scholarly journals IoT Bus Navigation System with Optimized Routing using Machine Learning

2021 ◽  
Vol 13 (3) ◽  
pp. 1-15
Author(s):  
Samer I. Mohamed ◽  
◽  
Muhamed Abdelhadi
Keyword(s):  
Machine Learning ◽  
Public Transportation ◽  
Operating Cost ◽  
Machine Learning Algorithms ◽  
Layered System ◽  
The Road ◽  
Chip Technology ◽  
On The Road ◽  
On Chip ◽  
Maintenance Schedules

As the population in Egypt is ever expanding, it is reflected in the increase of the number of vehicles on the road. Public transportation is the solution and the number of available buses can cover a significant amount of the population demand. However, the outdated state of the transportation infrastructure, the static nature of the lines and indistinct schedules create a confounding and unappealing user experience which prompts the users to stray to cars for their needs. So, an Intelligent Urban Transportation System (IUTS) is a must. IUTS is a multi-layered system which provides the solution for most of these problems. It operates on different layers starting from a real time vehicle tracking for transparent and efficient management of assets, cash-less ticketing done through RFID cards, vehicle health and diagnostic data for creation of automated maintenance schedules and a friendly interactive driver interface. In this paper an approach based on combining all these technologies is discussed where the hardware component is implemented based on System-on-Chip technology with custom hardware to interface with the vehicle. The data collected from the on-board unit is sent to the cloud, and with the help of machine learning algorithms the dynamic responsiveness of the system is guaranteed. The proposed system outperforms other existing ones through the dynamic and optimized routing feature for the bus navigation to optimize the operating cost but still satisfy the passengers’demand.

scholarly journals Machine Learning to Classify Driving Events Using Mobile Phone Sensors Data

2021 ◽  
Vol 15 (02) ◽  
pp. 124
Author(s):  
Yazan Alqudah ◽  
Belal Sababha ◽  
Esam Qaralleh ◽  
Tarek Yousseff
Keyword(s):  
Machine Learning ◽  
Road Safety ◽  
Autonomous Vehicles ◽  
Machine Learning Algorithms ◽  
Motion Sensors ◽  
The Road ◽  
Crowd Sensing ◽  
Innovative Solution ◽  
On The Road ◽  
Self Driving Cars

With the ever-increasing vehicle population and introduction of autonomous and self-driving cars, innovative research is needed to ensure safety and reliability on the road. This work introduces an innovative solution that aims at understanding vehicle behavior based on sensors data. The behavior is classified according to driving events. Understanding driving events can play a significant role in road safety and estimating the expense and risks of driving and consuming a vehicle. Rather than relying on the distance and time driven, driving events can provide a more accurate measure of vehicle driving consumption.  This measure will become more valuable as more autonomous vehicles and more ride sharing applications are introduced to roads around the world. Estimating driving events can also help better design the road infrastructure to reduce energy consumption.  By sharing data from official vehicles and volunteers, crowd sensing can be used to better understand congestion and road safety. This work studies driving events and proposes using machine learning to classify these events into different categories. The acquired data is collected using embedded mobile device motion sensors and are used to train machine learning algorithms to classify the events.

scholarly journals Human-Computer Interaction with Special Emphasis on Converting Brain Signals to Speech

2020 ◽  
Vol 9 (6) ◽  
pp. 523-529
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Science Fiction ◽  
Linear Models ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
The Road ◽  
Brain Signals ◽  
On The Road ◽  
The Brain

Huge hurdle neuro engineers face on the road to effective brain-computer interfaces is attempting to translate the big selection of signals made by our brain into words pictures which may be simply communicable. The science-fiction plan of having the ability to manage devices or communicate with others simply by thinking is slowly but surely, obtaining nearer to reality. Translating brainwaves into words has been another large challenge for researchers, but again with the help of machine learning algorithms, superb advances are seen in recent years. The exploitation of deep learning and acceptable machine learning algorithms, the management signals from the brain will regenerate to some actions or some speech or text. For this, a neural network is created for the brain and conjointly a mapping is completed to catch all the brain signals in which neural network will be additionally used for changing these signals into actions. From the past literature, it is being concluded that the Deep Neural Networks are one of the main algorithms that are being placed into use for this research. This review article majorly focuses on studying the behavioral patterns generated by the brain signals and how they can be converted into actions effectively so that people suffering from semi or full paralysis can use this technology to live a normal life if not completely but to a certain extent. Also, it focuses on analyzing and drawing a comparison between linear and non-linear models and to conclude the best-suited model for the same currently available to the researchers.

CREATING WALKING LED TRANSIT STATIONS FOR WOMEN IN MALAYSIA

2020 ◽  
Vol 7 (1) ◽  
pp. 99
Author(s):  
Yong Adilah Shamsul Harumain ◽  
Nur Farhana Azmi ◽  
Suhaini Yusoff
Keyword(s):  
Quality Of Life ◽  
Developing Countries ◽  
Public Transportation ◽  
Carbon Emission ◽  
The Other ◽  
Walking Distance ◽  
The Road ◽  
On The Road ◽  
Female User

Transit stations are generally well known as nodes of spaces where percentage of people walking are relatively high. The issue is do more planning is actually given to create walkability. Creating walking led transit stations involves planning of walking distance, providing facilities like pathways, toilets, seating and lighting. On the other hand, creating walking led transit station for women uncover a new epitome. Walking becomes one of the most important forms of mobility for women in developing countries nowadays. Encouraging women to use public transportation is not just about another effort to promote the use of public transportation but also another great endeavour to reduce numbers of traffic on the road. This also means, creating an effort to control accidents rate, reducing carbon emission, improving health and eventually, developing the quality of life. Hence, in this paper, we sought first to find out the factors that motivate women to walk at transit stations in Malaysia. A questionnaire survey with 562 female user of Light Railway Transit (LRT) was conducted at LRT stations along Kelana Jaya Line. Both built and non-built environment characteristics, particularly distance, safety and facilities were found as factors that are consistently associated with women walkability. With these findings, the paper highlights the criteria  which are needed to create and make betterment of transit stations not just for women but also for walkability in general.

Real-Time V2V Communication With a Machine Learning-Based System for Detecting Drowsiness of Drivers

2021 ◽  
Vol 13 (4) ◽  
pp. 35-50
Author(s):  
Ahmed Y. Awad ◽  
Seshadri Mohan
Keyword(s):  
Machine Learning ◽  
Traffic Accidents ◽  
Ad Hoc ◽  
Economic Losses ◽  
Drowsy Driving ◽  
The Road ◽  
V2v Communication ◽  
Physical Injuries ◽  
On The Road ◽  
The U.S

This article applies machine learning to detect whether a driver is drowsy and alert the driver. The drowsiness of a driver can lead to accidents resulting in severe physical injuries, including deaths, and significant economic losses. Driver fatigue resulting from sleep deprivation causes major accidents on today's roads. In 2010, nearly 24 million vehicles were involved in traffic accidents in the U.S., which resulted in more than 33,000 deaths and over 3.9 million injuries, according to the U.S. NHTSA. A significant percentage of traffic accidents can be attributed to drowsy driving. It is therefore imperative that an efficient technique is designed and implemented to detect drowsiness as soon as the driver feels drowsy and to alert and wake up the driver and thereby preventing accidents. The authors apply machine learning to detect eye closures along with yawning of a driver to optimize the system. This paper also implements DSRC to connect vehicles and create an ad hoc vehicular network on the road. When the system detects that a driver is drowsy, drivers of other nearby vehicles are alerted.

scholarly journals Traffic Density Classification Using Twitter Data and GPS Based On Android Application

2020 ◽  
Vol 14 (2) ◽  
pp. 113
Author(s):  
Mohammad Afrizal ◽  
Idham Ananta Timur
Keyword(s):  
Public Transportation ◽  
Traffic Density ◽  
The Public ◽  
The Road ◽  
Twitter Data ◽  
Average Accuracy ◽  
Android Applications ◽  
On The Road ◽  
The City ◽  
Special Region

Increasing the number of vehicles in Special Region of Yogyakarta caused by congestion occurred at various traffic points in Special Region of Yogyakarta. The solution to reducing congestion is by increasing the use of public transportation within the city, but it still not in demand by the public. Optimizing daily activities, community always tries to avoid the traffic density on the road to be bypassed.Some research on social media has been used to detect traffic density anomalies. However, the system still cannot provide traffic density information on roads that will be passed by the user because it is just a mapping. Based on this problem, this study aims to classify the traffic density on the road that will be passed by users in the Special Region of Yogyakarta into the category of high traffic and low traffic by utilizing Twitter and GPS data.The results show that Android Applications are able to classify traffic density on the road to be traversed using Geonames.org API. Using the naïve bayes classification algorithm, the system can classify traffic density on 14 streets with an average accuracy of 77.5%, 90% precision, 79.1% recall, and 82.8% f-score.

scholarly journals Analytical Models for Traffic Congestion and Accident Analysis

2021 ◽  
Author(s):  
Hongrui Liu ◽  
Rahul Ramachandra Shetty
Keyword(s):  
Traffic Congestion ◽  
Regression Tree ◽  
Machine Learning Algorithms ◽  
Analytical Models ◽  
Gradient Boosting ◽  
Decision Tree Classifier ◽  
The Road ◽  
Tree Classifier ◽  
Extreme Gradient Boosting ◽  
On The Road

In the US, over 38,000 people die in road crashes each year, and 2.35 million are injured or disabled, according to the statistics report from the Association for Safe International Road Travel (ASIRT) in 2020. In addition, traffic congestion keeping Americans stuck on the road wastes millions of hours and billions of dollars each year. Using statistical techniques and machine learning algorithms, this research developed accurate predictive models for traffic congestion and road accidents to increase understanding of the complex causes of these challenging issues. The research used US Accidents data consisting of 49 variables describing 4.2 million accident records from February 2016 to December 2020, as well as logistic regression, tree-based techniques such as Decision Tree Classifier and Random Forest Classifier (RF), and Extreme Gradient boosting (XG-boost) to process and train the models. These models will assist people in making smart real-time transportation decisions to improve mobility and reduce accidents.

scholarly journals Application of the Principle of Good Faith in Consumer Financing Agreements

2019 ◽  
Vol 8 (4) ◽  
pp. 4170-4172
Keyword(s):  
Public Transportation ◽  
Secondary Data ◽  
Good Faith ◽  
Philosophical Study ◽  
The Road ◽  
Transportation Equipment ◽  
Diverse Community ◽  
On The Road ◽  
Motorized Vehicles

Increasingly diverse community mobility now results in an increase in the need for transportation equipment, both in terms of quantity and quality, however, on the other hand the available public transportation facilities are far from what is expected. This encourages to be encouraged to have a private facility. Today the development of motorized vehicle use is increasing rapidly. This is because motorized vehicles have advantages compared to public transportation, for example in terms of comfort and safety when on the road. The increase in transportation needs also boosted the growth of Consumer Financing Institutions perceived by consumers as a simpler procedure compared to bank financing institutions. The agreement signed between consumers and the Consumer Financing Institution is a standard agreement, in which consumers have no right to determine the contents of the agreement. This leads to the frequent occurrence of defaults on the part of consumers, because consumers do not understand the contents of the agreement properly. Good faith is an agreement principle that can control the occurrence of agreements that tend to incriminate parties. This paper aims to reveal the role of the principle of good faith in the establishment and implementation of the Consumer Financing Agreement. The study method used is a normative and philosophical study method based on secondary data.

Application of Machine Learning Methods for Passenger Demand Prediction in Transfer Stations of Istanbul's Public Transportation System

2020 ◽  
pp. 196-216
Author(s):  
Hacer Yumurtaci Aydogmus ◽  
Yusuf Sait Turkan
Keyword(s):  
Machine Learning ◽  
Public Transportation ◽  
Demand Forecasting ◽  
Transportation System ◽  
Machine Learning Algorithms ◽  
Demand Prediction ◽  
Passenger Demand ◽  
World Demand ◽  
Public Transportation System ◽  
Transfer Stations

The rapid growth in the number of drivers and vehicles in the population and the need for easy transportation of people increases the importance of public transportation. Traffic becomes a growing problem in Istanbul which is Turkey's greatest urban settlement area. Decisions on investments and projections for the public transportation should be well planned by considering the total number of passengers and the variations in the demand on the different regions. The success of this planning is directly related to the accurate passenger demand forecasting. In this study, machine learning algorithms are tested in a real-world demand forecasting problem where hourly passenger demands collected from two transfer stations of a public transportation system. The machine learning techniques are run in the WEKA software and the performance of methods are compared by MAE and RMSE statistical measures. The results show that the bagging based decision tree methods and rules methods have the best performance.

INOVASI PELAYANAN PUBLIK PARK AND RIDE TERMINAL INTERMODA JOYOBOYO OLEH DINAS PERHUBUNGAN KOTA SURABAYA

Publika ◽  
2021 ◽  
pp. 77-92
Author(s):  
Dyah Eka Pratiwi ◽  
Trenda Aktiva Oktariyanda
Keyword(s):  
Public Service ◽  
Public Transportation ◽  
New Technologies ◽  
Public Awareness ◽  
Service Innovation ◽  
City Government ◽  
The Road ◽  
Park And Ride ◽  
The Government ◽  
On The Road

Pelayanan publik merupakan elemen yang sangat penting dalam penyelenggaraan pemerintahan. Inovasi yang dibuat oleh Pemkot Surabaya bersama Dishub Kota Surabaya berkaitan dengan sistem parkir online yang disebut Park and Ride TIJ. Inovasi pelayanan ini diciptakan untuk mengatasi permasalahan peningkatan kepemilikan kendaraan di Kota Surabaya yang membuat kebutuhan parkir meningkat, tetapi tidak diikuti dengan penambahan lahan parkir. Parkir di badan jalan mengakibatkan pergerakan lalu lintas terhambat sehingga terjadi kemacetan terutama di pusat keramaian tengah kota seperti Jalan Wonokromo, Jalan Darmo, dan Jalan Setail. Tujuan penelitian ini ialah untuk mendeskripsikan Inovasi Pelayanan Publik Park and Ride TIJ Oleh Dishub Kota Surabaya. Jenis penelitian yang digunakan adalah deskriptif dengan pendekatan kualitatif. Fokus penelitian dengan teori milik Yogi Suwarno (2008:19) yaitu aspek-aspek penting yang menunjukkan suatu organisasi telah melakukan inovasi meliputi Pengetahuan Baru, Cara Baru, Objek Baru, Teknologi Baru, dan Penemuan Baru. Teknik pengumpulan data melalui wawancara, observasi, dan dokumentasi. Teknik analisis data menggunakan reduksi data, penyajian data dan ditarik kesimpulan berdasarkan data yang menjawab rumusan masalah. Hasil dari penelitian ini adalah semua fasilitas yang ada di Park and Ride TIJ sudah sangat bagus dan memenuhi kebutuhan masyarakat. Hanya saja kurangnya kesadaran masyarakat untuk menggunakan fasilitas yang sudah disediakan oleh pemerintah. Setelah didirikan Park and ride pun masih ditemukan masalah yakni banyak masyarakat masih melakukan parkir liar terutama pengunjung Kebun Binatang Surabaya, serta sopir angkot yang “ngetem” di pinggir jalan sehingga menimbulkan kemacetan. Kemudian terkait dengan penerapan e-payment, karena banyak masyarakat masih menggunakan uang tunai untuk pembayaran parkir di Park nad Ride TIJ. Kata Kunci: Pelayanan Publik, Inovasi Pelayanan, Park and Ride   Public service is a very important element in government administration. The innovation made by the Surabaya City Government and the Surabaya City Transportation Agency is related to an online parking system called the TIJ Park and Ride. This service innovation was created to solve the problem of increasing vehicle ownership in the city of Surabaya which makes parking needs increase, but not followed by additional parking lots. Parking on the road causes traffic movement to be hampered, resulting in congestion, especially in the downtown area such as Jalan Wonokromo, Jalan Darmo, and Jalan Setail. The purpose of this study was to describe the TIJ Park and Ride Public Service Innovation by the Surabaya City Transportation Agency. This type of research is descriptive with a qualitative approach. The focus of research with Yogi Suwarno's (2008: 19) theory is important aspects that show an organization has made innovations including New Knowledge, New Methods, New Objects, New Technologies, and New Inventions. Data collection techniques through interviews, observation and documentation. Data analysis techniques used data reduction, data presentation and conclusions drawn based on data that answered the problem formulation. The result of this research is that all existing facilities at the TIJ Park and Ride are very good and meet the needs of the community. It's just a lack of public awareness to use the facilities provided by the government. After the establishment of Park and Ride, problems were still found, namely that many people were still parking illegal, especially visitors to the Surabaya Zoo, as well as public transportation drivers who "stuck" on the side of the road, causing congestion. Then related to the application of e-payments, because many people still use cash for parking payments at TIJ Park nad Ride. Keywords: Public Service, Service Innovation, Park and Ride

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