Improving Urban Traffic Throughput With Vehicle Platooning: Theory and Experiments

Smith, Stanley W.; Kim, Yeojun; Guanetti, Jacopo; Li, Ruolin; Firoozi, Roya; Wootton, Bruce; Kurzhanskiy, Alexander A.; Borrelli, Francesco; Horowitz, Roberto; Arcak, Murat

doi:10.1109/access.2020.3012618

Cited by 32 publications

(11 citation statements)

References 19 publications

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“…For Eco-CACC-U control, many researchers have taken a systematic approach to test and evaluate that particular technology (38)(39)(40)(41). Lammert et al evaluated fuel consumption results of two Class 8 tractor-trailer combinations platooned together compared with their stand-alone fuel consumption (42).…”

Section: Literature Reviewmentioning

confidence: 99%

“…They tested various speeds, distance gaps, and the mass of the vehicles to determine the best combination leading to the lowest fuel consumption. Smith et al developed a model-predictive control-based approach for vehicle platooning in an urban traffic setting ( 38 ). Their study involved experiments performed with real test vehicles on a closed track and demonstrated that vehicle platooning has the potential to increase throughput significantly at intersections.…”

Section: Literature Reviewmentioning

confidence: 99%

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Evaluating an Eco-Cooperative Automated Control System

Ahn

Farag

et al. 2022

Transportation Research Record: Journal of the Transportation R

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The paper evaluates an Eco-Cooperative Automated Control (Eco-CAC) system on a large-scale network considering a combination of internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), and battery-only electric vehicles (BEVs) in a microscopic traffic simulation environment. We used a novel integrated control system that: (1) routes ICEVs, HEVs, and BEVs in a fuel/energy-efficient manner; (2) selects vehicle speeds based on anticipated traffic network evolution; (3) minimizes vehicle fuel/energy consumption near signalized intersections; and (4) intelligently modulates the longitudinal motion of vehicles along freeways within a cooperative platoon to minimize fuel/energy consumption. The study tested the system using the INTEGRATION software on the Los Angeles (LA), U.S., downtown network for three different demand levels: no congestion, mild congestion, and heavy congestion. The results demonstrated that the Eco-CAC system effectively reduces vehicle fuel and energy consumption, travel time, total delay, and stopped delay in heavily congested conditions. However, different vehicle compositions produced different results. In particular, the maximum energy consumption savings for BEVs (36.9%) for a current vehicle composition occurred at a 10% market penetration rate (MPR) of connected automated vehicles (CAVs) in mild congestion, while the maximum savings for a future vehicle composition (35.5%) occurred at a 50% CAV MPR in no congestion. The system reduced fuel consumption for ICEVs and HEVs by up to 5.4% and 6.3% at a 25% CAV MPR in heavy congestion for current and future vehicle compositions, respectively. However, the system increased total fuel consumption by up to 4.6% at a 50% CAV MPR in no congestion for a current vehicle composition. The study demonstrates that the effectiveness of the Eco-CAC system depends on traffic conditions, including congestion level, network configuration, CAV MPR, and vehicle composition.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Evaluating an Eco-Cooperative Automated Control System

Ahn

Farag

et al. 2022

Transportation Research Record: Journal of the Transportation R

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Section: B) Green Lightmentioning

confidence: 99%

“…Similar with [37], we consider that a platoon is deemed to pass the stop line if the leader vehicle of the platoon passes the stop line. Thus, V k,1 first observes the remaining time of green light and then estimates whether it can accelerate with the maximum acceleration a specified in [26] to ensure it passes the stop line before the due time of the green light [37]. If V k,1 can pass the stop line, V k,1 makes a uniform acceleration linear motion with acceleration a until it passes the stop line; Otherwise, it reduces its acceleration in real time, similar to its operation under the red light.…”

Section: B) Green Lightmentioning

confidence: 99%

Time-Dependent Performance Modeling for Platooning Communications at Intersection

Wu,

Zhao,

Fan

2022

Preprint

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With the development of internet of vehicles, platooning strategy has been widely studied as the potential approach to ensure the safety of autonomous driving. Vehicles in the form of platoon adopt 802.11p to exchange messages through vehicle to vehicle (V2V) communications. When multiple platoons arrive at an intersection, the leader vehicle of each platoon adjusts its movement characteristics to ensure that it can cross the intersection and thus the following vehicles have to adjust their movement characteristics accordingly. In this case, the time-varying connectivity among vehicles leads to the significant non-stationary performance change in platooning communications, which may incur safety issues. In this paper, we construct the time-dependent model to evaluate the platooning communication performance at the intersection based on the initial movement characteristics. We first consider the movement behaviors of vehicles at the intersection including turning, accelerating, decelerating and stopping as well as the periodic change of traffic lights to construct movement model, and then establish a hearing network to reflect the time-varying connectivity among vehicles. Afterwards, we adopt the pointwise stationary fluid flow approximation (PSFFA) to model the non-stationary behavior of transmission queue. Then, we consider four access categories (ACs) and continuous backoff freezing of 802.11p to construct the models to describe the time-dependent access process of 802.11p. Finally, based on the time-dependent model, the packet transmission delay and packet delivery ratio are derived.The accuracy of our proposed model is verified by comparing the simulation results with analytical results.

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“…Automated and connected mobility is currently forecasted reshaping public and private transportation over the next few decades [1][2][3][4]. Remarkable benefits could be achieved in general through implementing automated mobility, including enhancing passenger comfort, reducing energy consumption for propulsion, enhancing traffic management, and improving road safety, among others [5]. This technological advance demands developing effective and flexible numerical tools for controlling and designing automated vehicles [6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Anselma

2021

Energies

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Assessing the potential of advanced driver assistance systems requires developing dedicated control algorithms for controlling the longitudinal speed of automated vehicles over time. In this paper, a multiobjective off-line optimal control approach for planning the speed of the following vehicle in adaptive cruise control (ACC) driving is proposed. The implemented method relies on the principle of global optimality fostered by dynamic programming (DP) and aims to minimize propelling energy consumption and enhance passenger comfort. The powertrain model and onboard control system are integrated within the proposed car-following optimization framework. The retained ACC approach ensures that the distance between the following vehicle and the preceding vehicle is always maintained within allowed limits. The flexibility of the proposed method is demonstrated here through ease of implementation on a wide range of powertrain categories, including a conventional vehicle propelled by an internal combustion engine solely, a pure electric vehicle, a parallel P2 hybrid electric vehicle (HEV) and a power-split HEV. Moreover, different driving conditions are considered to prove the effectiveness of the proposed optimization-driven ACC approach. Obtained simulation results suggest that up to 22% energy-saving and 48% passenger comfort improvement might be achieved for the ACC-enabled vehicle compared with the preceding vehicle by implementing the proposed optimization-driven ACC approach. Engineers may adopt the proposed workflow to evaluate corresponding real-time ACC approaches and assess optimal powertrain design solutions for ACC driving.

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Improving Urban Traffic Throughput With Vehicle Platooning: Theory and Experiments

Cited by 32 publications

References 19 publications

Evaluating an Eco-Cooperative Automated Control System

Evaluating an Eco-Cooperative Automated Control System

Time-Dependent Performance Modeling for Platooning Communications at Intersection

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

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