scholarly journals Platoon Merging Approach Based on Hybrid Trajectory Planning and CACC Strategies

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2626
Author(s):  
Carlos Hidalgo ◽  
Ray Lattarulo ◽  
Carlos Flores ◽  
Joshué Pérez Rastelli
Keyword(s):  
Trajectory Planning ◽  
Traffic Congestion ◽  
Efficient Solutions ◽  
Test Case ◽  
Cruise Control ◽  
Automated Driving ◽  
Modular Architecture ◽  
The Road ◽  
Cooperative Adaptive Cruise Control ◽  
Multiple Vehicles

Currently, the increase of transport demands along with the limited capacity of the road network have increased traffic congestion in urban and highway scenarios. Technologies such as Cooperative Adaptive Cruise Control (CACC) emerge as efficient solutions. However, a higher level of cooperation among multiple vehicle platoons is needed to improve, effectively, the traffic flow. In this paper, a global solution to merge two platoons is presented. This approach combines: (i) a longitudinal controller based on a feed-back/feed-forward architecture focusing on providing CACC capacities and (ii) hybrid trajectory planning to merge platooning on straight paths. Experiments were performed using Tecnalia’s previous basis. These are the AUDRIC modular architecture for automated driving and the highly reliable simulation environment DYNACAR. A simulation test case was conducted using five vehicles, two of them executing the merging and three opening the gap to the upcoming vehicles. The results showed the good performance of both domains, longitudinal and lateral, merging multiple vehicles while ensuring safety and comfort and without propagating speed changes.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

A First Investigation of Truck Drivers’ Preferences and Behaviors using a Prototype Cooperative Adaptive Cruise Control System

2018 ◽  
Vol 2672 (34) ◽  
pp. 39-48 ◽  
Author(s):  
Shiyan Yang ◽  
Steven E. Shladover ◽  
Xiao-Yun Lu ◽  
Hani Ramezani ◽  
Aravind Kailas ◽  
...  
Keyword(s):  
Adaptive Cruise Control ◽  
Aerodynamic Drag ◽  
Truck Drivers ◽  
Cruise Control ◽  
Fuel Savings ◽  
The Road ◽  
Cooperative Adaptive Cruise Control ◽  
And Behaviors ◽  
On The Road ◽  
And Performance

Cooperative adaptive cruise control (CACC) is a driver-assist technology that uses vehicle-to-vehicle wireless communication to realize faster braking responses in following vehicles and shorter headways compared with adaptive cruise control. This technology not only enhances road safety, but also offers fuel savings benefits as a result of reduced aerodynamic drag. The amount of fuel savings is dictated by the following distances and the driving speeds. So, the overarching goal of this work is to explore driving preferences and behaviors when following in “CACC mode,” an area that remains largely unexplored. While in CACC mode, the brake and throttle actions are automated. A human factors study was conducted to investigate truck drivers’ experiences and performance using CACC at shorter-than-normal vehicle following time gaps. “On-the-road” experiments were conducted by recruiting drivers from commercial fleets to operate the second and third trucks in a three-truck CACC string. The driving route spanned 160 miles on freeways in Northern California and five different time gaps between 0.6 and 1.8 seconds were tested. Factors such as cut-ins by other vehicles, road grades, and traffic conditions were found to influence the drivers’ opinions about use of CACC. The findings presented in this paper provide insights into the factors that will influence driver reactions to the deployment of CACC in their truck fleets.

scholarly journals Transitions Between Highly Automated and Longitudinally Assisted Driving: The Role of the Initiator in the Fight for Authority

2020 ◽  
pp. 001872082094618 ◽  
Author(s):  
Davide Maggi ◽  
Richard Romano ◽  
Oliver Carsten
Keyword(s):  
Road Safety ◽  
Driving Simulator ◽  
Cruise Control ◽  
Automated Driving ◽  
Safety Issues ◽  
The Road ◽  
Operational Design ◽  
Level 3 ◽  
Driving Task

Objective A driving simulator study explored how drivers behaved depending on their initial role during transitions between highly automated driving (HAD) and longitudinally assisted driving (via adaptive cruise control). Background During HAD, drivers might issue a take-over request (TOR), initiating a transition of control that was not planned. Understanding how drivers behave in this situation and, ultimately, the implications on road safety is of paramount importance. Method Sixteen participants were recruited for this study and performed transitions of control between HAD and longitudinally assisted driving in a driving simulator. While comparing how drivers behaved depending on whether or not they were the initiators, different handover strategies were presented to analyze how drivers adapted to variations in the authority level they were granted at various stages of the transitions. Results Whenever they initiated the transition, drivers were more engaged with the driving task and less prone to follow the guidance of the proposed strategies. Moreover, initiating a transition and having the highest authority share during the handover made the drivers more engaged with the driving task and attentive toward the road. Conclusion Handover strategies that retained a larger authority share were more effective whenever the automation initiated the transition. Under driver-initiated transitions, reducing drivers’ authority was detrimental for both performance and comfort. Application As the operational design domain of automated vehicles (Society of Automotive Engineers [SAE] Level 3/4) expands, the drivers might very well fight boredom by taking over spontaneously, introducing safety issues so far not considered but nevertheless very important.

scholarly journals Why do we make safe behaviour so hard for drivers?

2021 ◽  
Vol 32 (1) ◽  
Keyword(s):  
Road Safety ◽  
Visual Information ◽  
Developed Countries ◽  
Assistive Technologies ◽  
Road User ◽  
Cruise Control ◽  
Automated Driving ◽  
The Road ◽  
Road Users ◽  
Road System

Despite significant improvements in road safety in Australia and developed countries over some decades, the downward trend in fatalities and serious injuries has slowed markedly, and even stalled. New strategies are needed to turn this trend around. Current road safety philosophy, the Safe System, has been effective, but needs broadening to increase the scope of solutions. The Safe System accepts that road users make errors and that the road system should be forgiving of those errors. This leads to countermeasures that emphasise limiting consequences of crashes like lowered speeds, crashworthy vehicles and roads. The problem is that conceptualising road-user error as inevitable ignores the fact that many road-user errors are caused by poor design of the road system including roads, vehicles and road rules. It means road safety overlooks productive avenues for prevention of road-user error and crashes. This paper discusses this issue with Safe System and provides examples of poor road system design that make it difficult for road users to behave safely. This includes poor road rules like inappropriate speed limits, inadequate road design such as poor signage and confusing lane-marking, inadequate vehicle design that limits vision or provides false visual information, as well as problems with driver-assistive technologies: cruise control, automated driving and warning systems. In each case the paper discusses how poor design fails to account for human capacities making it hard for road-users to behave safely. Importantly the paper looks at solutions to these problems and provides some new principles for Safe System.

scholarly journals Modeling Microscopic Car-Following Strategy of Mixed Traffic to Identify Optimal Platoon Configurations for Multiobjective Decision-Making

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Mudasser Seraj ◽  
Jiangchen Li ◽  
Zhijun Qiu
Keyword(s):  
Mixed Traffic ◽  
Cruise Control ◽  
Automated Driving ◽  
Driving System ◽  
Car Following ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control ◽  
Traffic Stream ◽  
Car Following Model ◽  
The Cost

Microscopic detail of complex vehicle interactions in mixed traffic, involving manual driving system (MDS) and automated driving system (ADS), is imperative in determining the extent of response by ADS vehicles in the connected automated vehicle (CAV) environment. In this context, this paper proposes a naïve microscopic car-following strategy for a mixed traffic stream in CAV settings and specified shifts in traffic mobility, safety, and environmental features. Additionally, this study explores the influences of platoon properties (i.e., intra-platoon headway, inter-platoon headway, and maximum platoon length) on traffic stream characteristics. Different combinations of MDS and ADS vehicles are simulated in order to understand the variations of improvements induced by ADS vehicles in a traffic stream. Simulation results reveal that grouping ADS vehicles at the front of traffic stream to apply Cooperative Adaptive Cruise Control (CACC) based car-following model will generate maximum mobility benefits for upstream vehicles. Both mobility and environmental improvements can be realized by forming long, closely spaced ADS vehicles at the cost of reduced safety. To achieve balanced mobility, safety, and environmental advantages from mixed traffic environment, dynamically optimized platoon configurations should be determined at varying traffic conditions and ADS market penetrations.

Robust Cooperative Adaptive Cruise Control Design for Connected Vehicles

2015 ◽  
Author(s):  
Mark Trudgen ◽  
Javad Mohammadpour
Keyword(s):  
Traffic Congestion ◽  
Adaptive Cruise Control ◽  
Connected Vehicles ◽  
Cruise Control ◽  
String Stability ◽  
Reduction Techniques ◽  
Stability Robustness ◽  
Cooperative Adaptive Cruise Control ◽  
And Performance ◽  
Viable Approach

In this paper, we design and validate a robust H∞ controller for Cooperative Adaptive Cruise Control (CACC) in connected vehicles. CACC systems take advantage of onboard sensors and wireless technologies working together in order to achieve smaller inter-vehicle following distances, with the overall goal of increasing vehicle throughput on busy highways, and hence serving as a viable approach to reduce traffic congestion. A group of connected vehicles equipped with CACC technology must also ensure what is known as string stability. This requirement effectively dictates that disturbances should be attenuated as they propagate along the platoon of following vehicles. In order to guarantee string stability and to cope with the uncertainties seen in the vehicle model used for a model-based CACC, we propose to design and implement a robust H∞ controller. Loop shaping design methodology is used in this paper to achieve desired tracking characteristics in the presence of competing string stability, robustness and performance requirements. We then employ model reduction techniques to reduce the order of the controller and finally implement the reduced-order controller on a simulation model demonstrating the robust properties of the closed-loop system.

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