itsblue: A Bluetooth-Based Framework for Intersection Management ITS Applications

2016 ◽  
Author(s):  
Ahmed Alghamdi ◽  
Tamer Nadeem ◽  
Mecit Cetin
Keyword(s):  
Intersection Management

scholarly journals Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed
Keyword(s):  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Autonomous Driving ◽  
Use Cases ◽  
Cooperative Driving ◽  
Vehicle To Vehicle ◽  
Future Challenges ◽  
Vehicle To Infrastructure ◽  
High Level ◽  
Intersection Management

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

R2 IM- Robust and Resilient Intersection Management of Connected Autonomous Vehicles

2020 ◽  
Author(s):  
Mohammad Khayatian ◽  
Rachel Dedinsky ◽  
Sarthake Choudhary ◽  
Mohammadreza Mehrabian ◽  
Aviral Shrivastava
Keyword(s):  
Autonomous Vehicles ◽  
Intersection Management

A Survey on Intersection Management of Connected Autonomous Vehicles

2020 ◽  
Vol 4 (4) ◽  
pp. 1-27 ◽  
Author(s):  
Mohammad Khayatian ◽  
Mohammadreza Mehrabian ◽  
Edward Andert ◽  
Rachel Dedinsky ◽  
Sarthake Choudhary ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Intersection Management

Development and Evaluation of Cooperative Intersection Management Algorithm under Connected and Automated Vehicles Environment

2021 ◽  
pp. 036119812199458
Author(s):  
Slobodan Gutesa ◽  
Joyoung Lee ◽  
Dejan Besenski
Keyword(s):  
Travel Time ◽  
Information Exchange ◽  
Fixed Time ◽  
Optimization Method ◽  
Time Signal ◽  
Market Penetration ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Concept Evaluation ◽  
Intersection Management

Recent technological advancements in the automotive and transportation industry established a firm foundation for development and implementation of various connected and automated vehicle solutions around the globe. Wireless communication technologies such as the dedicated short-range communication protocol are enabling information exchange between vehicles and infrastructure. This research paper introduces an intersection management strategy for a corridor with automated vehicles utilizing vehicular trajectory-driven optimization method. Trajectory-Driven Optimization for Automated Driving provides an optimal trajectory for automated vehicles based on current vehicle position, prevailing traffic, and signal status on the corridor. All inputs are used by the control algorithm to provide optimal trajectories for automated vehicles, resulting in the reduction of vehicle delay along the signalized corridor with fixed-time signal control. The concept evaluation through microsimulation reveals that, even with low market penetration (i.e., less than 10%), the technology reduces overall travel time of the corridor by 2%. Further increase in market penetration produces travel time and fuel consumption reductions of up to 19.5% and 22.5%, respectively.

Intersection Management Based on V2I Velocity Synchronization

2015 ◽  
pp. 449-470 ◽  
Author(s):  
Xuguang Hao ◽  
Abdeljalil Abbas-Turki ◽  
Florent Perronnet ◽  
Rachid Bouyekhf ◽  
Abdellah El Moudni
Keyword(s):  
Intersection Management
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