A review of recent advancements and applications of 4D millimeter-wave radar in smart highways

Abstract Smart highways, as vital components of intelligent transportation systems (ITS), have driven a growing demand for sophisticated sensing technologies. Among these, 4D millimeter-wave (mmWave) radar has emerged as a cornerstone, thanks to its capacity for high-resolution, real-time monitoring of complex traffic scenes. Unlike traditional radar systems, 4D mmWave not only measures the distance, velocity, and azimuth of moving objects but also captures elevation information, yielding an enriched three-dimensional understanding of the road environment. Although substantial research has been conducted on 4D mmWave radar in onboard applications, a comprehensive review focusing on its potential in roadside scenarios, such as smart highways, is currently lacking. This paper addresses that gap by first reviewing the operating principles of 4D mmWave radar and then examining how it integrates with complementary sensors. We assess its performance in key roadside functions, including multi-target detection, vehicle trajectory tracking, and macroscopic traffic flow monitoring. Further, we discuss critical challenges—such as real-time data processing bottlenecks, system scalability across extended highway networks, and suppression of inter-radar interference. By synthesizing current research and pinpointing outstanding issues, this review offers a comprehensive overview of 4D mmWave radar’s expanding role in smart highway ITS and outlines promising directions for future investigation.

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Institutions

Publication Details

Journal
Urban Lifeline
Published
2025-08-18
DOI
https://doi.org/10.1007/s44285-025-00048-1
Citations
5
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
24.97

Funders

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article

A review of recent advancements and applications of 4D millimeter-wave radar in smart highways

Kai Zhang, Qing Wang, Xiaolin Meng
5 citations
Urban Lifeline
Radar Systems and Signal Processing
24.97
article

A review of recent advancements and applications of 4D millimeter-wave radar in smart highways

Kai Zhang, Qing Wang, Xiaolin Meng
article en
5 citations

Abstract

Abstract Smart highways, as vital components of intelligent transportation systems (ITS), have driven a growing demand for sophisticated sensing technologies. Among these, 4D millimeter-wave (mmWave) radar has emerged as a cornerstone, thanks to its capacity for high-resolution, real-time monitoring of complex traffic scenes. Unlike traditional radar systems, 4D mmWave not only measures the distance, velocity, and azimuth of moving objects but also captures elevation information, yielding an enriched three-dimensional understanding of the road environment. Although substantial research has been conducted on 4D mmWave radar in onboard applications, a comprehensive review focusing on its potential in roadside scenarios, such as smart highways, is currently lacking. This paper addresses that gap by first reviewing the operating principles of 4D mmWave radar and then examining how it integrates with complementary sensors. We assess its performance in key roadside functions, including multi-target detection, vehicle trajectory tracking, and macroscopic traffic flow monitoring. Further, we discuss critical challenges—such as real-time data processing bottlenecks, system scalability across extended highway networks, and suppression of inter-radar interference. By synthesizing current research and pinpointing outstanding issues, this review offers a comprehensive overview of 4D mmWave radar’s expanding role in smart highway ITS and outlines promising directions for future investigation.

Urban LifelineVol. 3(1)
Southeast University (CN)
Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 1%
Radar Systems and Signal Processing
24.97
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A review of recent advancements and applications of 4D millimeter-wave radar in smart highways — Kai Zhang, Qing Wang, et al. · Urban Lifeline (2025) | TGRS Research Map | TGRS