Analytical studies on an optimized adaptive cruise control model of traffic flow based on self-stabilizing strategy

2020 ◽  
Vol 31 (04) ◽  
pp. 2050054
Author(s):  
Zhipeng Li ◽  
Yingying Liu ◽  
Shangzhi Xu ◽  
Yeqing Qian
Keyword(s):  
Adaptive Cruise Control ◽  
High Reliability ◽  
Cruise Control ◽  
Stabilizing Control ◽  
Traffic Capacity ◽  
Cooperative Adaptive Cruise Control ◽  
Strict Requirement ◽  
Real Time Information ◽  
Fuel Consumption And Emissions ◽  
The Impact

Cooperative adaptive cruise control (CACC) system possesses more remarkable ability to suppress disturbance and enhance the traffic capacity than adaptive cruise control (ACC). However, CACC asks for strict requirement on wireless communication and precise equipment, which remains a big difficulty to implement. This paper extends a new ACC model by introducing the self-stabilizing control with historical data, aimed at achieving the close performance of CACC and make it practicable. Substituting real-time information with pre-stored data substantially reduces the technical demand and offers high reliability to withstand the network delay. Linear stability analysis for this model points out enhancing the value of the gain or time delay of self-stabilizing control benefits to stabilize the traffic. The theories are corroborated via the simulation and further numerical simulations explicate the impact on fuel consumption and emissions and traffic capacity.

Safety, Energy, and Emissions Impacts of Adaptive Cruise Control and Cooperative Adaptive Cruise Control

2020 ◽  
Vol 2674 (6) ◽  
pp. 253-267 ◽  
Author(s):  
Iman Mahdinia ◽  
Ramin Arvin ◽  
Asad J. Khattak ◽  
Amir Ghiasi
Keyword(s):  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Field Tests ◽  
System Level ◽  
Level Energy ◽  
Cruise Control ◽  
Driver Assistance Systems ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon ◽  
Fuel Consumption And Emissions

Connected and automated vehicle technologies have the potential to significantly improve transportation system performance. In particular, advanced driver-assistance systems, such as adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC), may lead to substantial improvements in performance by decreasing driver inputs and taking over control of the vehicle. However, the impacts of these technologies on the vehicle- and system-level energy consumption, emissions, and safety have not been quantified in field tests. The goal of this paper is to study the impacts of automated and cooperative systems in mixed traffic containing conventional, ACC, and CACC vehicles. To reach this goal, experimental data based on real-world conditions are collected (in tests conducted by the Federal Highway Administration and the U.S. Department of Transportation) with presence of ACC, CACC, and conventional vehicles in a vehicle platoon scenario and a cooperative merging scenario. Specifically, a platoon of five vehicles with different vehicle type combinations is analyzed to generate new knowledge about potential safety, energy efficiency, and emission improvement from vehicle automation and cooperation. Results show that adopting the CACC system in a five-vehicle platoon substantially reduces the driving volatility and reduces the risk of rear-end collision which consequently improves safety. Furthermore, it decreases fuel consumption and emissions compared with the ACC system and manually-driven vehicles. Results of the merging scenario show that while the cooperative merging system slightly reduces the driving volatility, the fuel consumption and emissions can increase because of sharper accelerations of CACC vehicles compared with manually-driven vehicles.

scholarly journals Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2433
Author(s):  
Hao Chen ◽  
Hesham A. Rakha
Keyword(s):  
Energy Consumption ◽  
Adaptive Cruise Control ◽  
Combustion Engine ◽  
Signalized Intersections ◽  
Simulation Software ◽  
Vehicle Speed ◽  
Cruise Control ◽  
Optimal Speed ◽  
Cooperative Adaptive Cruise Control ◽  
The Impact

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

Mobility and Energy Consumption Impacts of Cooperative Adaptive Cruise Control Vehicle Strings on Freeway Corridors

2020 ◽  
Vol 2674 (9) ◽  
pp. 111-123
Author(s):  
Hao Liu ◽  
Xiao-Yun Lu ◽  
Steven E. Shladover
Keyword(s):  
Energy Consumption ◽  
Fuel Economy ◽  
Adaptive Cruise Control ◽  
Baseline Scenario ◽  
Vehicle Speed ◽  
Market Penetration ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control ◽  
Freeway Corridors ◽  
The Impact

Cooperative adaptive cruise control (CACC) vehicle string operations have the potential to improve significantly the mobility and energy consumption performance of congested freeway corridors. This study examines the impact of CACC string operations on vehicle speed and fuel economy on the 13-mi SR-99 corridor, near Sacramento, CA. It extends the existing body of knowledge by performing a multi-scenario simulation analysis of the freeway corridor. A simulation study evaluated the performance of the corridor under various CACC market penetration scenarios and traffic demand inputs. The CACC string operation was also analyzed when vehicle awareness device (VAD) and CACC managed lane (ML) strategies were implemented. The case study revealed that the average vehicle speed increased by 70% when the CACC market penetration increased from 0% to 100%. The highest average fuel economy, expressed in miles per gallon (mpg), was achieved under the 50% CACC scenario where mpg was 27. This was 10% higher than the baseline scenario. However, when the CACC market penetration was 50% or higher, the vehicle fuel efficiency only had minor increases. When CACC market penetration reached 100%, the corridor allowed 30% more traffic to enter the network without experiencing reduced average speed. Results also indicate that the VAD strategy increased the speed by 8% when the CACC market penetration was 20% or 40%, while there was a minor decrease in mpg. The ML strategy decreased the corridor performance when implemented alone.

Evaluation and Testing of Driver-Assistive Truck Platooning: Phase 2 Final Results

2017 ◽  
Vol 2615 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Richard Bishop ◽  
David Bevly ◽  
Luke Humphreys ◽  
Stephen Boyd ◽  
Daniel Murray
Keyword(s):  
Fuel Economy ◽  
Short Range ◽  
Adaptive Cruise Control ◽  
Phase 1 ◽  
Phase 2 ◽  
Cruise Control ◽  
Dedicated Short Range Communications ◽  
Cooperative Adaptive Cruise Control ◽  
Transportation Research ◽  
The Impact

Phase 2 final results are described for the FHWA Exploratory Advanced Research project titled Heavy Truck Cooperative Adaptive Cruise Control: Evaluation, Testing, and Stakeholder Engagement for Near Term Deployment, which evaluates the commercial feasibility of driver-assistive truck platooning (DATP). The project was led by Auburn University, in partnership with Peloton Technology, Peterbilt Trucks, Meritor WABCO, and the American Transportation Research Institute. DATP is a form of cooperative adaptive cruise control for heavy trucks (two-truck platoons). It takes advantage of the increasing maturity of vehicle-to-vehicle (V2V) communications (and the expected widespread deployment of V2V connectivity based on dedicated short-range communications over the next decade) to improve freight efficiency, fleet efficiency, safety, and highway mobility as well as reduce emissions. Notably, truck fleets can implement DATP regardless of the regulatory timeline for dedicated short-range communications. The Phase 2 analysis built on Phase 1 and included a testing program of a DATP prototype (with detailed SAE Type 2 fuel economy testing), wireless communications optimization, traffic modeling to understand the impact on roadways at various levels of market penetration, and additional analysis of methods to find DATP partners as well as aerodynamic simulations to understand drag on the vehicles. Detailed analysis of the fuel economy testing data is provided.

scholarly journals Assessment of ACC and CACC systems using SUMO

10.29007/r343 ◽  
2018 ◽  
Author(s):  
Kallirroi N. Porfyri ◽  
Evangelos Mintsis ◽  
Evangelos Mitsakis
Keyword(s):  
Adaptive Cruise Control ◽  
Flow Characteristics ◽  
Simulation Models ◽  
Cruise Control ◽  
Traffic Efficiency ◽  
Cooperative Adaptive Cruise Control ◽  
Automation Systems ◽  
Full Speed ◽  
Car Following Model ◽  
The Impact

Emerging developments in the field of automotive technologies, such as Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) systems, are expected to enhance traffic efficiency and safety on highways and urban roads. For this reason, substantial effort has been made by researchers to model and simulate these automation systems over the last few years. This study aims to integrate a recently developed car-following model for ACC and CACC equipped vehicles in the microscopic traffic simulation tool SUMO; the implemented ACC/CACC simulation models originate from empirical ones, ensuring the collision-free property in the full-speed-range operation. Simulation experiments for different penetration rates of cooperative automated vehicles, desired time-gap settings and network topologies are conducted to test the validity of the proposed approach and to assess the impact of ACC and CACC equipped vehicles on traffic flow characteristics.

Connected Vehicle-Cooperative Adaptive Cruise Control Algorithm to Divide and Reform Connected Vehicle Platoons at Signalized Intersections to Improve Traffic Throughput and Safety

2021 ◽  
pp. 036119812110054
Author(s):  
Yuwei Bie ◽  
Tony Z. Qiu
Keyword(s):  
Adaptive Cruise Control ◽  
Control Variable ◽  
Signalized Intersections ◽  
Connected Vehicle ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control ◽  
Before And After ◽  
Vehicle Platoons ◽  
Real Time Information ◽  
Time Information

The cooperative adaptive cruise control (CACC) algorithm is a simple and effective way to form small-headway platoons so that road capacity and traffic throughput can be improved. The CACC algorithm has been broadly discussed in relation to the highway driving environment where frequent stopping and merging are uncommon. This paper proposes that CACC can also benefit urban arterials, using the appropriate algorithm to predict platoon behavior with optimized trajectories to divide and reform platoons before and after signalized intersections, thus maintaining small, safe headways. Connected vehicle (CV) technology is the key to adapting and improving the CACC algorithm, as it enables the signal phasing plan to be sent to a target CACC platoon and allows vehicles to acquire real-time information from other vehicles in the platoon. In this research, a CV-CACC algorithm is proposed consisting of two functions: platoon division and platoon reforming. The new algorithm is also equipped with acceleration as a new control variable instead of speed, so that the platoon is able to accommodate sharp speed changes around intersections, something the baseline CACC is unable to accommodate. In this study, computer simulations have been conducted to test the reliability of the CV-CACC algorithm and compare its performance against the baseline CACC algorithm.

Impact of Cooperative Adaptive Cruise Control on a Multilane Highway under a Differentiated Per-Lane Speed Limit Policy

2021 ◽  
pp. 036119812110114
Author(s):  
Zhe Xiao ◽  
Xiaoyu Guo ◽  
Xiucheng Guo ◽  
Yi Li
Keyword(s):  
Adaptive Cruise Control ◽  
Speed Limit ◽  
Market Penetration ◽  
Cruise Control ◽  
Passenger Cars ◽  
Policy Makers ◽  
Car Market ◽  
Cooperative Adaptive Cruise Control ◽  
The Subject ◽  
The Impact

Cooperative adaptive cruise control (CACC) has drawn wide attention in recent years for its potential throughput benefit, as it is a promising intermediate technology to the highly connected and automated vehicles. The impact of CACC on multilane highways has been the subject of several studies, but they assumed traffic under a uniform speed limit. Recent research has revealed that traffic performs differently under a differentiated per-lane speed limit (DPLSL) policy with heavy vehicle (HV) restricted lanes. Whether the benefits of CACC still remain under a DPLSL policy has not been explored. This study developed cellular automaton models to incorporate CACC-equipped and non-equipped vehicles (i.e., passenger cars, HVs) on a two-way eight-lane highway with a DPLSL. Results shown throughputs by lane increase up to 78.5% as the CACC car market penetration rate (MPR) rises. Such increases became sharper (i.e., ≥10%) for inner lanes (i.e., HV restricted lanes) and outer lanes after reaching a 40% and a 60% CACC car MPR, separately. Moreover, HVs induced a 1.5% to 15.7% throughput reduction across lanes even under higher CACC car MPRs (i.e., 60%, 80%). This DPLSL policy may cause the lanes to experience a throughput penalty when they are adjacent to lanes with a different speed limit as the MPR of CACC cars rises. Lastly, in traffic with a 60% CACC car MPR, increases are brought further by considering 10% of HV with CACC, especially on those HV non-restricted lanes. The study is helpful for policy makers to further prepare for the prevalence of CACC in the forthcoming years.

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.

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