Multihop Routing in Hybrid Vehicle-to-Vehicle and Vehicle-to-Infrastructure Networks

2018 ◽  
Author(s):  
Yilin Li ◽  
Jian Luo ◽  
Zhongfeng Li ◽  
Richard A. Stirling-Gallacher ◽  
Wen Xu ◽  
...  
Keyword(s):  
Hybrid Vehicle ◽  
Infrastructure Networks ◽  
Multihop Routing ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure

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.

scholarly journals Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1221
Author(s):  
Anum Mushtaq ◽  
Irfan ul Haq ◽  
Wajih un Nabi ◽  
Asifullah Khan ◽  
Omair Shafiq
Keyword(s):  
Traffic Flow ◽  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Flow Management ◽  
V2v Communication ◽  
Cooperative Strategies ◽  
Vehicle To Vehicle ◽  
Traffic Flow Management ◽  
Vehicle To Infrastructure ◽  
Formation And Evolution

Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow.

Application of Connected and Automated Vehicles in a Large-Scale Network by Considering Vehicle-to-Vehicle and Vehicle-to-Infrastructure Technology

2020 ◽  
pp. 036119812096310
Author(s):  
Md Hasibur Rahman ◽  
Mohamed Abdel-Aty
Keyword(s):  
Traffic Safety ◽  
Control Algorithm ◽  
Large Scale ◽  
Signal Control ◽  
Market Penetration ◽  
Automated Vehicles ◽  
Large Scale Network ◽  
Vehicle To Vehicle ◽  
Scale Network ◽  
Vehicle To Infrastructure

Application of connected and automated vehicles (CAVs) is expected to have a significant impact on traffic safety and mobility. Although several studies evaluated the effectiveness of CAVs in a small roadway segment, there is a lack of studies analyzing the impact of CAVs in a large-scale network by considering both freeways and arterials. Therefore, the objective of this study is to analyze the effectiveness of CAVs at the network level by utilizing both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies. Also, the study proposed a new signal control algorithm through V2I technology to elevate the performance of CAVs at intersections. A car-following model named cooperative adaptive cruise control was utilized to approximate the driving behavior of CAVs in the Aimsun Next microsimulation environment. For the testbed, the research team selected Orlando central business district area in Florida, U.S. To this end, the impacts of CAVs were evaluated based on traffic efficiency (e.g., travel time rate [TTR], speed, and average approach delay, etc.) and safety surrogates (e.g., standard deviation of speed, real-time crash-risk models for freeways and arterials, time exposed time-to-collision). The results showed that the application of CAVs reduced TTR significantly compared with the base condition even with the low market penetration level. Also, the proposed signal control algorithm reduced the approach delay for 94% of the total intersections present in the network. Moreover, safety evaluation results showed a significant improvement of traffic safety in the freeways and arterials under CAV conditions with different market penetration rates.

scholarly journals Traffic Flow Density Model and Dynamic Traffic Congestion Model Simulation Based on Practice Case with Vehicle Network and System Traffic Intelligent Communication

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1172 ◽  
Author(s):  
Eduard Zadobrischi ◽  
Lucian-Mihai Cosovanu ◽  
Mihai Dimian
Keyword(s):  
Traffic Congestion ◽  
Model Simulation ◽  
Communication Technologies ◽  
Transport Systems ◽  
Flow Density ◽  
Factors Affecting ◽  
Dedicated Short Range Communications ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Intelligent Communication

The massive increase in the number of vehicles has set a precedent in terms of congestion, being one of the important factors affecting the flow of traffic, but there are also effects on the world economy. The studies carried out so far try to highlight solutions that will streamline the traffic, as society revolves around transportation and its symmetry. Current research highlights that the increased density of vehicles could be remedied by dedicated short-range communications (DSRC) systems through communications of the type vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) or vehicle-to-everything (V2X). We can say that wireless communication technologies have the potential to significantly change the efficiency and road safety, thus improving the efficiency of transport systems. An important factor is to comply with the requirements imposed on the use of vehicle safety and transport applications. Therefore, this paper focuses on several simulations on the basis of symmetry models, implemented in practical cases in order to streamline vehicle density and reduce traffic congestion. The scenarios aim at both the communication of the vehicles with each other and their prioritization by the infrastructure, so we can have a report on the efficiency of the proposed models.

The Localisation Problem in Cooperative Vehicle Applications

2010 ◽  
pp. 200-218 ◽  
Author(s):  
Javier Ibañez-Guzmán
Keyword(s):  
Wireless Communications ◽  
Information Sources ◽  
Road Transportation ◽  
Vehicle To Vehicle ◽  
Communications Technologies ◽  
Digital Road Maps ◽  
Aggregation Of Information ◽  
Vehicle To Infrastructure ◽  
Road Maps ◽  
Spatio Temporal

The next paradigm towards enhancing vehicle safety and road transportation represent cooperative systems. Advances in computer and communications technologies are facilitating the establishment of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications links. This enables the sharing and aggregation of information which results in an extension of the driver awareness horizon in an electronic manner. In this chapter, V2V and V2I applications are considered as a spatio-temporal problem. The tenet is that sharing information can be made only if this is time stamped and related to a spatial description of the information sources. The chapter formulates the spatio-temporal problem having as constraint the precision of the pose estimates of the vehicles involved. It regards the localisation problem and accuracy of digital road maps as a combined issue that needs to be addressed for the successful deployment of cooperative vehicle applications. Two case studies, intersection safely and an overtaking manoeuvre are included. Recommendations on the precision limits of the vehicle pose estimations and the potential uncertainties that need to be considered when designing V2V and V2I applications complete the chapter.

Social interactions in traffic: The effect of external factors

2018 ◽  
Vol 62 (1) ◽  
pp. 97-101 ◽  
Author(s):  
Tanja Stoll ◽  
Nadine-Rebecca Strelau ◽  
Martin Baumann
Keyword(s):  
Social Interactions ◽  
Cooperative Behavior ◽  
Lane Change ◽  
Lane Changing ◽  
Vehicle To Vehicle ◽  
Driving Task ◽  
Vehicle To Infrastructure ◽  
Underlying Mechanisms ◽  
Intention To Change ◽  
Vehicle To Infrastructure Communication

Social interactions were always part of the driving task, but the introduction of vehicle-to-vehicle and vehicle-to-infrastructure communication opens up new possibilities for cooperative interactive driving. It enables drivers to coordinate their maneuvers cooperatively with other involved traffic users. To ensure drivers’ acceptance of such automated systems it is necessary to understand the underlying mechanisms of human cooperation in traffic. In this experiment, we investigate potential influencing factors on the willingness to behave cooperatively in a lane change situation on a highway. In a video-based study, we manipulated the costs of cooperation, the situation’s criticality for the lane-changing vehicle and the way in which the intention to change the lane was indicated. Cooperative behavior is influenced by lower costs, a higher situation’s criticality and by signaling the intention to lane change. These results offer insights that may be used in the developing process of Human Machine Interfaces (HMI) for cooperatively interacting vehicles

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