception was motorways, where a different trend in traffic was found. In sum, during the first three weeks of the state of emergency, people followed government regulations and restrictions and changed their travel behavior accordingly. However, following this period, the traffic gradually returned to the prepandemic state. This occurred three weeks before the state of emergency was terminated. From a behavioral perspective, this article briefly discusses the possible causes of such discrepancies between de jure and de facto pandemic measures, i.e., the governmental communication strategy related to loosening of movement restrictions, media reality, and certain culture-related traits.

Investigating the Effect of Suburban Buses on Traffic Flow and Carbon Monoxide Emission by Aimsun Simulation Software

Incorrect placement of use in the urban area can affect the demand pattern of trips, traffic flow between the different districts, and air pollution. Traffic simulators were used to study the impact of this factor on traffic flow and pollutant emission in traffic networks. The purpose of this study was to investigate the effect of the incorrect placement of the Tehran West Terminal on the flow of traffic and the amount of carbon monoxide emission in the network using the Aimsun simulation software. Hence, the suburban bus route was simulated from the West Terminal to the Bakery intersection in the presence and absence of suburban buses. Then parameters were investigated, such as carbon monoxide emissions, fuel consumption, delay time, total travel time, and average speed of traffic flow. The results showed that when suburban buses are present in the network, the average traffic speed rate decreased by 7.6%, and the total travel time and network delay time increased by 11.1% and 9.1%, respectively, which in general indicates a decrease in the quality of the in-network traffic flow. Also, fuel consumption and carbon monoxide emissions increased with suburban bus presence in the network by 13.7% and 9.1%, respectively. The results can confirm that lack of attention to urban development limits and ignoring the importance of sustainable urban management in controlling traffic demand can have negative economic and environmental consequences.

Overcoming Challenges of Distributed Fiber-Optic Sensing for Highway Traffic Monitoring

This work presents a wide-area highway monitoring system based on distributed fiber-optic sensing (DFOS) as a cost-effective way of gathering traffic information at numerous sensing points along a fiber cable. The primary advantage of our proposed DFOS system is that it utilizes an existing fiber cable buried beneath the highway to detect and localize the vibrations of passing vehicles. Each section along the fiber cable acts as a sensing point and registers the vibration of nearby vehicles. The amplitude and location of vibrations as measured by DFOS can supplement the information obtained from existing point sensor systems (traffic camera, inductive loop detector) which are typically installed hundreds of meters apart. We trained a neural network for speed estimation ( SpeedNet) and also proposed novel solutions to some of the challenges posed when using DFOS to monitor traffic. To demonstrate the potential of DFOS, we conducted a field test for two days on a 45-km section of the Tomei expressway in Japan. Our proposed SpeedNet model estimated average traffic speeds every minute for an overall accuracy of over 90% as compared with existing loop detector-based sensors. As cameras suffer from weather and intensity changes, and loop detectors can be difficult to install at multiple locations, monitoring traffic using DFOS over an existing fiber-optic cable shows tremendous potential.

Decrease in average traffic speed and increase in harmful emissions of vehicles at unregulated pedestrian crossings in cities

The problem of environmental pollution is one of urgent problems of mankind. This problem especially applies to large cities of any state. Atmospheric air, which performs life-supporting, protective and other functions, is subject to the greatest change. Increased air pollution leads to a negative impact on public health. So, every year number of social movements and various events is growing, expressing great concern about the state of air in the city of Bishkek. Basically, organizational and technical measures are aimed at improving road safety by reducing speed. But along with a decrease in traffic speed, fuel consumption increases, which in turn leads to a proportional increase in exhaust gas emissions. Especially in places where artificial irregularities are established, intensive braking occurs, followed by acceleration of the vehicle. This article is devoted to assessing the impact of unregulated pedestrian crossings on average speed of traffic and emission of harmful substances by vehicles. Relationship between the average traffic speedat unregulated pedestrian crossings and the total delay of vehicles has been established. An increase in emissions from vehicles at unregulated pedestrian crossings is substantiated, which makes it possible to calculate the cumulative emissions from vehicles on the sections of the city’s road network more accurately. This article presents the results of experimental studies of the influence of artificial irregularities, stopping points and parking places on the traffic speed and emissions of exhaust gases into the atmosphere.

Impact of Traffic on Carbon Monoxide Concentrations Near Urban Road Mid-Blocks

An increase in population, number of vehicles and rate of urbanization have happened drastically in the past decades, resulting in deteriorating air quality and a threat to the environment. Vehicular emissions are among the primary and noted sources of air pollution in urban areas. Carbon monoxide (CO) is one of the major pollutants emitted from vehicles, affecting the environment adversely. The present study attempts to develop models to predict CO concentrations at different mid-block sections of urban roads using multiple linear regression (MLR) and artificial neural networks (ANN) methods. The proportional share of vehicles and average traffic speed are considered as inputs to the models. The traffic volume, speed and CO concentrations collected at different mid-block sections have been analyzed. A good correlation between average traffic speed, traffic volume and CO concentrations was observed. The study also shows that the classified traffic volume and average traffic speed in a mid-block could help explain the variance in CO levels significantly, with R2 value of 0.91 and 0.97 for MLR and ANN models, respectively. It has been observed that the CO level would be as high as 14 ppm at or below the average speed of 25 km/h for moving vehicles. The linear increase in CO concentration was found due to decrease in average speed of traffic stream. The model validation illustrates that the estimated CO concentrations match well the observed CO concentrations under the same set of traffic and roadway conditions with an MAPE value of 0.18% and 0.11% for MLR and ANN models, respectively. It seems interesting to see that the ANN model had better predicted the CO values than MLR model. This study considers developing cities to determine the CO levels. The results of the study would help Pollution Control Board officials and traffic control authorities to implement necessary measures for improving air quality in the cities under consideration.

Effect of a traffic speed based cruise control on an electric vehicle s performance and an energy consumption model of an electric vehicle

This paper proposes a cruise control system (CCS) to improve an electric vehicle's range, which is a significant hurdle in market penetration of electric vehicles. A typical driver or a conventional adaptive cruise control (ACC) controls an electric vehicle (EV) such that it follows a lead vehicle or drives close to the speed limit. This driving behaviour may cause the EV to cruise significantly above the average traffic speed. It may later require the EV to slow down due to the traffic ripples, wasting a part of the EV's kinetic energy. In addition, the EV will also waste higher speed dependent dissipative energies, which are spent to overcome the aerodynamic drag force and rolling resistance. This paper proposes a CCS to address this issue. The proposed CCS controls an EV's speed such that it prevents the vehicle from speeding significantly above the average traffic speed. In addition, it maintains a safe inter-vehicular distance from the lead vehicle. The design and simulation analysis of the proposed CCS were in a MATLAB simulation environment. The simulation environment includes an energy consumption model of an EV, which was developed using data collected from an electric bus operation in London. In the simulation analysis, the proposed system reduced the EV's energy consumption by approximately 36.6% in urban drive cycles and 15.4% in motorway drive cycles. Finally, the experimental analysis using a Nissan e-NV200 on two urban routes showed approximately 30.8% energy savings.

Influence of Large Vehicles on the Speed of Expressway Traffic Flow

Large vehicles impact the quality of traffic flow. To predict the impact of large‐scale vehicles on the average speed of traffic flow, vehicle speeds under different vehicle mixing rates were collected through field observations. A laser roadside traffic survey instrument with automatic vehicle type identification functionality was used to collect cross section traffic flow data. The v/C ratio, large vehicle mixing rate, and average speed of traffic were calculated for each data set. A total of 158 traffic flow data sets were captured and divided into three groups according to the v/C ratio of the expressway. The v/C ratio ranges of the three groups are v/C ≤ 0.35, 0.35 < v/C ≤ 0.55, and 0.55 < v/C ≤ 0.90. SPSS software was used to analyze the correlation between the vehicle mixing rate and the average speed under different traffic flow conditions, and a model was determined between the average speed of the vehicle flow and the large vehicle mixing rate. Analysis of the results with SPSS revealed a negative logarithmic linear relationship between the average traffic speed and the mixing rate of large vehicles. The results could also be applied to passenger cars. The models are considered as corrections of the average speed of the traffic flow after the mixing of large vehicles. When the mixing rate of large vehicles is close to zero, the forecast value of the model is the average speed of passenger cars. Furthermore, as the traffic volume of the road section increased, the influence of the mixing rate on traffic flow speed became more obvious. The adaptability of the proposed prediction model of the expressway mixing rate was verified by evaluating model predictions against actual measurements.

Deep Behavioral Cloning for Traffic Control with Virtual Expert Demonstration Under a Parallel Learning Framework

Intelligent traffic signal control is necessary for improving traffic efficiency. These fast changing and challenging traffic scenarios and demands are generally handled by professional traffic engineers. However, it may take years of time and thousands of practices to train such an engineer. This paper proposes a deep behavioral cloning method to learn how to control the traffic signal effectively and efficiently from virtual expert demonstration. The method imitates promising working behavior of optimized offline solutions, and applies it to solve online traffic signal control problems of the similar scenario. Different traffic demand patterns are generated through a combination of different kinds of components. Then the virtual demonstration is constructed by getting an exclusive and optimized solution for each generated virtual traffic demand pattern through a heuristic random search method. After that, a deep neural network-based behavioral cloning method is employed to learn from the virtual demonstration and finish on-line traffic signal control task. The experimental results show that compared with other methods, the proposed method significantly reduces the waiting time and time loss in different situations. And the average traffic speed of the road network at different saturation levels can be improved by 1.58% to 11.54%.

The Impact of Flexible Platoon Formation Operations

Vehicle platooning, a coordinated vehicle movement strategy, has been proposed to address a range of current transport challenges such as traffic congestion, road safety, energy consumption and pollution. While the current literature mainly focuses on platoon control strategies and intra-platoon communication, comparatively little work is done on how to form these platoons. Literature assumes platoon formation by tail merge which is sufficient only for planned formation on a ramp or at a ramp-highway junction. In this article we study the impact of three different merge operations, namely front, middle, and tail merge. The efficiency of these operations is analyzed under different scenarios, varying the vehicles speed adjustment strategy, traffic density, and the density of mergeable vehicles. The impact of the merge operations is represented in terms of merge time, merge distance, average traffic speed, and merge success rate. Our experiments show that in an ideal no traffic scenario, the middle merge is costlier in terms of merge time for the same merge distance whereas in the presence of traffic middle merge helps is quick platoon formation on an average in a higher traffic density in particular. This insight should provide a more flexible toolkit for planning a platoon formation.

Simulation and modeling traffic flow based on Division K Nearest Neighbor

A new traffic flow model is proposed based on cellular automata and Division K Nearest Neighbor for the predication problem of traffic flow state change trend. The model firstly gives the update rules of vehicle state evolution and lane change rules of a vehicle, and establishes the state prediction model based on Division K Nearest Neighbor. Finally, the simulation analysis is conducted by the use of experimental platform, and the relationship between the factors such as average traffic flow speed, average flow rate, traffic flow density and lane change frequency, etc. is deeply studied. The results show that the prediction model has great advantages in the medium and low density area, and lower lane change rate has limited effect on the improvement of traffic flow.

Performance Evaluation of Unsignalized Intersection and Anticipated Alternative Solutions for Designated Corridors in Wolaita Sodo Town

The growth of traffic congestion on many streets, intersections and highways is a major concern to travelers, administrators, merchants, developers and the community at large. Its detrimental impacts in terms of longer journey times, higher fuel consumption, increased emissions of air pollutants, greater transport and other affected costs and changing investment decisions are increasingly recognized and felt across the country. Congestion reduces the effective accessibility of residents, activities and jobs resulting in lost opportunities for both the public and business. This issue is now days a great concern for Ethiopia and major cities in the country. Due to this evaluation of traffic congestion and determination of level of service with the cause of traffic congestion is the first step. From these major cities in Ethiopia, Wolaita Sodo city is now highly observed by traffic congestion especially at intersections. In this paper, first data of traffic volume count, entry time, and departure time and road width collected. Then average traffic speed ,traffic volume and traffic headway in terms of level of service and function were analyzed by using HCM-2000 and Microsoft excel sheets for only three most congested intersections. Keywords: Capacity, Congestion, Intersections, Performance Evaluation DOI : 10.7176/CER/11-10-02 Publication date: November 30 th 2019

Mathematical models to determine the influence of road parameters and conditions on vehicular speed

The study of vehicular movement modes in adverse weather conditions allowed defining the dependence of traffic modes at certain road segments on weather conditions. It is found that the average vehicle speed changes within a year over a wide range depending on road conditions even on its straight horizontal sections. There is a considerable difference in the maximum speed of traffic movement. Complex road sections significantly influence the traffic mode during any period of the year, especially in adverse weather conditions. The road surface condition exerts the greatest impact on the traffic speed. If the adhesion coefficient equals 0.2-0.3 the average traffic speed is 20-25% lower than if that adhesion coefficient equals 0.5-0.6, and in ice conditions the average traffic speed decreases by 40-50%. The proposed calculation formula allows defining the influence of weather conditions on the traffic mode of free-moving cars or cars in a joint traffic flow. It provides for the feasibility study regarding measures aimed to increase the traffic speed in adverse weather conditions of the year. Based on the observations and calculations the correlation dependences of average and maximum traffic speeds on the adhesion coefficient within a 7.0 m-wide road without the hard shoulder were obtained.

Estimation of real-world traffic emissions for CO, SO2, and NO2 through measurements in urban tunnels in Tehran, Iran.

Mobile sources are considered to be one of the most important sources of air pollution among which are motor vehicles, recognized as the major contributor of air pollutants in urban areas. To determine the emissions for CO, SO2, and NO2 from motor vehicles as part of the attempt to realize the extent of traffic air pollution, measurements were carried out in two heavily traversed traffic tunnels in Tehran metropolitan area. The concentrations of pollutants and metrological and traffic data were collected through intensive measurements from September 27 to October 17, 2016. Resalat Tunnel fleet was composed of about 10% diesel-fueled vehicles and 90% non-diesel-fueled vehicles while throughout the entire duration of our campaign, only non-diesel-fueled vehicles traversed Niayesh Tunnel. Under an average traffic speed of 43 km h-1, emission factors from Resalat Tunnel campaign were measured to be (6.59 ± 2.69)E+3, (1.42 ± 0.84)E+2, and 6.80 ± 4.99 mg km-1 for CO, SO2, and NO2, respectively. These values were respectively 11% higher, 22% lower, and 40% higher than those from Niayesh Tunnel measurements which were recorded at a traffic speed of 30 km h-1. Current results indicate that the vehicular emissions in certain countries, especially the developing ones and in this case, Iran, are quite different from those measured in developed countries and that the high emission levels of SO2 in Iran are associated with the high sulfur content of the gasoline.

The impact of the average traffic flow speed on occurrence risk of road crash

Traffic flow characteristics have a significant impact on occurrence risk of road crash. The most important characteristics of the traffic flow, the impact of which is the subject of numerous studies, are the traffc flow, density, average traffic flow speed, dispersion of traffic flow speeds, as well as the contents of vehicle in traffic flow. These characteristics are in strong correlation between each other, so changes in one parameter conditional make change of other parameters. Research shows that speed-related traffic flow parameters have a significant impact on occurrence risk of road crash. Therefore, in this study an analysis of the impact of the change in the average speed of the traffic flow on the risk of an accident occurred. The research includes a section of the single carriageway from Preljina to Ljig. After the construction of the highway in the stated section of the signle carriageway, a change in the characteristics of the traffic flow occurred, with this study examining the impact of changing the average speed of the traffic flow to the occurrence risk of road crash. The connection between the speed of traffic flow and the risk of accidents has been confirmed in this study, so with the increase in average speed the risk of accidents increases.