Efficient Driving on Multilane Roads Under a Connected Vehicle Environment

Kamal, Abdus Samad; Taguchi, Shun; Yoshimura, Takeshi

doi:10.1109/tits.2016.2519526

Cited by 70 publications

(29 citation statements)

References 35 publications

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“…Other studies have also reported significant fuel consumption savings in field and simulation tests of their ACC and CACC control algorithms (see e.g. Eben Li, Li, & Wang, 2013;Kamal, Taguchi, & Yoshimura, 2016;Luo, Liu, Li, & Wang, 2010;Rios-torres & Malikopoulos, 2016;Wang, Hoogendoorn, Daamen, & van Arem, 2014) including controllers for hybrid electric vehicles (Luo, Chen, Zhang, & Li, 2015;Vajedi & Azad, 2015) In a context where there are intersections, the controller proposed by Zohdy and Rakha (2016) provides advice about the optimum course of vehicles equipped with CACC. These researchers reported fuel savings of, on average, 33%, 45%, and 11% for their system compared with the conventional intersection control approaches of a traffic signal, all-way-stop, and roundabout, respectively.…”

Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

700

383

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KEYWORDSautomated driving; first, second, and third order impacts; policy and societal implications; ripple effect ABSTRACTIn this paper, the potential effects of automated driving that are relevant to policy and society are explored, findings discussed in literature about those effects are reviewed and areas for future research are identified. The structure of our review is based on the ripple effect concept, which represents the implications of automated vehicles at three different stages: first-order (traffic, travel cost, and travel choices), second-order (vehicle ownership and sharing, location choices and land use, and transport infrastructure), and third-order (energy consumption, air pollution, safety, social equity, economy, and public health). Our review shows that first-order impacts on road capacity, fuel efficiency, emissions, and accidents risk are expected to be beneficial. The magnitude of these benefits will likely increase with the level of automation and cooperation and with the penetration rate of these systems. The synergistic effects between vehicle automation, sharing, and electrification can multiply these benefits. However, studies confirm that automated vehicles can induce additional travel demand because of more and longer vehicle trips. Potential land use changes have not been included in these estimations about excessive travel demand. Other third-order benefits on safety, economy, public health and social equity still remain unclear. Therefore, the balance between the short-term benefits and long-term impacts of vehicle automation remains an open question.

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Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

700

383

View full text Add to dashboard Cite

show abstract

“…Estimating and predicting traffic situations over time is an essential capability for sophisticated driver assistance systems and autonomous driving [10]. An efficient vehicle driving system, based on detailed anticipation of surrounding traffic with the aims of optimizing driving performance was proposed in [11]. A review of fundamental goals, development and future perspectives of driver assistance systems was provided in [12].…”

Section: A Background Informationmentioning

confidence: 99%

Ecological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles

Sajadi-Alamdari

Voos

Darouach

2020

IEEE Intell. Transport. Syst. Mag.

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Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological advanced driver assistance system can improve the longitudinal velocity regulation in a safe and energy-efficient driving strategy. The main contribution of this paper is the design of a real-time risksensitive nonlinear model predictive controller to plan the online cost-effective cruising velocity in a stochastic traffic environment. The basic idea is to measure the relevant states of the electric vehicle at runtime, and account for the road slopes, the upcoming curves, and the speed limit zones, as well as uncertainty in the preceding vehicle behaviour to determine the energy-efficient velocity profile. Closed-loop Entropic Value-at-Risk as a coherent risk measure is introduced to quantify the risk involved in the system constraints violation. The obtained simulation and field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of safe and energy-efficient states regulation and constraints satisfaction.

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“…By assuming a V2X environment, where traffic information for both the current lane and adjacent lanes are known in advance, each connected vehicle can select a sequence of lane changes over a given horizon with the aim to optimise an individual cost function (travel time, driver comfort etc.) This approach for lane selection has been used in [67,68] where an optimal strategy has been exploited to compute both the optimal lane and acceleration of the subject vehicle, over a finite horizon to minimise a cost function related to the driving efficiency and comfort. The effectiveness of including traffic information of an entire road segment for the optimal selection of the target lane has been proven numerically in [68] in which two simulation case-studies were considered.…”

Section: Lane Changementioning

confidence: 99%

“…This approach for lane selection has been used in [67,68] where an optimal strategy has been exploited to compute both the optimal lane and acceleration of the subject vehicle, over a finite horizon to minimise a cost function related to the driving efficiency and comfort. The effectiveness of including traffic information of an entire road segment for the optimal selection of the target lane has been proven numerically in [68] in which two simulation case-studies were considered. In the first scenario, shown in Figure 3, there is only one subject vehicle indicated as SV.…”

Section: Lane Changementioning

confidence: 99%

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Towards connected autonomous driving: review of use-cases

Montanaro

Dixit

Fallah

et al. 2018

Vehicle System Dynamics

140

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Connected autonomous vehicles are considered as mitigators of issues such as traffic congestion, road safety, inefficient fuel consumption, and pollutant emissions that current road transportation system suffers from. Connected Autonomous vehicles utilise communication systems to enhance the performance of autonomous vehicles and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring. The former refers to the ability to share and fuse information gathered from vehicle sensors and road infrastructures to create a better understanding of the surrounding environment while the latter enables groups of vehicles to drive in a co-ordinated way which ultimately results in a safer and more efficient driving environment. However, there is a gap in understanding how and to what extent connectivity can contribute in improving the efficiency, safety and performance of autonomous vehicles. Therefore, the aim of this paper is to investigate the potential benefits that can be achieved from connected autonomous vehicles through analysing five use-cases: (i)vehicle platooning, (ii) lane changing, (iii) intersection management, (iv) intersection management, and (v) road friction estimation. The current paper highlights that although connectivity can enhance the performance of autonomous vehicles and contribute to improvement of current transportation system performance, the level of achievable benefits depends on factors such as the penetration rate of connected vehicles, the number of autonomous vehicles, traffic scenarios, and the way of augmenting off-board information into vehicle control systems.

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Efficient Driving on Multilane Roads Under a Connected Vehicle Environment

Cited by 70 publications

References 35 publications

Policy and society related implications of automated driving: A review of literature and directions for future research

Policy and society related implications of automated driving: A review of literature and directions for future research

Ecological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles

Towards connected autonomous driving: review of use-cases

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