Digital Effects and Delays in Connected Vehicles: Linear Stability and Simulations

2013 ◽  
Author(s):  
Wubing B. Qin ◽  
Gábor Orosz
Keyword(s):  
Time Delays ◽  
Ride Quality ◽  
Vehicle Design ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Control Loops ◽  
V2v Communication ◽  
Dedicated Short Range Communication ◽  
Vehicle To Vehicle ◽  
Vehicle Platoons

To improve the ride quality in connected vehicle platoons, information about the motion of the leader can be transmitted using vehicle-to-vehicle (V2V) communication and such information can be incorporated in the controllers of the following vehicle. However, according to the current V2V standards, dedicated short range communication (DSRC) devices transmit information every 100 ms which introduces time delays into the control loops. In this paper we study the effects of these time delays on the dynamics of vehicle platoons subject to digital control and derive conditions for plant stability and string stability. It is shown that when the time delay exceeds a critical value, no gain combination can stabilize the system. Our results have important implications on connected vehicle design.

Designing Network Motifs in Connected Vehicle Systems: Delay Effects and Stability

2013 ◽  
Author(s):  
Linjun Zhang ◽  
Gábor Orosz
Keyword(s):  
Nearest Neighbor ◽  
Connected Vehicle ◽  
Cruise Control ◽  
Long Distance ◽  
Analysis And Design ◽  
Vehicle Communication ◽  
V2v Communication ◽  
Vehicle To Vehicle ◽  
Distance Communication ◽  
Vehicle Platoons

Arising technologies in vehicle-to-vehicle (V2V) communication allow vehicles to obtain information about the motion of distant vehicles. Such information can be presented to the driver or incorporated in advanced autonomous cruise control (ACC) systems. In this paper, we investigate the effects of multi-vehicle communication on the dynamics of connected vehicle platoons and propose a motif-based approach that allows systematical analysis and design of such systems. We investigate the dynamics of simple motifs in the presence of communication delays, and show that long-distance communication can stabilize the uniform flow when the flow cannot be stabilized by nearest neighbor interactions. The results can be used for designing driver assist systems and communication-based cruise control systems.

scholarly journals Evaluating Connected Vehicles and Their Applications

2016 ◽  
Vol 138 (12) ◽  
pp. S12-S17 ◽  
Author(s):  
Mohd Azrin Mohd Zulkefli ◽  
Pratik Mukherjee ◽  
Yunli Shao ◽  
Zongxuan Sun
Keyword(s):  
Real Time ◽  
Energy Savings ◽  
Traffic Information ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
New Paradigm ◽  
Target Vehicle ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Research Platform

This article presents evaluation results of connected vehicles and their applications. Vehicle-to-vehicle communication (V2V) and vehicle-to-infrastructure communication (V2I) can enable a new paradigm of vehicle applications. The connected vehicle applications could significantly improve vehicle safety, mobility, energy savings, and productivity by utilizing real-time vehicle and traffic information. In the foreseeable future, connected vehicles need to operate alongside unconnected vehicles. This makes the evaluation of connected vehicles and their applications challenging. The hardware-in-the-loop (HIL) testbed can be used as a tool to evaluate the connected vehicle applications in a safe, efficient, and economic fashion. The HIL testbed integrates a traffic simulation network with a powertrain research platform in real time. Any target vehicle in the traffic network can be selected so that the powertrain research platform will be operated as if it is propelling the target vehicle. The HIL testbed can also be connected to a living laboratory where actual on-road vehicles can interact with the powertrain research platform.

Stability analysis of connected vehicles with V2V communication and time delays: CTCR method via Bézout’s resultant

2021 ◽  
pp. 014233122098142
Author(s):  
Sirin Akkaya ◽  
Onur Akbati ◽  
Ali Fuat Ergenc
Keyword(s):  
Characteristic Equation ◽  
Time Delays ◽  
Characteristic Root ◽  
Sufficient Conditions ◽  
Connected Vehicles ◽  
Multiple Time ◽  
String Stability ◽  
V2v Communication ◽  
Multiple Time Delays ◽  
Input Delays

This paper is focused on the distributed control of connected vehicles via vehicle-to-vehicle (V2V) communication. A mixed predecessor following topology with a virtual leader under constant time headway policy is analysed in case of communication and input delays. The longitudinal dynamics of each vehicle in the platoon is represented by a third-order linear model. Unavoidable communication and input delays are introduced into the platoon structure which converts the characteristic equation of the system into a transcendental type. The stability regions of the system in delay space are obtained by utilizing the cluster treatment of characteristic root (CTCR) method in the case of single and multiple time delays. A new Bézout resultant matrix-based approach is proposed to determine the kernel and offspring hypersurfaces of the CTCR method. The determination of these kernel and offspring hypersurfaces becomes computational costly as the number of vehicles increases in the platoon due to the increasing degree of characteristic equation. However, the proposed method reduces the dimensions of the coefficient matrix which is created by using the characteristic equation. It is concluded that the proposed method confirms the internal stability of the connected vehicles with both generic information flow topologies and formation between vehicles under single and multiple time delays. Thereafter, a local string stability definition is proposed in terms of spacing errors. Sufficient conditions to obtain string stability under mixed predecessor following topology for the existence and nonexistence of time delay are given. Finally, several simulation studies with different scenarios are conducted to display the effectiveness of the proposed model and method for internal and string stabilities.

Suggestion-Based Fuel Efficient Control of Connected and Automated Vehicles

2020 ◽  
Author(s):  
Tinu Vellamattathil Baby ◽  
Pouria Karimi Shahri ◽  
Amir H. Ghasemi ◽  
Baisravan HomChaudhuri
Keyword(s):  
Control Method ◽  
Control Strategies ◽  
Fuel Efficiency ◽  
Connected Vehicle ◽  
Automated Vehicles ◽  
V2v Communication ◽  
Vehicle To Vehicle ◽  
Decision Variables ◽  
Efficient Control ◽  
To Receive

Abstract This paper presents a suggestion-based fuel efficient controller for connected and automated vehicles (CAVs) in presence of human-driven vehicles (HDVs). The suggestion-based controller, apart from evaluating the fuel efficient control solution of the host CAV, provides suggested velocity commands to the HDVs so that the fuel efficiency of itself or the group can improve. We assume that in the connected vehicle system, the HDVs are also able to receive information though Vehicle to Vehicle (V2V) communication and they always try to follow the suggested commands. The suggestion-based control provides additional decision variables to the CAVs with which they can influence the actions of the HDVs and hence improve the fuel efficiency of the whole group. The controller is implemented in a model predictive control (MPC) framework where the suggested command velocities are held constant over some prescribed time so that the driver gets enough time to reach the suggested command velocities. For this control method to function, we present a model that captures the response of a HDV to different suggested-commands. The parameters of the model is obtained from a table-top drive simulator. The accuracy of this model is also validated with the experimental data (table-top drive simulator) and the results are presented in this paper. Simulation studies for the control strategies show the efficacy of the proposed control strategy when compared with existing baseline methods.

scholarly journals Vehicle and Powertrain Optimization for Autonomous and Connected Vehicles

2017 ◽  
Vol 139 (09) ◽  
pp. S19-S23 ◽  
Author(s):  
Yunli Shao ◽  
Mohd Azrin Mohd Zulkefli ◽  
Zongxuan Sun
Keyword(s):  
Energy Savings ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Traffic Information ◽  
Connected Vehicle ◽  
V2v Communication ◽  
Vehicle To Vehicle ◽  
Potential Benefits ◽  
Vehicle To Infrastructure ◽  
Save Energy

This article discusses the potential of using autonomous and connected vehicle (CV) technologies to save energy. It also focuses on the potential energy savings of internal combustion engine-based vehicles (ICVs) and hybrid electric vehicles (HEVs). An example of vehicle and powertrain co-optimization for HEV eco-approaching and departure is also given. CV technologies are gaining increasing attention around the world. Vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication enable real-time access to traffic information that was not available before, including preceding vehicles’ location, speed, pedal position, traffic signal phasing and timing (SPaT). The example shown in this article demonstrates the potential benefits from vehicle and powertrain co-optimization by investigating an eco-approaching and departure application. More research in this area can offer more mature solutions to implement such optimization in a real-production vehicle.

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 Real-Time Safety Optimization of Connected Vehicle Trajectories Using Reinforcement Learning

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3864
Author(s):  
Tarek Ghoul ◽  
Tarek Sayed
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Low Cost ◽  
Safety Evaluation ◽  
Traffic Volume ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Real World Data ◽  
Physical Constraints ◽  
Traffic Conflicts

Speed advisories are used on highways to inform vehicles of upcoming changes in traffic conditions and apply a variable speed limit to reduce traffic conflicts and delays. This study applies a similar concept to intersections with respect to connected vehicles to provide dynamic speed advisories in real-time that guide vehicles towards an optimum speed. Real-time safety evaluation models for signalized intersections that depend on dynamic traffic parameters such as traffic volume and shock wave characteristics were used for this purpose. The proposed algorithm incorporates a rule-based approach alongside a Deep Deterministic Policy Gradient reinforcement learning technique (DDPG) to assign ideal speeds for connected vehicles at intersections and improve safety. The system was tested on two intersections using real-world data and yielded an average reduction in traffic conflicts ranging from 9% to 23%. Further analysis was performed to show that the algorithm yields tangible results even at lower market penetration rates (MPR). The algorithm was tested on the same intersection with different traffic volume conditions as well as on another intersection with different physical constraints and characteristics. The proposed algorithm provides a low-cost approach that is not computationally intensive and works towards optimizing for safety by reducing rear-end traffic conflicts.

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.

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