scholarly journals Traffic Management and Accident Recording and Reporting System for Smart Cities

Accident deaths are a major problem not only in India but the entire world. Statistics are a proof that far more number of accidents deaths are due to car accidents rather than airplane crash deaths. In this paper, the proposed model aims to solve the problem by establishing an information infrastructure that would help connect the street cameras to the concerned authorities like police and ambulance and provide critical assistance to the victims at the fastest. It has been noticed that most of the car accident deaths in India are due to untimely assistance provide to the victims. The proposed solution best works in the scenario of accident prone areas and would save the high operational costs due to human involvement and provide more objective support. The system serves as an information gateway from the street camera to authorities like the police and hospitals. It detects accidents using image processing and sends an alert to the authorities. An adaptive traffic flow system has been introduced at the junctions and it is based on the traffic density in the lanes

2020 ◽  
Vol 32 (2) ◽  
Author(s):  
Imma Widyawati Agustin ◽  
Christia Meidiana ◽  
Sri Muljaningsih

AbstrakBerbagai permasalahan transportasi yang sering dialami dengan kepadatan lalu lintas yang tinggi salah satunya adalah kecelakaan lalu lintas. Kecelakaan lalu lintas di Kota Surabaya pada tahun 2017 tercatat sebanyak 1.338 kejadian kecelakaan. Jumlah kejadian kecelakaan ini didominasi oleh kendaraan pribadi seperti sepeda motor dan mobil. Penelitian ini bertujuan membuat model peluang kecelakaan mobil di Kota Surabaya yang didasarkan pada data karakteristik jalan dan karakteristik pengendara untuk mengetahui tindakan yang tepat dalam menurunkan angka kecelakaan mobil. Metode yang digunakan dalam penelitian ini adalah analisis generalized linear model (GLM) untuk melihat model peluang kecelakaan mobil berdasarkan karakteristik jalan dan regresi logistik biner untuk melihat model peluang kecelakaan mobil berdasarkan karakteristik pengendara mobil. Penelitian ini difokuskan pada six ruas jalan yang memiliki tingkat kecelakaan tertinggi dan sedang, serta diwakilkan dengan 348 responden pengendara mobil. Dari hasil analisis GLM didapatkan model peluang kecelakaan McA = 𝑒𝑒4,5 − 0,707 Lebar badan jalan yang menunjukkan bahwa hanya lebar badan jalan yang mempengaruhi peluang kecelakaan mobil. Hal ini dapat diintepretasikan bahwa jika lebar badan jalan memiliki peningkatan 10% dari lebar badan jalan sebelumnya, maka model pendekatan dengan GLM memprediksi akan terjadi peningkatan jumlah kecelakaan mobil sebanyak 84 korban. Dari hasil analisis regresi logistik biner didapatkan model peluang kecelakaan di mana perilaku pengendara yang mempengaruhi peluang kecelakaan mobil adalah membawa surat berkendara seperti SIM dan STNK (X3.6), mematuhi lampu lalu lintas (X3.10), memberi tanda berbelok/darurat (X3.11), menggunakan sabuk pengaman (X3.12), dan mengantuk saat mengendarai (X3.13).Kata kunci: Model kecelakaan, pengendara mobil, generalized-linear-model, Kota Surabaya.AbstractSimulation Study of Car Accident Model to Improve Traffic Safety in the Urban Area: Various transportation problems that are often experienced with high traffic density, one of which is a traffic accident. The number of accidents is dominated by private vehicles such as motorbikes and cars. This study aimed to make a car accident model in Surabaya Ciy based on the road and the driver characteristics to find out the right actions in reducing the number of car accidents. The study used the analysis of generalized linear model (GLM) and binary logistic regression. It focused on six road segments that have the highest and moderate accident rates, and it was represented by 348 respondents of car drivers. The results of the GLM analysis obtained a probability model of McA = 𝒆𝒆𝟒𝟒,𝟓𝟓 − 𝟎𝟎,𝟕𝟕𝟕 𝟕𝟕 𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹 𝑾𝑾𝑾𝑾𝑾 𝑾𝑾𝑾𝑾 which shows only the width of the road body that affects the chances of a car accident. It can be interpreted that if the road width has increased by 10% from the previous road width, the GLM approach model predicts an increase in the number of car accidents by 84 victims. Furthermore, the driver’s behavior that affects the chances of a car accident include carrying a driver license and vehicle registration (X3.6), obeying a traffic light (X3.10), giving a turning/emergency sign (X3.11), using a seat belt (X3.12), and being drowsy when driving (X3.13).Keywords: Accident model, car driver, generalized-linear-model, Surabaya City.


In smart cities, traffic congestion is one of the significant problems for citizens. Traffic management is an essential one for the quick development of populace and urban movement in metropolitan areas, and traffic blockage is often seeming on streets. To handle different issues for managing traffic on the streets and to help experts in inappropriate arrangement, a smart traffic management system with the IoT (Internet of Things) is proposed in this paper. Mechanisms to utilize IR sensors to distinguish traffic density isn't easy as smooth a solo vehicle recognized at the last sensor so that it can suggest traffic density in high in any event, even if there is free space before it. A technique to be proposed to solve the previously mentioned issues efficiently is by utilizing the Internet of things for traffic management systems. This paper aims to propose a Fuzzy controller to deal with traffics in smart cities. Fuzzy induction used to compute exact traffic, which separates the parking vehicle and moving vehicle. There is an issue of separating parking and un-parking vehicles in the existing systems. So, we planned to solve this using fuzzy logic.


Number of vehicles increasing day by day in the world which results in traffic, air pollution, delay in reaching designation. Traffic density is increased in the roads, especially in the signals. The traffic congestion has negatively affected the efficiency, aggressiveness, and financial development of a nation. Thus, congestion control of traffic has become a significant zone of research, and a substantial number of answers for this issue left different research endeavors in the said field in recent decades. The traffic volume changing after some time, and in this way, long traffic lines are produced at the street intersections. Consequently, the Intelligent Transport System answers these related issues. It has incredible possible and ability to make transportation systems safe and smart efficiently. ITS provides the accessing and driving services of effortlessly participating transportation systems in a smart city. Traffic congestion can be managed in a proper manner by using time estimation and other route diversion in a pre-informed way. For this, we have to calculate the values of traffic congestion density and find the neighboring route. Density algorithm and distance measure algorithm were used to find the traffic density, and the Swarm algorithm was used to find the nearby path.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1633 ◽  
Author(s):  
Beom-Su Kim ◽  
Sangdae Kim ◽  
Kyong Hoon Kim ◽  
Tae-Eung Sung ◽  
Babar Shah ◽  
...  

Many applications are able to obtain enriched information by employing a wireless multimedia sensor network (WMSN) in industrial environments, which consists of nodes that are capable of processing multimedia data. However, as many aspects of WMSNs still need to be refined, this remains a potential research area. An efficient application needs the ability to capture and store the latest information about an object or event, which requires real-time multimedia data to be delivered to the sink timely. Motivated to achieve this goal, we developed a new adaptive QoS routing protocol based on the (m,k)-firm model. The proposed model processes captured information by employing a multimedia stream in the (m,k)-firm format. In addition, the model includes a new adaptive real-time protocol and traffic handling scheme to transmit event information by selecting the next hop according to the flow status as well as the requirement of the (m,k)-firm model. Different from the previous approach, two level adjustment in routing protocol and traffic management are able to increase the number of successful packets within the deadline as well as path setup schemes along the previous route is able to reduce the packet loss until a new path is established. Our simulation results demonstrate that the proposed schemes are able to improve the stream dynamic success ratio and network lifetime compared to previous work by meeting the requirement of the (m,k)-firm model regardless of the amount of traffic.


Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 253-270
Author(s):  
Mohammed Bin Hariz ◽  
Dhaou Said ◽  
Hussein T. Mouftah

This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3658
Author(s):  
Qingfeng Zhu ◽  
Sai Ji ◽  
Jian Shen ◽  
Yongjun Ren

With the advanced development of the intelligent transportation system, vehicular ad hoc networks have been observed as an excellent technology for the development of intelligent traffic management in smart cities. Recently, researchers and industries have paid great attention to the smart road-tolling system. However, it is still a challenging task to ensure geographical location privacy of vehicles and prevent improper behavior of drivers at the same time. In this paper, a reliable road-tolling system with trustworthiness evaluation is proposed, which guarantees that vehicle location privacy is secure and prevents malicious vehicles from tolling violations at the same time. Vehicle route privacy information is encrypted and uploaded to nearby roadside units, which then forward it to the traffic control center for tolling. The traffic control center can compare data collected by roadside units and video surveillance cameras to analyze whether malicious vehicles have behaved incorrectly. Moreover, a trustworthiness evaluation is applied to comprehensively evaluate the multiple attributes of the vehicle to prevent improper behavior. Finally, security analysis and experimental simulation results show that the proposed scheme has better robustness compared with existing approaches.


Author(s):  
Hatem Abou-Senna ◽  
Mohamed El-Agroudy ◽  
Mustapha Mouloua ◽  
Essam Radwan

The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.


2014 ◽  
Vol 24 (2) ◽  
pp. 397-404 ◽  
Author(s):  
Baozhen Yao ◽  
Ping Hu ◽  
Mingheng Zhang ◽  
Maoqing Jin

Abstract Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.


2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.


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