Review of Recent Developments in Sustainable Traffic Management System

Sharma, Bhawini; Maherchandani, Jai Kumar

doi:10.1007/978-981-16-6482-3_40

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…According to the research, [23] developed the generic assistance model for drivers using logic reasoning applied to a database of traffic conditions. Everything from automobiles to traffic signs to traffic lights, as well as the relationships between them, can be found in the same region.…”

Section: Related Workmentioning

confidence: 99%

Internet of Things-Based Intelligent Ontology Model for Safety Purpose Using Wireless Networks

Shakya

Sundar

Kushwaha

et al. 2022

Wireless Communications and Mobile Computing

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Intelligent transportation systems (ITS) are a newer trend in technology that improve the safety and performance in transportation systems. The exchange of information is considered as one of the key elements for ITS since it involves communication between vehicles and other components of ITS on road. On other hand, the data collections via Internet of Things (IoT) sensors play a major role for data collection and transmission between the vehicles and road segments in ITS. The data collection provides the current traffic and weather conditions that is considered necessary for driving in traffic. However, energy savings is one of the predominant objectives of electric vehicle (EV) while it is connected with ITS. In this research, we propose an ontology-based architecture for EVs using the data collected from IoT sensor network, which is intended to improve the overall driving experience. The system uses IoT sensor data to execute a range of activities in order to ensure the driver safety and comfort while on the road. The simulation is conducted on an Eclipse SUMO simulator, and the performance is reported. The results of simulation shows that the proposed intelligent model on making decisions along with weather and traffic conditions is reported efficient than existing ITS models.

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Section: Related Workmentioning

confidence: 99%