Study of Driver Assistant Services using Ubiquitous Smartphone

This work leverages the wide diffusion of smartphones and existing cellular network to implement a centralized, real-time, Advanced Driver Assistance System. Each vehicle is equipped with a smartphone that periodically computes and sends vehicle's global position and speed through GPRS or UMTS network. The centralized server snaps all running vehicles into digital maps and implements safety algorithms to detect potential dangerous situations. The identification of a prospective crash generates a warning on the smartphone to alert the driver. This paper presents the general hardware and software architecture and the implementation of two use cases. An evaluation of the critical aspects of the system is also provided.

International Journal of Engineering and Technology

Using mobile phones during traffic progress is one of the main causes traffic accidents because drivers do not focus on driving, they try to listen phone calls or to text some messages... Most of research work has focused to car driving. However, using motorbike is very popular in some developing countries such as Vietnam, India, etc. Up to now, there are just a few works, which focus to motorbike driving with obvious limitations. Thus, in this research, we proposed a complete solution for bikers who own a smartphone. Our work exploits the information from built-in sensors in Android smartphone. A complete scheme for motorbike driving is proposed. In this scheme, the user state is detected by improving the current Google activity recognition API. If the state is "On vehicle", the phone automatically switches to silent mode and send to the caller an SMS. Our work provides a mechanism to receive the calls from VIP contacts and urgent calls. The phone would switch back to the normal mode if the state is not "On vehicle". Furthermore, it sends the accident location to the relatives when an accident occurs to save their lives automatically. The application was tested carefully and it can be used to protect the lives of motorbike drivers. Keyword-3-DOF Accelerometers, GPS, Accidental Location, Motor Safe I. INTRODUCTION According to the Traffic Police Department, Vietnam has more than 45 million motorbikes in over 90 million people until 2016 with 21.568 traffic accidents occurred in this year and the number of people died and injured were 8.680 and 19.280 respectively (see Fig.1). One of the main causes in traffic accidents is using the phone while controlling vehicles (see Fig. 2). They usually use the phone for listening to music, calling, messaging or playing some app games like Pokemon Go...[3][4]. Hence, they lose focus on controlling vehicles because of being limited visibility and being distracted from other drivers... Then they cannot handle all situations. Furthermore, the time between the occurrence of accidents and the notification to relatives and medical services is too slow; it results in increasing the number of fatal cases [5]. In order to reduce the number of traffic accidents and people died as well, there are several published methods used to protect drivers during the controlling vehicles process in recent years by researchers and companies. Nevertheless, most of the reported publications focus on developing the supported systems for cars such as: Accelerometer based Transportation System [6], Accident Avoidance and Driver Assist Technologies [7], PRE-SAFE® [8], etc. The systems in [11][12][13] used smartphones to detect the accident in combination with automatic sending alert notification to relatives and hospital services, but these applications do not have function to switch the phone to silent mode when receiving incoming calls from unimportant or unknown people while driving. Therefore, drivers are easily distracted while driving.

Pervasive and Mobile Computing, 2017

Road surface monitoring is an important problem in providing smooth road infrastructure to the commuters. The key to road condition monitoring is to detect road potholes and bumps, which affect the driving comfort and transport safety. This paper presents a smartphone based sensing and crowdsourcing technique to detect the road surface conditions. The in-built sensors of the smartphone like accelerometer and GPS 1 have been used to observe the road conditions. It has been observed that several techniques in the past have been proposed using these sensors. Such techniques either use fixed threshold values which are road or vehicle condition dependent or use machine learning based classified training which requires intensive and continuous training. The motivation of our work is to improve classification accuracy of detecting road surface conditions using DTW 2 technique which has not been researched on data based on motion sensors. The main features of DTW is its ability to automatically cope with time deformations and different speeds associated with time data, its simplicity is to be used in resource constrained devices such as smartphones and also the simplicity in its training procedure which is must as fast as compared to techniques such as SVM 3 , HMM 4 and ANN 5. Our technique shows better accuracy and efficiency with detection rate of 88.66% and 88.89% for potholes and bumps respectively, when compared with the existing techniques With the

Current technologies have been evolved day by day for the betterment of the human life style, because of these technologies necessary comfort and safeties are enjoyed by the people. Due to increased vehicle density, infringement of rules and rashness many accidents may occur. The main objective of this paper is to prevent the vehicle accident while crossing the pavement edge line of the road and using mobile crowd sensing system, distribute the alert message to the drivers travelling on the congested roads. Bat algorithm is used to predict the edge line and calculating the distance between the vehicle and the edge line. The proposed edge line detection algorithm is helpful for preventing the road accident caused by the car drivers while crossing pavement the edge line of the road. When the driver crosses the edge line of the road, the speed of the vehicle is to be controlled by ESC (Electronic Stability Control) program inside the vehicle. By using mobile crowed sensing architecture, collect alerts from people driving on the congested roads and then distributes the alerts to other drivers. The drivers from other roads can be benefits from real time traffic information. In this proposed edge line detection method an additional feature such as sending SMS to the registered mobile number along with GPS location of the car and the information about the route, traffic signal and distance to reach the destiny is also given based on the user's request. 1. Introduction The transportation industry is highly connected with maintenance costs, disasters, fatal accidents, injuries and loss of life. More number of people across the world is losing their lives in car accidents and road disasters every year. This problem can be addressed by using the Internet of Things and preventing the accident by predicting the edge path line by using bat's algorithm. With the right implementation of IoT technology, the fatal accident may be prevented as well as help the blind people while using the edge line. The proposed method makes predictions and reaches destination that will make our roads safer. In each country, there are rules and regulations that impose safe driving. But while rules are rather reactive in nature and force drivers to drive safely to avoid punishment, IoT can play a more proactive role in helping drivers adopt safe habits. " Road sensors are going to be one of the most crucial developments that will take place in the world of transportation with the introduction of the Internet of Things technology " [1] The term ―things in the IOT refers to a wide variety of devices such as heart monitoring implants, biochip transponders on farm animals, electric clams in coastal waters, automobiles with built-in sensors, or field operation devices that assist fire-fighters in search and rescue. Current market examples include thermostat systems and washer/dryers that utilize Wi-Fi for remote monitoring. [2] To solve the problem of death caused by accident which occur because of the delay in help provided by rescue, can be solved by a new system of accident detection technique which finds out the occurrence of accident through various sensors and intimate the occurrence of accident to the nearest rescue teams or patrol services by the use of GSM and GPS system. Hence the proposed method has come up with the system to reduce the risk and effect of accidents. The remainder of this paper is structured as follows. In Section 2, we introduce basic concepts related to pavement line, global positioning system, Bat Algorithm. In Section 3, we introduce the proposed Edge line detection using bat algorithm. Section 4 is dedicated to results and discussion. Finally, we present the conclusion of our work in Section 5. 2. Related work: 2.1 Pavement Edge Lines Pavement edge lines are used to indicate the edges of carriageways which have no curbs. They serve as a visual guidance for the drivers, indicating to them the limits up to which the driver can safely venture. They especially are useful during adverse weather and poor visibility where the paved shoulder is of a lesser structural strength than the main pavement, the edge lines are used to promote travel on the main pavement itself. Edge lines are in the form of a single continuous line placed about 150 mm from the edge. 2.2 Global Positioning System (GPS) is a popular technology which was developed by American Department of Defense (DoD) for military use. Later on it was available for civilian use. It is utilized for wide range of applications such as

International Journal of Advance Engineering and Research Development

The project aims to produce a Road Condition Detection Device (RCDD).The main components of the project are the arduino module and the Android smartphone. The arduino will be used as a sensing module and the smartphone will be user interface. The road conditions will be evaluated in real time using the arduino and the data collected by it will be sent to the android smartphone using the bluetooth module. The collected data will be used by the android application to and the relative condition of the road and the abnormal road condition will be marked on the Google Maps using GPS of the smartphone. So, the road condition will be known to the driver and they can change their driving behaviors for improving the safety of the people, comfort and efficiency. The amount of accidents which are caused by the bad road condition will be lowered

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2020

Technological evolution impacts several industries, including automotive. The combination of software with advancements in sensory capabilities results in new Advanced Driver Assistance System (ADAS). The pervasiveness of smartphones and their sensory capabilities makes them an solid platform for the development of ADAS. Our work is motivated by concerns on the reliability of data acquired from such devices for developing ADAS. We performed a number of controlled experiments to understand which factors impact the collection of accelerometer data with smartphones. We conclude that the quality of data acquired is not significantly affected by using different smartphones, car mounts, rates of sampling, or vehicles for the purpose of developing ADAS. Our results indicate that smartphone sensors can be used to develop ADAS.

Procedia - Social and Behavioral Sciences, 2014

The monitoring of road surface anomalies, such as potholes, speed bumps etc., has a great importance in order to ensure safety and comfort for all road users, from pedestrian to drivers. The constant mapping of road real conditions also allows adequate infrastructure's maintenance and management operations, together with a consistent allocation of resources. For this reason, informing road users on infrastructure quality and getting information from the same users have become the new frontier of mobile devices applications for driving assistance and navigation (such as a specific social network for safety road). In the light of the above and thanks to the results obtained from previous studies, this paper focuses on the development of a useful automated sensing system for the monitoring of road surface quality. The system is based on the use of a simple application for smartphones that employs two main sensors piggybacked on mobile devices: a GPS receiver for vehicle's localization and a three axis accelerometer to collect acceleration data due to vehicles motion on road anomalies. The information collected during the trip is transferred in real time (1Hz frequency) to a central server where data are processed using automated algorithms for signal analysis. In particular, high-energy events are identified by monitoring and measuring the vertical acceleration impulse. A statistical analysis of experimental data has led to the detection of specific thresholds to which the impulse values are continuously compared. Several experimental tests were carried out for corroborating the approach and to validate the system accuracy. Results exhibited high performance of the system architecture. This study is part of the extensive research project M2M (Mobile to Mobility, PON co-financed by European Regional Development Fund, FESR), that is based on the use of mobile sensor computing systems forgiving realtime information to road users in order to make the transportation system more safe and comfortable.

2020

Smartphones are potentially useful to be adopted as a cost-effective and easy to implement tool for the measurement of road surface roughness condition, which is very essential for road monitoring and maintenance planning. In this study, an experiment has been carried out to collect data from accelerometers and gyroscopes on smartphones. The collected data is processed in the frequency domain to calculate magnitudes of the vibration. Road roughness condition that is modelled as a linear function of the vibration magnitudes, taking into account of both data from accelerometer and gyroscope as well as the average speed, achieves better estimation than the model that takes into account the magnitude from the accelerometer and the average speed alone. The finding is potentially significant for the development of a more accurate model and a better smartphone app to estimate road roughness condition from smartphone sensors. Keywords—(As per ACM Keywords) Road monitoring, Accelerometer, Gy...

2014

Since the vehicle users are increasing day by day it has become necessary for the driver to get assistance on road on highway while travelling. For safety purpose the user should be aware of the road conditions. With advanced technology mobile phones are well equipped with three axis accelerometer and GPS system. Android operating system of smart phone having three axis accelerometer and the GPS tracking system that can be used to analyze the road conditions for driver’s awareness and maximize safety. In this paper the emphasis is to provide assistance to the driver while travelling. The data available can educate the driver as how safely and efficiently he can drive the vehicle. In addition to this a device similar to wireless black box can be used in a same vehicle to monitor if the accidents occur. The device consists of collision sensor, microcontroller unit, GPS and GSM module. This wireless device will send a short message to the relatives informing that the event of accident ...

Monitoring the road condition has gain significant importance in last few years. There are various reasons for extending research in this field: first, it will ensure safety and comfort to various road users; second, smooth roads will lead to less vehicle damage and government investment; third, the availability of low cost sensors in Smartphones; fourth, the rapid increase in the rate of Smartphone users. Thus, it is necessary to develop systems which are able to detect road conditions using sensors present in Smartphone. Several methods have been proposed towards addressing this problem. This paper reviews the various road conditions detection systems appeared in the literature. This paper also provides the areas which can be further modified to develop a more robust system.