An efficient cooperative lane-changing algorithm for sensor- and communication-enabled automated vehicles

Awal, Tanveer; Murshed, Manzur; Ali, Mortuza

doi:10.1109/ivs.2015.7225900

Cited by 25 publications

(17 citation statements)

References 18 publications

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“…In (Scarinci et al, 2017) a cooperative merging assistant is introduced to facilitate merging on ramp traffic and relying on vehicle connectivity. The simulations in (Awal et al, 2015) show improvement with respect to MOBIL, in terms of merge time and rate, wait time, fuel consumption, average velocity, and flow at the cost of slightly increased travel time for main road vehicles. In (Scarinci et al, 2015) a merging assistant system that relies on vehicle cooperation, reduces the number of "latemerging" vehicles and subsequent likelihood of flow break-downs.…”

Section: Cooperative Lane Change and Mergementioning

confidence: 93%

“…However cooperative lane selection and merging for CAVs has only been recently discussed. In (Awal et al, 2015) a cooperative lane-changing algorithm is simulated that considers follower vehicles in current and target lanes when making a lane change decision. In (Scarinci et al, 2017) a cooperative merging assistant is introduced to facilitate merging on ramp traffic and relying on vehicle connectivity.…”

Section: Cooperative Lane Change and Mergementioning

confidence: 99%

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Energy saving potentials of connected and automated vehicles

Vahidi

Sciarretta

2018

Transportation Research Part C: Emerging Technologies

416

126

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Connected and automated vehicles (CAV) are marketed for their increased safety, driving comfort, and time saving potential. With much easier access to information, increased processing power, and precision control, they also offer unprecedented opportunities for energy efficient driving. This paper is an attempt to highlight the energy saving potential of connected and automated vehicles based on first principles of motion, optimal control theory, and a review of the vast but scattered eco-driving literature. We explain that connectivity to other vehicles and infrastructure allows better anticipation of upcoming events, such as hills, curves, slow traffic, state of traffic signals, and movement of neighboring vehicles. Automation allows vehicles to adjust their motion more precisely in anticipation of upcoming events, and save energy. Opportunities for cooperative driving could further increase energy efficiency of a group of vehicles by allowing them to move in a coordinated manner. Energy efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles.

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Section: Cooperative Lane Change and Mergementioning

confidence: 93%

Section: Cooperative Lane Change and Mergementioning

confidence: 99%

Energy saving potentials of connected and automated vehicles

Vahidi

Sciarretta

2018

Transportation Research Part C: Emerging Technologies

416

126

View full text Add to dashboard Cite

show abstract

“…Only a few studies have evaluated the energy savings of cooperative lane change and merge. One of them is presented by Awal et al (2015). The authors propose a cooperative strategy that considers vehicles in current and target lanes during lane changing phases.…”

Section: Lane Change and Mergementioning

confidence: 99%

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Othman

Nunzio

Sciarretta

et al. 2021

Handbook of Climate Change Mitigation and Adaptation

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In the member countries of the Organization for Economic Cooperation and Development (OECD), projections show that the improved energy efficiency in transportation may lead to a net decline of about 2% in energy use until 2040, thus outpacing the predicted increase of vehicle-miles traveled (VMT). However, in OECD-Europe, transportation still represents the biggest source of carbon emissions, contributing by about 25% to the total CO2 emissions, with cars and vans representing more than two thirds of this share. The situation is even more alarming in non-OECD countries, where the transportation energy demand is expected to rise by 64% until 2040. The shift that we are witnessing toward the adoption of connected and automated vehicles (CAVs) is going to be perhaps, the most disruptive since the early days of automobiles and could revolutionize movement of people and goods. This level of connectivity and autonomy will transform transportation in several dimensions with important societal and economic impacts: improved safety, increased comfort, time saving potential, and more efficient road utilization are among the most widely discussed positive impacts of CAVs. However, the potential energy efficiency benefits of these technologies remain uncertain. From a single-vehicle efficiency perspective, research suggests that lightweight, low-speed, autonomous vehicles have the potential to achieve fuel economy an order of magnitude higher than current cars. Yet, at system-wide level, current estimates suggest that the total energy consumption impacts can range from a 90% decrease to a 200% increase in fuel consumption as compared to a projected 2050 baseline energy consumption. The paradigm that traffic congestion mitigation should reduce CO2 emissions is yet to be proved. Therefore, interest in transportation regulation problems with explicit environmental considerations is growing. This work takes a more in-depth look at increased opportunities for energy-efficient driving with energy-oriented traffic management and CAVs deployment. In particular, the focus will be put on the road traffic control strategies in urban networks using connectivity to enable variable speed limits and traffic light adaptive control, as well as the energy-saving opportunities that arise for individual CAVs by anticipating future road geometry, traffic conditions, and interactions with neighboring vehicles.

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“…VI-A-VI-B, is given by Theorems 1-2, respectively. Theorem 1: Consider the OCP with constraints (11f)-(11i) and cost function (12). The set K lat (t) can be obtained by the following control policies of vehicles V 1 ,V 2 and V 3 :…”

Section: Solution Of the Optimal Control Problemmentioning

confidence: 99%

“…Several approaches have been presented which address specific traffic situations, e.g. the coordination of multiple vehicles at road intersections [8]- [11], lane-changing and merging [12], and lane closures [13]. Furthermore, decision-making techniques based on algorithms from game theory, e.g.…”

Section: Introductionmentioning

confidence: 99%

Driving strategy selection for cooperative vehicles using maneuver templates

Manzinger¹,

Leibold

Althoff

2017

2017 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-We introduce a novel concept based on maneuver templates, which are formalized collaborative maneuvers, to select cooperative driving strategies. The approach is based on the exclusion principle, where we derive provable conditions to discard unsafe cooperative maneuvers for a given traffic situation. We thereby consider the full action set of all cooperative vehicles and do not discretize the action space. We demonstrate the applicability of our approach with numerical examples.

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An efficient cooperative lane-changing algorithm for sensor- and communication-enabled automated vehicles

Cited by 25 publications

References 18 publications

Energy saving potentials of connected and automated vehicles

Energy saving potentials of connected and automated vehicles

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Driving strategy selection for cooperative vehicles using maneuver templates

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