Towards a Sustainable Ecosystem of Intelligent Transportation Systems

Tseng, Lewis; Wong, Liwen

doi:10.1109/percomw.2019.8730669

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…3 Sustainability transcends the management of Studies have shown that increased use of vehicles results in a subsequent rise in the number of road accidents. 4 Statistics from Asia showed that in 2018, an estimated over 50,000 deaths were caused by preventable or careless accidents. 5 Some of the causes of road accidents include congestion-related collisions, distracted driving, and improper taking of bends, unsafe changing of lanes, environmental disasters, and pedestrian or animal crossing.…”

Section: R E T R a C T E Dmentioning

confidence: 99%

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RETRACTED: Intelligent transportation system for sustainable environment in smart cities

Liang

Jia

2021

International Journal of Electrical Engineering & Education

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Advanced technology has ushered in the urge to enhance the travel experience. Besides the consistent desire to travel faster and more comfortably, the need to ensure transportation sustainability has remained constant. Smart cities employ top-grade technological applications to facilitate operations. Intelligent transportation systems involve the use of advanced transportation technologies. Through the integration of the Internet of Vehicles, cars in traffic can send and receive data between themselves and other vehicles and the environment. This data is processed to ensure efficient transportation by controlling traffic flows and preventing accidents. In this study, a literature review is conducted on how intelligent transportation systems contribute to environmental sustainability in smart cities. With technologies such as electricity-driven cars and autonomous vehicles, the systems minimize the emission of toxic substances to the environment while enhancing the interaction of the car with its surroundings to avoid accidents.

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Section: R E T R a C T E Dmentioning

confidence: 99%

“…The integration of infrastructure and ITC to achieve digital management; (4) From closed communities into smart communities. To build a smart city in the era of big data, its construction plan must have the following points.…”

Section: R E T R a C T E Dmentioning

confidence: 99%

RETRACTED: Intelligent transportation system for sustainable environment in smart cities

Liang

Jia

2021

International Journal of Electrical Engineering & Education

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“…It is mainly used to optimize decision making in transportation. The main applications of the IT system are efficient mobility, traffic management, 9 data transmission technology, electronic sensor technology, and intelligent control technology in the transportation system 10 . So IT scheme is considered by the smart cities as a major component.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation on the node mobility with respect to human driver behavior prediction in vehicular ad hoc network using adaptive deer hunting Optimized Link State Routing Protocol

Swamynathan¹,

Palanichamy²,

Jerald³

2021

Int J Communication

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Summary In vehicular ad hoc network (VANET) broadcasting is considered as the critical area of research. The vehicles are connecting in an ad hoc manner to create a network of a wider range. In an intelligent transport system (ITS), with vehicle to vehicle (V2V) communication in the VANET is used to support the network backbone and which the accident prevention technique has been deployed for ensuring the road safety. The major reason for the road accident is the abnormal driving behavior of human drivers. The movement pattern of the vehicle is the main factor of the network topology so that the impact of human driving pattern influences the performance and behavior of the network. Driving behavior can be classified as reckless, normal, drunken, and fatigue driving. During driving, the behavior of human drivers was predicted in this paper, thereby providing the performance analysis on the mobility of the network. For the improvement of a driver behavior, the hybridized mega‐trend diffusion (MTD) with optimized deep belief network–sunflower optimization (DBN‐SFO) is used. Here, the network performance of the adaptive deer hunting Optimized Link State Routing Protocol (ADHOLSR) is analyzed in NS2 simulation platform.

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