Iot Sensors In Automotive Applications For Driver Assistance And Safety – An enhanced LoRaWAN security protocol for privacy protection in IoT with a case study of smart factory powered parking

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Iot Sensors In Automotive Applications For Driver Assistance And Safety

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Automotive Imaging Sensors

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Five Connectivity Requirements For V2x Autonomous Vehicle Technology

Juan Guerrero-Ibáñez Juan Guerrero-Ibáñez Scilit Preprints.org Google Scholar 1, Sherali Zeadally Sherali Zeadally Scilit Preprints.org Google Scholar 2, Juan Contreras-Castillo Juan Contreras-Castillo Scilit.

Received: 22 February 2018 / Revised: 12 April 2018 / Accepted: 12 April 2018 / Published: 16 April 2018

(This article belongs to the special issue on Internet Architecture, Systems and Applications for Smart Cities)

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Modern society faces serious challenges not only in transportation systems, but also in traffic congestion, safety, and pollution. Information communication technologies have gained more attention and importance in modern transportation systems. Automakers are developing in-vehicle sensors and applications in a variety of areas, including applications, safety, traffic management, and data. Government agencies are implementing infrastructure such as roadside cameras and sensors to collect information about the environment and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve more responsive and smarter transportation systems. We discuss how sensor technology can be integrated with transport infrastructure to achieve a sustainable intelligent transport system (ITS), and how safety, traffic control and information applications can benefit from multiple sensors deployed in different parts of the ITS. Finally, we discuss some of the challenges that need to be addressed to ensure a fully functional and collaborative ITS environment.

Transportation systems have become the mainstay of economic development in all countries. However, many cities around the world face uncontrolled traffic growth, causing serious problems such as delays, traffic congestion, rising fuel prices and rising carbon emissions.

Waste, accidents, emergencies and deterioration of living standards in modern society. According to a report by the Texas Transportation Institute, commuters spend about 42 hours a year in traffic and drivers use 3 billion gallons of fuel each year, at a total cost of $160 billion, or $960,000. for passenger [1]. As reported by the United Nations Population Fund [2] and the Bureau of Population Information [3], such problems will become more difficult in the future due to population growth and increased migration to urban areas in many countries around the world. Therefore, there is a strong need to improve the safety and efficiency of transport.

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Advances in information and communication technologies (ICT) in areas such as hardware, software, and communications have created new opportunities for developing sustainable and intelligent transportation systems. Integrating ICT with transport infrastructure will enable a better and safer travel experience and a move to Intelligent Transport Systems (ITS) focused on four key principles: sustainability, integration, safety and responsibility. These principles will play a key role in achieving the main goals of smart transport systems, which include accessibility and mobility, environmental sustainability and economic development [4].

The success of ITS largely depends on the platform used to capture, collect and process accurate data from the environment. Sensor platforms fall into two categories. The first category is an in-vehicle sensor platform that collects information about the vehicle’s condition. A second category of urban sensing platforms is used to collect information about road conditions. Sensor technology is a critical component used to collect data during vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. This information is then fed into traffic management systems for further processing, analysis and subsequent decisions/actions. Smart and intelligent ITS promises to solve problems such as high fuel prices and high CO levels

The main contributions of this work are threefold. First, we describe and discuss how sensor technology can be integrated with transportation infrastructure to achieve a sustainable intelligent transportation system that addresses issues such as high-level CO.

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Increasing emissions, high congestion and road safety. We explain where sensors can be deployed in transportation infrastructure, the types of data they collect, and how this data can be used to improve transportation. Second, we discuss how user applications (driving assistance, passenger entertainment, collision warning, etc.) and ITS applications (traffic control, traffic conditions, etc.) can take advantage of sensor technologies embedded in ITS components. We also present a taxonomy of applications that make direct use of collected sensor data to improve transportation systems by making them more efficient, cost-effective, and efficient for end-users and transportation system management organizations. Finally, we discuss some of the challenges that sensor technologies will face in the future to achieve a fully functional, scalable, and collaborative ITS environment.

In the past decade, sensor technology has become ubiquitous and has attracted a lot of attention. Sensors have been deployed in many fields, including healthcare [7, 8], agriculture [9, 10], forestry [11, 12], transportation, and marine [13, 14]. In transportation, sensor technology supports the design and development of many applications for traffic control, safety, and entertainment. In recent years, sensors and actuators such as tire pressure sensors and rear vision systems have become mandatory in vehicle manufacturing and the implementation of intelligent transportation systems (due to federal regulation in the United States [15]). Providing services to improve driver and passenger satisfaction, improve road safety and reduce traffic congestion. Manufacturers want other sensors to monitor vehicle performance and condition and provide greater efficiency and assistance to drivers. Currently, the average number of sensors in a vehicle is about 60–100, but as vehicles become “smarter,” the number of sensors may reach 200 sensors per vehicle [16].

In [17], the author presents a classification of three sensors based on their location in the vehicle: powertrain, chassis, and body. Another work classifies in-vehicle sensors based on the type of application the sensor is intended to support and defines four categories: safety sensors, diagnostic sensors, convenience sensors, and environmental monitoring sensors [18]. We extend the classification proposed by [18] to include two additional sensors, driver monitoring and vehicle monitoring sensors, as shown in Table 1.

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In ITS, a variety of sensors are identified to develop applications that help solve problems such as: (1) traffic congestion and parking problems, (2) long travel times, and (3) high levels of CO.

Emissions, (4) increasing the number of road accidents, among others, are important for improving vehicle performance and driving experience. Figure 1 shows the most common sensors used in vehicles today.

Tire pressure monitoring is a program required by the US National Highway Administration to alert drivers with acoustic, light, or vibration alarms when tire pressure is low [19].

Automotive Sensors And Driver Assistance Systems

Parking assist and reverse warning systems use proximity, ultrasonic and electromagnetic sensors. Proximity sensors can detect when a vehicle is approaching something. Ultrasonic sensors use a form of sonar to determine how far the vehicle is from an object, alerting the driver when the vehicle is closer than a certain threshold. Electromagnetic sensors alert the driver when an object enters the electromagnetic field created around the front and rear bumpers. Proximity sensors were used to create a system based on a rectangular capacitive proximity sensor array to detect the degree of headspace to meet the Insurance Institute for Highway Safety (IIHS) guidelines [20]. However, these types of sensors are often affected by temperature and humidity, reducing their accuracy.

Radio Detection and Ranging (RADAR) and laser sensors continuously scan the road for front, side, and rear collisions and allow safety applications to adjust the throttle and activate the brakes to prevent accidents.

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