Autonomous Traffic Management: Open Issues and New Directions

Hamdani, Sara El; Benamar, Nabil

doi:10.1109/mownet.2018.8428937

Cited by 14 publications

(5 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some researchers focused on ramp metering as in [22], while others concentrated on intersection management on a larger scale such as [23] and [24]. That said, besides the AV traffic management algorithm itself, which is sometimes quite complicated, there are side problems that need to be handled [25] such as the coexistence of AV with human-driven cars, pedestrians, motorcyclists, etc. ; dealing with complicated situations such as severe weather conditions or natural accidents, advanced architecture support.…”

Section: ) Traffic Flow Optimizationmentioning

confidence: 99%

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Hataba

Sherif

Mahmoud

et al. 2022

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

Artificial Intelligence (AI) is changing every technology we are used to deal with. Autonomy has long been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Big auto manufacturers as well are investing billions of dollars to produce Autonomous Vehicles (AVs). This new technology has the potential to provide more safety for passengers, less crowded roads, congestion alleviation, optimized traffic, fuel-saving, less pollution as well as enhanced travel experience among other benefits. But this new paradigm shift comes with newly introduced privacy issues and security concerns. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected. They collect huge troves of information, which needs to be protected from breaches. In this work, we investigate security challenges and privacy concerns in AVs. We examine different attacks launched in a layer-based approach. We conceptualize the architecture of AVs in a four-layered model. Then, we survey security and privacy attacks and some of the most promising countermeasures to tackle them. Our goal is to shed light on the open research challenges in the area of AVs as well as offer directions for future research.

show abstract

Section: ) Traffic Flow Optimizationmentioning

confidence: 99%

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Hataba

Sherif

Mahmoud

et al. 2022

IEEE Open J. Commun. Soc.

View full text Add to dashboard Cite

show abstract

“…Mohamed Nahri et al 19 Deep analysis of traffic state. Sara EI Hamdani et al 20 Discussed many issues related to traffic control.…”

Section: Novel Framework For Real Time Collection Of Information Rela...mentioning

confidence: 99%

Intelligent traffic management system using Ant Colony Optimization and Internet of Things

Dureja

Sangwan

2022

Int J Communication

View full text Add to dashboard Cite

Summary Miniaturization of Internet of Things (IoT) enabled devices has led to advancement in Intelligent Transportation System. Some of the challenges for efficient traffic management are connection of vehicles through an IP based infrastructure for transportation, reliable, and flexible traffic control management, maintaining quality of services for video streaming applications in Internet of Vehicles and many more. Today there is a need of an efficient transportation system with improved efficiency of traffic safety and lower traveling costs. An intelligent traffic control system using Ant Colony Optimization (ACO) algorithm has been proposed and analyzed in this paper. Proposed algorithm has been compared with existing state of art algorithms in terms of average waiting time and average traveling time.

show abstract

“…Similarly, the mathematical model proposed in this study is considered independent of the communication protocols and the architectural details for the model are beyond the scope of this paper. The pros and cons of using V2V and V2I communication strategies were highlighted in [28]. The study assumes standardised methods should be used based on current and future best practices of message delivery and communication technologies and by using a combination of V2V and V2I, where former could be used, e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Novel mathematical model to determine geo‐referenced locations for C‐ITS communications to generate dynamic vehicular gaps

Bhargava

Choy

Jennings

et al. 2020

IET intell. transp. syst

View full text Add to dashboard Cite

The study aims at determining geo-reference locations for dynamic cooperative communications to be established, allowing the generation of dynamic vehicular gaps between the Dangerous Goods Vehicles and their surrounding vehicles, such that they could travel via a tunnel as a platoon and in isolation. This will ensure the safety of other road users in line with checkand-allow procedures at the road tunnel on Trans-European Transport Network, as per ADR regulations. The model is verified for different road layouts approaching a road tunnel in the UK, using varying traffic scenarios to determine if the identified georeferenced location by the model is at suitable distances for gap generation. The results are compared against the simulated real-world tunnel traffic flow with conventional vehicles involving escorting of Dangerous Goods Vehicles via human operators. The mixed traffic and connected vehicles traffic flow scenarios are simulated for dynamic gap generation and compared against real-world tunnel scenario to analyse the improvements in travel time, queues and congestion.

show abstract

Autonomous Traffic Management: Open Issues and New Directions

Cited by 14 publications

References 23 publications

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Security and Privacy Issues in Autonomous Vehicles: A Layer-Based Survey

Intelligent traffic management system using Ant Colony Optimization and Internet of Things

Novel mathematical model to determine geo‐referenced locations for C‐ITS communications to generate dynamic vehicular gaps

Contact Info

Product

Resources

About