Connected Vehicle Environment: Opportunities & Challenges

2016 ◽  
Author(s):  
Carl K. Andersen
Keyword(s):  
Connected Vehicle

PreScan-Based Nonlinear Longitudinal Control for Connected Vehicle Platoon

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Yunheng Luo ◽  
Yongfu Li ◽  
Lin Liu ◽  
Wei Hao
Keyword(s):  
Connected Vehicle ◽  
Longitudinal Control ◽  
Vehicle Platoon

Control Model Constructing on Real-Time Dynamic Reversible Lane in Condition of Connected Vehicle

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Lina Mao ◽  
Wenquan Li ◽  
Pengsen Hu ◽  
Guiliang Zhou ◽  
Huiting Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Control Model ◽  
Connected Vehicle ◽  
Time Dynamic

Prototyping EcoCAR Connected Vehicle Testing System Using DigiCAV Development Platform

2020 ◽  
Author(s):  
Trevor Crain ◽  
Pawel Jaworski ◽  
Ioannis Kyriakopoulos ◽  
Richard Blachford ◽  
Brian C. Fabien
Keyword(s):  
Testing System ◽  
Connected Vehicle ◽  
Development Platform ◽  
Vehicle Testing

scholarly journals Blockchain-Based Solutions for UAV-Assisted Connected Vehicle Networks in Smart Cities: A Review, Open Issues, and Future Perspectives

Telecom ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 108-140
Author(s):  
Paulo Álvares ◽  
Lion Silva ◽  
Naercio Magaia
Keyword(s):  
Traffic Congestion ◽  
Resource Constraints ◽  
Smart Cities ◽  
The Internet ◽  
Connected Vehicle ◽  
Sensitive Data ◽  
Internet Of Vehicles ◽  
Smart Vehicles ◽  
Security Properties ◽  
Vehicle Networks

It had been predicted that by 2020, nearly 26 billion devices would be connected to the Internet, with a big percentage being vehicles. The Internet of Vehicles (IoVa) is a concept that refers to the connection and cooperation of smart vehicles and devices in a network through the generation, transmission, and processing of data that aims at improving traffic congestion, travel time, and comfort, all the while reducing pollution and accidents. However, this transmission of sensitive data (e.g., location) needs to occur with defined security properties to safeguard vehicles and their drivers since attackers could use this data. Blockchain is a fairly recent technology that guarantees trust between nodes through cryptography mechanisms and consensus protocols in distributed, untrustful environments, like IoV networks. Much research has been done in implementing the former in the latter to impressive results, as Blockchain can cover and offer solutions to many IoV problems. However, these implementations have to deal with the challenge of IoV node’s resource constraints since they do not suffice for the computational and energy requirements of traditional Blockchain systems, which is one of the biggest limitations of Blockchain implementations in IoV. Finally, these two technologies can be used to build the foundations for smart cities, enabling new application models and better results for end-users.

Sequential Optimization of an Emergency Response Vehicle’s Intra-Link Movement in a Partially Connected Vehicle Environment

2021 ◽  
pp. 036119812110179
Author(s):  
Gaby Joe Hannoun ◽  
Pamela Murray-Tuite ◽  
Kevin Heaslip ◽  
Thidapat Chantem
Keyword(s):  
Emergency Response ◽  
Lateral Position ◽  
Automated System ◽  
Sequential Optimization ◽  
Connected Vehicles ◽  
Linear Programs ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Short Term ◽  
New Approach

This paper introduces a semi-automated system that facilitates emergency response vehicle (ERV) movement through a transportation link by providing instructions to downstream non-ERVs. The proposed system adapts to information from non-ERVs that are nearby and downstream of the ERV. As the ERV passes stopped non-ERVs, new non-ERVs are considered. The proposed system sequentially executes integer linear programs (ILPs) on transportation link segments with information transferred between optimizations to ensure ERV movement continuity. This paper extends a previously developed mathematical program that was limited to a single short segment. The new approach limits runtime overhead without sacrificing effectiveness and is more suitable to dynamic systems. It also accommodates partial market penetration of connected vehicles using a heuristic reservation approach, making the proposed system beneficial in the short-term future. The proposed system can also assign the ERV to a specific lateral position at the end of the link, a useful capability when next entering an intersection. Experiments were conducted to develop recommendations to reduce computation times without compromising efficiency. When compared with the current practice of moving to the nearest edge, the system reduces ERV travel time an average of 3.26 s per 0.1 mi and decreases vehicle interactions.

scholarly journals Optimization and Evaluation of Platooning Car-Following Models in a Connected Vehicle Environment

2021 ◽  
Vol 13 (6) ◽  
pp. 3474
Author(s):  
Guang Yu ◽  
Shuo Liu ◽  
Qiangqiang Shangguan
Keyword(s):  
Communication Technology ◽  
Intelligent Transportation Systems ◽  
Rapid Development ◽  
Safety Margin ◽  
Practical Method ◽  
Transportation Systems ◽  
Systematic Evaluation ◽  
Connected Vehicle ◽  
Car Following ◽  
Cooperative Driving

With the rapid development of information and communication technology, future intelligent transportation systems will exhibit a trend of cooperative driving of connected vehicles. Platooning is an important application technique for cooperative driving. Herein, optimized car-following models for platoon control based on intervehicle communication technology are proposed. On the basis of existing indicators, a series of evaluation methods for platoon safety, stability, and energy consumption is constructed. Numerical simulations are used to compare the effects of three traditional models and their optimized counterparts on the car-following process. Moreover, the influence of homogenous and heterogeneous attributes on the platoon is analyzed. The optimized model proposed in this paper can improve the stability and safety of vehicle following and reduce the total fuel consumption. The simulation results show that a homogenous platoon can enhance the overall stability of the platoon and that the desired safety margin (DSM) model is better suited for heterogeneous platoon control than the other two models. This paper provides a practical method for the design and systematic evaluation of a platoon control strategy, which is one of the key focuses in the connected and autonomous vehicle industry.

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