Driving information logger with in-vehicle communication for autonomous vehicle research

Sung, Kyungbok; Min, Kyoungwook; Choi, Jeongdan

doi:10.23919/icact.2018.8323732

Cited by 10 publications

(5 citation statements)

References 7 publications

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“…The ultrasonic sensor is also known as sonar that uses for echolocation to know the distance of the nearby objects. The device sensor has the ability to accomplish of finding the object distance placed at different location using the technique called as Doppler Effect (Sung et al , 2018). The round-trip time gives the distance at which the object has placed.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Autonomous vehicles are capable of determining the type of vehicles that are very near to it by comparing the information stored in the memory of the controller to identify exact vehicle size. They are also used to mitigate the inevitable human errors (Sung et al , 2018). Most of the self-driven vehicles (SDV) use ultrasonic sensors as the basis to adjudicate its surrounding field for safe driving and safe parking.…”

Section: Introductionmentioning

confidence: 99%

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Safety driven intelligent autonomous vehicle for smart cities using IoT

Kalappan

Venkatesan²,

Kumar³

2021

IJPCC

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Purpose Autonomous vehicles rely on IoT-based technologies to take numerous decisions in real-time situations. However, added information from the sensor readings will burden the system and cause the sensors to produce inaccurate readings. To overcome these issues, this paper aims to focus on communication between sensors and autonomous vehicles for better decision-making in real-time. The system has unique features to detect the upcoming and ongoing vehicles automatically without intervention of humans in the system. It also predicts the type of vehicle and intimates the driver. Design/methodology/approach The system is designed using the ATmega 328 P and ESP 8266 chip. Information from ultrasonic and infrared sensors are analyzed and updated in the cloud server. The user can access all these real-time data at any point of time. The stored information in cloud servers is used for integrating artificial intelligence into the system. Findings The real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation. Practical implications The system is implemented on embedded platform with IoT technology. The sensor information is updated to the cloud using the Blynk application for the user in real time. Originality/value The system is proposed for smart cities with IoT technology where the user and the system are aware of the surrounding environment. The system is mainly concerned with the accuracy of sensors and the distance between the vehicles in real-time environment.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Safety driven intelligent autonomous vehicle for smart cities using IoT

Kalappan

Venkatesan²,

Kumar³

2021

IJPCC

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“…A log is generated by a specific module at a particular time; it is in itself partial and low-level, especially in a complex and dynamic system. Thus, only an experienced engineer who comprehends the entire system could collect and aggregate the data into a meaningful event based on speculation [21]. Some salient scenarios imagined by the experienced can be tested, and they are so-called oracle tests.…”

Section: Problem Statementmentioning

confidence: 99%

A Formal and Quantifiable Log Analysis Framework for Test Driving of Autonomous Vehicles

Sung

Min

Choi

et al. 2020

Sensors

Self Cite

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We propose a log analysis framework for test driving of autonomous vehicles. The log of a vehicle is a fundamental source to detect and analyze events during driving. A set of dumped logs are, however, usually mixed and fragmented since they are generated concurrently by a number of modules such as sensors, actuators and programs. This makes it hard to analyze them to discover latent errors that could occur due to complex chain reactions among those modules. Our framework provides a logging architecture based on formal specifications, which hierarchically organizes them to find out a priori relationships between them. Then, algorithmic or implementation errors can be detected by examining a posteriori relationships. However, a test in a situation of certain parameters, so called an oracle test, does not necessarily trigger latent violations of the relationships. In our framework, this is remedied by adopting metamorphic testing to quantitatively verify the formal specification. As a working proof, we define three metamorphic relations critical for testing autonomous vehicles and verify them in a quantitative manner based on our logging system.

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“…Research and development have been prompted to support safe driving and the independent driving system. The electric car's invention, integrated with the selfdriving system, is intended to solve three transportation problems simultaneously; accidents, traffic jams, and carbon dioxide emission (Sung et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Autonomous Vehicle Radiation Based on Traffic Flow Analysis

Kordelia

Armizoprades

2022

MAROSTEK: Jurnal Teknik, Komputer, Agroteknologi Dan Sains

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The transportation sector is heading to a new futuristic era, the fully-autonomous vehicles. Radar, lidar, and Sonar are considered critical aspects of self-driving technology. However, these sensors come with inherent danger. Their exposure has a hazardous impact on humans and living things. A forecast made using the level of service classification shows that there will be excessive radiation exposure when these cars dominate the traffic. This prediction must be taken into account when designing a level-five autonomous fleet.

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Driving information logger with in-vehicle communication for autonomous vehicle research

Cited by 10 publications

References 7 publications

Safety driven intelligent autonomous vehicle for smart cities using IoT

Safety driven intelligent autonomous vehicle for smart cities using IoT

A Formal and Quantifiable Log Analysis Framework for Test Driving of Autonomous Vehicles

Autonomous Vehicle Radiation Based on Traffic Flow Analysis

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