Evaluation of the effect of fixed speed cameras on speeding behavior among Iranian taxi drivers through telematics monitoring

Tavolinejad, Hamed; Malekpour, Mohammad‐Reza; Rezaei, Nazila; Jafari, Ali; Ahmadi, Naser; Nematollahi, Ali; Abdolhamidi, Elham; Mehr, Elmira Foroutan; Hasan, Milad; Farzadfar, Farshad

doi:10.1080/15389588.2021.1957100

Cited by 12 publications

(10 citation statements)

References 17 publications

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“…Moreover, fatal and severe injury crashes were reduced by 11–44% in the vicinity of FSC sites ( 20 ). However, several studies indicated the sub-optimal efficacy of FSCs on adherence to speed limits in Asian cities ( 21 – 23 ). One of the potential reasons for FSCs' failure to achieve expected effectiveness is a phenomenon called distance halo or kangaroo driving (KD) ( 23 – 25 ).…”

Section: Introductionmentioning

confidence: 99%

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

Malekpour

Azadnajafabad

Rezazadeh-Khadem

et al. 2022

Front. Public Health

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BackgroundThe adherence to speed limits can reduce deaths associated with road traffic injuries (RTIs) by more than a quarter. This study aimed to evaluate the effective factors on the speeding behavior of Iranian taxi drivers around fixed speed cameras.MethodTelematics devices used in this study collected the location and speed of the vehicles. The units of analysis in this study were trips per camera, including 2.5 km before and after each camera. Linear regression analysis was used to identify kangaroo driving (KD), defined as trips with a significant V-shape in speed distribution around the camera. In the clustered camera zones, cameras were placed at regular intervals of approximately 3.5 km.FindingsA total of 93,160 trips were recorded from 13,857,443 data points. There was an inverse association between drivers' age and KD with an odds ratio (OR) of 0.98 (95% confidence interval: 0.98–0.98). The intercity trips had a substantially higher probability of KD than urban trips (OR: 4.94 [4.73–5.16]). The tendency of drivers toward KD during the daylight hours vs. nighttime was significant for both urban (OR: 1.15 [1.06–1.25]) and intercity (OR: 1.18 [1.14–1.22]) trips. The 4 −8 a.m. period had the highest chance of KD in both urban (10.71% [7.41–14.53]) and intercity (44.13% [41.18–47.09]) trips. There was a significant decrease in the odds of KD inside the clustered camera zones (OR: 0.22 [0.20–0.25]).ConclusionThe heterogeneous occurrence of KD in different locations and times indicates the necessity of evidence-based decision-making in urban planning to improve safe driving behaviors. The lower occurrence of KD in clustered camera zones could be a practical key to the effective control of speeding behaviors by helping in the efficient placement of cameras through sustainable development of cities and roads.

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Section: Introductionmentioning

confidence: 99%

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

Malekpour

Azadnajafabad

Rezazadeh-Khadem

et al. 2022

Front. Public Health

Self Cite

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“…The traffic fines and risky driving in Iran are studied in different ways, including the relationship between the number of traffic offenses and fuel costs within 2011 -2019 (47), the relationship between increasing traffic fines policies and the road traffic law enforcement (48), the prevalence and determination of speeding in Iran (49), the comparison study of traffic fines in Iran and other countries (50), risky driving fined by police in 2006 and 2007 in Tehran (51), the effect of cameras on speeding behavior of taxi drivers in two highways (52), and aggressive violations (e.g., "sound horn to indicate your annoyance", "get angry, give chase", and "aversion, indicating hostility"). Moreover, Iran and Great Britain, the Netherlands, and Finland are among the countries with higher speeding violations than other countries, such as Greek and Turkey (53).…”

Section: Discussionmentioning

confidence: 99%

Investigation of the Hourly and Spatial Patterns of Traffic Offenses During March-April 2019 in Iran Using Bivariate Generalized Additive Models and Integrated Nested Laplace Approximation

Fayaz

Abadi

Razzaghi

et al. 2022

Int J High Risk Behav Addict

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Background: The control, management, and prevention of driving accidents and risky driving are regarded as concerns for numerous countries, according to the World Health Organization. In this regard, many technologies, such as count stations, are recommended. They count traffic offenses, such as speeding and unsafe distance, hourly and daily, and have different patterns according to the hour of the day and the location. Objectives: This study aimed to investigate the risky driving behaviors according to traffic offenses in Iran and estimate their hourly and spatial patterns using generalized additive models (GAMs) and stochastic partial differential equation methods. Methods: There were 2,316 count data stations for one month within March-April 2019. This study estimated the hourly average of each traffic offense, Pearson’s and Spearman’s correlations, and the energy statistics for testing the bivariate normal distribution. There are five distributions, such as univariate Poisson, quasi-likelihood Poisson, Gaussian, location-scale Gaussian, and bivariate Gaussian in GAMs, to study the hourly patterns which were compared to the mean squared error (MSE) and correlation. Results: The hourly average of total vehicles and number of speeding and unsafe distance offenses per count station had positive skew distributions with mean values equal to 347 ± 456, 22.5 ± 44.2, and 65.9 ± 150, respectively. The correlation between traffic offenses in most provinces was significant, not large, and different. The GAM with the bivariate Gaussian distribution had the best performance according to the MSE and correlation. It revealed three hourly patterns for count predictions; the first was that speeding is higher than unsafe distances; the second was that unsafe distances are higher than speeding; the third was that speeding and unsafe distances do not have a specific pattern in some hours. The percentage of speeding was higher in the central, northeast, and southeast regions than in other parts of Iran, and the percentage of unsafe distances was higher for the north, northwest, west, and some parts of the southwest than in other parts of Iran, respectively. Conclusions: The hourly pattern of traffic offenses exists and has a complex structure. The spatial pattern of traffic offenses shows the riskiest points in Iran.

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“…e interference limit in this section considers the interference between the RSU sender pair and the receiver side of the vehicle node V, and the interference between the sender side of the K -relay forwarding and the receiver side of the vehicle node V. (3) is the interference between the K sender and the receiver V in different regions, where k, m, andG denote the channel gain between the k-th relay and the m-th node on the l-th subcarrier.…”

Section: Distributed Allocation Algorithmmentioning

confidence: 99%

“…However, as the granularity of containers is smaller, the number of containers that can be started by one physical machine is also larger, and the resource management for containers is more complex [2]. Common container scheduling tools such as Kubernetes and Docker Swarm Kit only provide some simple resource scheduling policies, which cannot fully utilize the performance of physical machines, so it is crucial to design a reasonable resource scheduling policy for microservice containers [3]. Vehicle networking refers to a system network that carries out wireless communication and information exchange among vehicles, roads, pedestrians, and the Internet on the basis of in-vehicle network, intervehicle network, and in-vehicle mobile Internet according to agreed communication protocols and data exchange standards.…”

Section: Introductionmentioning

confidence: 99%

Telematics Collaborative Resource Allocation Algorithm Based on Cloud Sidecar

Zhang

Shao

Liu

et al. 2022

Security and Communication Networks

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This paper provides an in-depth study and analysis of a distributed allocation algorithm for collaborative resources for cloud-edge-vehicle-based Telematics. The approach starts from the emerging application of urban environmental monitoring based on vehicular networking, with an integrated design of data sensing detection and transmission, and collaborative monitoring of vehicle swarm intelligence based on urban air quality collection to avoid redundancy of information and communication overload. A hybrid routing method with minimal delay for reliable data transmission is proposed. The power adjustment algorithm divides the channel into 3 states. When the CBR is less than 0.5, the channel is in an idle state, and when the CBR is greater than 0.5 and less than 0.8, the channel is in an active state. The algorithm designs redundancy strategies based on coding mechanisms to improve the reliability of data transmission, combines coding mechanisms with routing design, incorporates routing switching ideas, and performs probability-based routing decisions to minimize the delay. In straight-line road sections, a fuzzy logic prediction-based vehicle adaptive connectivity clustering routing algorithm is proposed to reduce the communication overhead during vehicle collaboration and ensure high network connectivity; at intersections, a probability-based minimum delay routing decision algorithm is proposed to reduce the information transmission delay. Experiments show that the proposed method effectively improves the efficiency of data-aware collection and transmission, and increases the reliability of transmission. With the explosive growth of video services, the problem of intelligent transmission of DASH-based video streams has become another research hotspot in mobile edge networks. Based on the edge container cloud architecture of vehicular networking, the resource constraints of microservices when deployed in the edge cloud platform were analyzed, and a multi-objective optimization model for microservice resource scheduling was established with the comprehensive performance objectives of shortest microservice invocation distance, highest resource utilization of physical machine clusters, and ensuring load balancing as much as possible.

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Evaluation of the effect of fixed speed cameras on speeding behavior among Iranian taxi drivers through telematics monitoring

Cited by 12 publications

References 17 publications

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

Investigation of the Hourly and Spatial Patterns of Traffic Offenses During March-April 2019 in Iran Using Bivariate Generalized Additive Models and Integrated Nested Laplace Approximation

Telematics Collaborative Resource Allocation Algorithm Based on Cloud Sidecar

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