Crashes in Iran annually lead to devastating consequences, resulting in loss of life and significant property damage. To mitigate these impacts, the deployment of fixed and mobile speed control cameras has been adopted as a strategy to regulate traffic and improve road safety. The aim of this study was to examine the behavior of drivers when approaching speed control cameras and their influence on crash occurrence. Fatal crash data from three consecutive years (2020-2022) were collected and analyzed using the Geographic Information System (GIS) in Tabriz City. Approximately 27 speed cameras located in crash-spots were investigated within 100-meter sections, both preceding and following the cameras. The results showed a significant reduction in fatal crashes within a 500-meter radius before the speed control cameras. However, crashes were more frequent within distances ranging from 500 to 1000 meters before the cameras, primarily occurring during the night. After passing the cameras, daily crashes increased, with incidents primarily involving pedestrians due to driver inattention occurring within the 500-meter range after the camera's location. The present study not only emphasizes the potential of speed control cameras in promoting safer driving behaviors, but also stresses the importance of conducting further investigations on drivers’ behaviors after passing the speed control cameras to enhance road safety measures.

Speed is considered as one of the most important factors in accidents. Using speed management methods and law enforcement by police can be effective in decreasing accidents caused by speed, but a few studies have been done about the effectiveness of these methods. By considering the previous studies information, the main purpose of this study was evaluating the effect of speed law enforcement on decreasing accidents. In this study the highway of Tabriz-Qazvin was examined in order to evaluating the effectiveness of using mobile speed control cameras on accidents caused by speed and SPSS software had been used for analyzing data. Information related to violations, accidents and the number of speed control cameras were collected and evaluated in consecutive years. After calculation it was realized that 33 percent of accidents depended on the number of violations and also 38 percent of decreasing accidents were for the number of speed control cameras.

Among government organizations, police has always been pioneer in providing better service to individuals in society. Now regarding sensitivity related to police service, the importance of using new technology such as information technology can become clear. On the other hand updating equipment and keeping pace with world full of accelerating changes can increase performance and organization efficiency and improve it position in the mind of individuals in the society. This topic has created many values for organizations. Disciplinary and service providing organizations such as police are not exceptional. Today speed control cameras are one of the most important deterrent factors for unauthorized speed and have a great role in providing better service to people. In this article in addition to speed control cameras, a conceptual model introduced to show the influence of technology and emphasizing the role of technology in improvement of police service quality described.

The present study is firstly aimed to identify, and prioritize factors affecting accidents on rural road of Ahar-Tabriz using artificial neural network (ANN), TOPSIS and multinomial logistic regression (MNL) models. Secondly, this study compares the results of priorities in three models based on preventive and reactive methods. The results of ANN model indicated that this model predicts accident severity via 86% in which prioritized factors such as horizontal and vertical curves, percentage of heavy vehicles, pavement condition, road drainage condition, volume of passing cars and use of speed control cameras, respectively. However, TOPSIS model has shown that the priority of the infrastructure factors affecting road safety include drainage condition, pavement condition, use of speed control cameras, horizontal and vertical curves, road signs, percent of heavy cars, road lighting condition, vehicle volume, and traffic calming, respectively. In addition, MNL model indicated that this model is capable of prediction in accident severity via 74.82% in which pavement condition, use of speed control cameras, road lighting condition, vehicle volume, and road signs are ranked as the most effective factors involved with accidents on rural roads, respectively. Therefore, by making a performance comparison based on Spearman's rank correlation coefficient, T-test analysis, it is found that there is no difference ANN and MNL models, however, there is a significant difference between TOPSIS and other models.

Based on the change in classification of the ten most important reasons of early death of diseases and injuries¡ traffic accidents will be changed from ninth reason to third reason in coming decade. Considering the most important reason in traffic crashes is exceeding allowable speed¡ this study is aimed to estimate the amount of effects of speed controlling cameras on the declining the number of accidents and the speed chosen by drivers. To gain that¡ some statistical descriptive criteria have been used to analyze records of speed and traffic volume on the freeway between Zanjan and Tabriz. These criteria are used for the data recorded in 1390¡ 1391 and 1392. Estimate the impact of speed cameras on reduce accidents on the future with using of ARIMA modeling of time series techniques have been performed.The analysis revealed a decrease cameras installed in Tabriz-Zanjan Freeway (3 ± 20%) at an average speed of passing vehicles. The reduction of (4 ± 30%) in violation of the speedlimits and eventually recorded over speed limit is too low.This study shows the cameras have had a significant effect on average speed reduction in general in all length of the freeway.

Correct identification of high collision segments and prioritization of these segments to intelligent transporta tion system (ITS) location is the most essential factors in rural safety enhancement. In this regard, speed control camera, including automated speed control (ASC) and automated section speed control (ASSC), play important role in rural network safety problem. By considering desirable effect of ASSC on high collision segments, it is beneficial that implement ASSC rather than ASC. So in this paper, we present effectively important criteria in cluding safety, traffic and numeral criteria to ASSC placement. The model is implemented on Tehran-Bazargan corridor (900 KM length). As a result, it is recommended that 21 speed cameras to monitor the high collision segments on this corridor.

The present study aims to identify the inconsistencies resulting from the interferences between the geometric features of the highway, access points and traffic control devices by extracting the frequent association rules and discovering the patterns that contribute to the recurrent crashes. A case study was conducted on a 117-kilometer urban highway around Mashhad. The data for five years of crashes were procured from the corresponding authorities and placed on the network under a geo spatial software environment. Then, the all features of the highway were collected. The trip times between the nodes and existing features were calculated via coding based on the data obtained from one of the route planning software. The operating speed was subsequently estimated. According to the obtained databank and considering the geometric features of the road (horizontal and vertical), the access points, road width, operating speed and position of the traffic control devices (signs and speed control camera), efforts were made to divide the road to the sections. Allocating the crash data to the sections and using the FP-Growth Algorithm, the frequent rules affecting the recurrent crash occurrences were extracted. The results showed that there are different combinations of the geometric road-related factors such as flat-straight alignment and horizontal curve along with cases like right-hand exit, consecutive entrance and exit, and reduced road width in addition to the presence of speed control camera and advanced direction signs on the highway sections together cause inconsistencies like the recurrent crash occurrences.

Highways are among the most important elements in urban transport. Highway connecting different parts of a city, enabling quick access in the city offer. That is why many people use such transportation facilities every day. There are many factors that affect the efficiency of a given highway. These factors can be found under a number of categories like design, maintenance, facilities, rules and regulations and other factors categorized. In European countries, to create structures and highways sustainable development and particular attention is its features. That is why the measures taken and their application in accordance with Iran could help to improve level of services of highways. Attention and budget allocation should be provided. The results suggest that police patrols with 30.4% in the first order of importance, were in the building at 25.3%, patrols monitor the road with 17.4%, especially third, fourth and highway police intangible 11.7 %, constant speed control cameras with 10% in the fifth and final time are also air patrols and helicopters.

Due to the fact that accidents at cities entrance roads have a significant role in road accidents. Accordingly, this issue has been one of the challenges of the last decade to reduce accidents and provide appropriate strategies for increasing the road safety. Thus, the objectives of the present study are first to identify and prioritize the factors affecting the accidents of cities entrance roads in 26 different types of roads in Tehran, Isfahan and Yazd provinces using artificial neural network - multilayer perceptron (ANN-MLP) and Poisson Regression (PR) models. Then, the study presents a road safety strategy model for controlling accidents regarding effective factors prioritized with various degrees of road performance. The results of the present study showed that the best model is the feed-neural network with Levenberg-Marquadt training function with 7 input variables, and 5 hidden neurons which the root mean square error (RMSE) of this model is 1.020 which includes longitudinal slope, operating speed, change the number of lanes, the percentage of heavy vehicles, degree of road performance, speed control camera, and road width. However, PR model indicated that operating speed, longitudinal slope, road width, change the number of lanes, degree of road performance, and the percentage of heavy vehicles. Further, the results of the proposed strategies to reduce the accident based on ANN-MLP, and PR models showed that longitudinal slope among all variables decreased number of accidents by 40%, and 45% for arterial roads class I, respectively.

Speed management is one of the most effective methods for controlling vehicle speeds. Using speed control devices is one of the most important and effective method for preventing speed violations on road. Considering the high cost of intelligent speed control systems, limits on financial budget projects and other restrictions, covering all the road segments by speed control system is uneconomical and almost impossible. Therefore, speed control systems required to be used only where it can have significant effect. In this paper, it is tried to develop a optimization model for maximizing the speed enforcement coverage on road. Various restrictions for locating speed cameras like physical characteristics of the road segment, accident statistics, and traffic volume were considered in optimization process. The Case Study is a part of Karaj-Chalus road from Amir-Kabir square to Gachsar with 60km length. The results were analyzed for different levels of budget.