Evidence map›Paper›PMID 33494191›Full record

ReviewSensors (Basel, Switzerland)2021

A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges.

M Nadeem Ahangar, Qasim Z Ahmed, Fahd A Khan, Maryam Hafeez

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  10. LLM Multimodal Traffic Accident Forecasting.Sensors (Basel, Switzerland) · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

M Nadeem AhangarSchool of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.
Qasim Z AhmedSchool of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.ORCID 0000-0002-3957-5341
Fahd A KhanSchool of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Maryam HafeezSchool of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatalities in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). Therefore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication technologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium-range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges.

Indexed as

autonomous vehiclesBluetoothdedicated short-range communicationsintelligent transport systemultra-wide bandV2IV2VV2XVANETvehicular communicationsZigBee

Identifiers

PMID33494191
PMCPMC7864337

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.