scholarly journals Supervision and Law Enforcement on Intelligent Transportation Systems on the Highway

2021 ◽  
Vol 2 (1) ◽  
pp. 125-131
Author(s):  
Nur Kumala Dewi

This research discusses the supervision and law enforcement on the transportation system, which will be applied to the smart transportation system. With this system, the police and local governments will be able to monitor the transportation system in a city, especially law enforcement on roads. The method used in this study is to use a literature review which is the basis for this research, by using a literature review it will be able to deepen a research, and be able to understand previous studies in order to create new research. The problem raised in this research is how to apply law enforcement on the highway to land transportation, both public vehicles and private vehicles that are on the highway every day, with strict law enforcement it will reduce crime on the road and can reduce accidents on the road Highway. This research will produce a proposed system, which can be used by the police and local governments in enforcing the law on public or private vehicles on the road.

Author(s):  
A. H. Nourbakhsh ◽  
M. R. Delavar ◽  
M. Jadidi ◽  
B. Moshiri

Abstract. Intelligent Transportation Systems (ITS) is one of the main components of a smart city. ITS have several purposes including the increase of the safety and comfort of the passengers and the reduction of the road accidents. ITS can enhance safety in three modes before, within and after the collision by preventing accident via assistive system, sensing the collision situation and calculating the time of the collision and providing the emergency response in a timely manner. The main objective of this paper is related to the smart transportation services which can be provided at the time of the collision and after the accident. After the accident, it takes several minutes to hours for the person to contact the emergency department. If an accident takes place for a vehicle in a remote area, this time increases and that may cause the loss of life. In addition, determination of the exact location of the accident is difficult by the emergency centres. That leads to the possibility of erroneous responder act in dispatching the rescue team from the nearest hospital. A new assistive intelligent system is designed in this regard that includes both software and hardware units. Hardware unit is used as an On-Board Unit (OBU), which consists of GPS, GPRS and gyroscope modules. Once OBU detects the accident, a notification system designed and connected to OBU will sent an alarm to the server. The distance to the nearest emergency center is calculated using Dijkstra algorithm. Then the server sends a request for assistance to the nearest emergency centre. The proposed system is developed and tested at local laboratory conditions. The results show that this system can reduce Ambulance Arrival Time (AAT). The preliminary results and architecture of the system have been presented. The inclination angle determined by the proposed system along with the car position identified by the installed GPS sensor assists the crash/accident warning part of the system to send a help request to the nearest road emergency centre. These results verified that the probability of having a remote and smart car crash/accident decision support system using the proposed system has been improved compared to that of the existing systems.


Author(s):  
Vikram Puri ◽  
Chung Van Le ◽  
Raghvendra Kumar ◽  
Sandeep Singh Jagdev

In urban transportation systems, bicycle sharing systems are majorly deployed in major cities of both developed and developing countries. The recent boom of bicycle sharing system along with its upgraded technology have opened new opportunities towards urban transportation system. With the enlargement of intelligent transportation systems (ITS's), smart bicycle sharing schemes are more popular to smart cities as a green transportation mode. In this article, the Internet of Things (IoT) and artificial intelligence-based monitoring devices have been proposed for the bicycles. This system contains a harmful exhaust gas sensor, wireless module, and a GPS receiver and camera that are capable to send data with time and date stamping. In addition, sensor also integrated on the bicycle for the fall detection. An artificial neural network (ANN) and support vector machine (SVM) applied to the data collected at central server is designed to analyze the root mean square error (RMSE), and coefficient of correlation (R2). Result shows that ANN performance is better when compared to SVM.


MATICS ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Raphael AKINYEDE

<p class="Text"><strong>—<em> </em></strong>In Vehicular Ad-Hoc Networks (VANETs), wireless-equipped vehicles form a network spontaneously while traveling along the road. The direct wireless transmission from vehicle to vehicle makes it possible for them to communicate even where there is no telecommunication infrastructure; this emerging new technology provide ubiquitous connectivity to vehicular nodes while on the move, The main idea is to provide ubiquitous connectivity to vehicular nodes while on the move, and to create efficient vehicle-to-vehicle communications that enable the Intelligent Transportation Systems (ITS). This is achieved by allowing nodes within certain ranges to connect with each other in order to exchange information. Since accident happens in split seconds, to avoid communication inefficiency, there is need for this information to get to the intended vehicle on time. To solve this problem, this work models each vehicle in a chain of others and how it responds to the traffic around it using Microscopic (also known as car-following) method for modeling traffic flow; driver- to-driver and driver-to-road interactions within a traffic stream and the interaction between a driver and another driver on road were considered. The essence of this modeling is to determine the minimum response time required for a vehicle in VANET to respond and communicate situations on the road. A simulated scenario was carried out for two vehicles, a leading vehicle and following vehicle. The result shows that with an average of 32 meters apart with average difference in velocity of   1.23m/s, a minimum of 0.9secs is required for efficient situation response communication to ensue between them.</p>


2017 ◽  
Vol 6 (1) ◽  
pp. 6-14 ◽  
Author(s):  
S.B. Efremov

In order to increase safety while driving and to minimize the burden on the driver, the information should be transmitted to him/her in such a way that the driver needn’t spent time on its recognition and comprehension. Projecting and visualization of information on the windshield can help simplify the dialogue between a car and a driver ("operator") and expand the influence of intellectual transport system using projection information about traffic jams in the field of perception of the driver, so that it does not interfere with the driver on the road. This article discusses the possible advantages and disadvantages of using "hints", created within the framework of the "augmented reality" to increase driving safety by treating them as a new form of communication between a car and a driver. So, it seems to be a new approach to the utilization of the system, based on performances in the field of augmented reality to recognize road signs, which impose virtual objects on the field of perception in all types of traffic situations including the uncomfortable weather conditions. This approach can be used to increase accuracy of intellectual transport system with the augmented reality to support the driver in various driving situations, increasing comfort and reducing the number of accidents


2020 ◽  
Vol 17 (4) ◽  
pp. 1304
Author(s):  
Muhammad Akram Akram Mujahid ◽  
Kamalrulnizam Bin Abu Bakar ◽  
Tasneem S.J Darwish ◽  
Fatima Zuhra ◽  
Muhammad Aamer Ejaz ◽  
...  

Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and pollute the environment. Emergency messages notify the drivers about road accidents and congestions, and how to avoid the dangerous zones. This paper classifies the emergency messages schemes into three categories based on relay node, clustering and infrastructure. The capabilities and limitations of the emergency messages schemes are investigated in terms of dissemination process, message forward techniques, road awareness and performance metrics. Moreover, it highlights VANET-based challenges and open research problems to provide the solutions for a safer, more efficient and sustainable future ITS.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5049
Author(s):  
Alexey Kashevnik ◽  
Andrew Ponomarev ◽  
Nikolay Shilov ◽  
Andrey Chechulin

This paper presents an analysis of modern research related to potential threats in a vehicle cabin, which is based on situation monitoring during vehicle control and the interaction of the driver with intelligent transportation systems (ITS). In the modern world, such systems enable the detection of potentially dangerous situations on the road, reducing accident probability. However, at the same time, such systems increase vulnerabilities in vehicles and can be sources of different threats. In this paper, we consider the primary information flows between the driver, vehicle, and infrastructure in modern ITS, and identify possible threats related to these entities. We define threat classes related to vehicle control and discuss which of them can be detected by smartphone sensors. We present a case study that supports our findings and shows the main use cases for threat identification using smartphone sensors: Drowsiness, distraction, unfastened belt, eating, drinking, and smartphone use.


2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Ailing Huang ◽  
Wei Guan ◽  
Yimei Chang ◽  
Zhen Yang

Although more attention has been attracted to benefit evaluation of Intelligent Transportation Systems (ITS) deployment, how ITS impact the traffic system and make great effects is little considered. As a subsystem of ITS, in this paper, Intelligent Transportation Management System (ITMS) is studied with its impact mechanism on the road traffic system. Firstly, the correlative factors between ITMS and the road traffic system are presented and 3 positive feedback chains are defined. Secondly, we introduce the theory of Fundamental Diagram (FD) and traffic system entropy to demonstrate the correlative relationship between ITMS and feedback chains. The analyzed results show that ITMS, as a negative feedback factor, has damping functions on the coupling relationship of all 3 positive feedback chains. It indicates that with its deployment in Beijing, ITMS has impacted the improvement of efficiency and safety for the road traffic system. Finally, related benefits brought by ITMS are presented corresponding to the correlative factors, and effect standards are identified for evaluating ITMS comprehensive benefits.


2019 ◽  
Vol 52 (7-8) ◽  
pp. 985-994
Author(s):  
Mustafa Teke ◽  
Fecir Duran

Intelligent transportation systems are advanced applications that inform vehicle drivers about road conditions. The main purpose of the intelligent transportation systems is to reduce either tangible or intangible loss for the drivers by ensuring the safety of passengers and vehicles. In this study, a system is designed and implemented using wireless sensor networks to inform vehicle drivers about the condition of the road surface. Icing has been chosen as the primary focus of the study since it is considered to be a big threat to road and driver’s safety. The temperature at 10 cm depth of the road, air temperature, relative humidity, air pressure and conductivity values are used as the input data for the prediction of icing on the road surface. The data were previously collected on Raspberry Pi which is a single-board computer and the data were read and processed instantly via k-nearest neighbor algorithm. Using these collected data, the road surface condition is classified as icy, dry, wet or salty-wet. The analyzed results for the road surface condition are presented to the drivers via a mobile application in real time. The drivers are alerted visually and audibly as they approach the coordinates on the road where risky conditions are present.


2021 ◽  
Vol 2 (3) ◽  
pp. 837-843
Author(s):  
Rachmat Suryadithia ◽  
Muhammad Faisal ◽  
Arman Syah Putra ◽  
Nurul Aisyah

The background of this research is to want to know the technological developments that exist in the intelligent transportation system, by knowing the developments it will be able to add to the repertoire of research and deepen similar research. The method used in this research is to conduct a literature review, by reading many journals that can be the basis for this research, reading will be able to develop the problems that have been researched. The problem raised in this research is wanting to know technological developments in the smart transportation system and making one example of a system that will be developed in smart transportation. This research will produce technological technologies that can be developed in smart transportation systems, and provide examples of research that can be developed on smart transportation systems.


Author(s):  
Kyu-Ok Kim ◽  
L. R. Rilett

In recent years, microsimulation has become increasingly important in transportation system modeling. A potential issue is whether these models adequately represent reality and whether enough data exist with which to calibrate these models. There has been rapid deployment of intelligent transportation system (ITS) technologies in most urban areas of North America in the last 10 years. While ITSs are developed primarily for real-time traffic operations, the data are typically archived and available for traffic microsimulation calibration. A methodology, based on the sequential simplex algorithm, that uses ITS data to calibrate microsimulation models is presented. The test bed is a 23-km section of Interstate 10 in Houston, Texas. Two microsimulation models, CORSIM and TRANSIMS, were calibrated for two different demand matrices and three periods (morning peak, evening peak, and off-peak). It was found for the morning peak that the simplex algorithm had better results then either the default values or a simple, manual calibration. As the level of congestion decreased, the effectiveness of the simplex approach also decreased, as compared with standard techniques.


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