Data fusion in intelligent transportation systems: Progress and challenges - A survey

By Nour-Eddin El Faouzi, Henry Leung, Ajeesh P. Kurian. 2011

460 citations recorded by the source corpus.

Subfields: Building and Construction, Environmental Engineering, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Javier del Ser
2. Ibai Lana
3. M. Vélez
4. Alexandre M. Bayen
5. Henry Leung
6. Zheng Yan
7. Laurence Tianruo Yang
8. Sherali Zeadally

In Environmental Engineering

1. Hao Zhu
2. Henry Leung
3. Alexandre M. Bayen
4. Eleni I. Vlahogianni
5. Ka-Veng Yuen
6. Lyudmila S. Mihaylova

In Signal Processing

1. Alexandre M. Bayen
2. Hao Zhu
3. Henry Leung
4. Laurence Tianruo Yang
5. Rasheed Hussain
6. Ka-Veng Yuen
7. Lyudmila S. Mihaylova

Citations in the corpus

• A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019, background): “Objectives and Topics Limitation [15] Focus on data fusion algorithms and theories Not highly related to IoT data fusion [16] Focus on data fusion methods in specific IoT environments Ignore privacy and security in IoT data fusion [17] Classification of data fusion methods: stage-based methods, feat”
• A survey of data fusion in smart city applications (2019, neutral): “El et al. [22] Provides a survey on the intelligent transportation systems, which use data fusion techniques.”
• Road Traffic Forecasting: Recent Advances and New Challenges (2018, background): “In this line, data fusion techniques allow to combine data from different sources in the same model, including traffic data from different sensors, or non-traffic inputs [33], and it is considered by [25], [34] as one of the main challenges in this field.”
• Overview of Environment Perception for Intelligent Vehicles (2017, background): “Intelligent vehicles technologies are based on the information of the ego vehicle and its surroundings, such as the lanes, roads, and other vehicles, using the sensors of intelligent vehicles [4], [5].”
• Autonomous Cars: Research Results, Issues, and Future Challenges (2019, background): “Information fusion based on data from various sources in connected cars and the autonomous car environment will have significant security challenges that must be resolved [188].”
• Estimate Dynamic Road Travel Time Based on Uncertainty Feedback (2014, background): “El Faouzi [12] investigated the use of evidence theory to present a classifier and distance based approach for the fusion of probe vehicle reports and measurements from loop detectors.”
• Potential Cyberattacks on Automated Vehicles (2015, background): “Moreover, attack trees do not specifically integrate the detection part, which is necessary to assess the probability of success of the attack.”
• Opinion Mining and Information Fusion: A survey (2016, background): “[156] provide a survey of the application of Information Fusion in different areas of Intelligent Transport Systems (ITS).”
• Traffic state estimation on highway: A comprehensive survey (2017, methodology): “…and Papageorgiou, 2005, section 1) (we avoid overlapping with this one), data fusion in generic intelligent transportation system (ITS) research (El Faouzi et al., 2011), emerging traffic data collection methods in 2011 (Antoniou et al., 2011), coordinate system in traffic flow models for TSE…”