Coordinated Adaptive Cruise Control System With Lane-Change Assistance

Dang, Ruina; Wang, Jianqiang; Li, Shengbo Eben; Li, Keqiang

doi:10.1109/tits.2015.2389527

Cited by 98 publications

(54 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, multi-objective ACC algorithms usually incorporate ride comfort (measured in terms of vehicle acceleration) along with safety and fuel consumption as system constraints (see e.g. Dang, Wang, Li, & Li, 2015;Li, Li, Rajamani, & Wang, 2011;Luo, Chen, Zhang, & Li, 2015;Moon, Moon, & Yi, 2009). Bellem, Schönenberg, Krems, and Schrauf (2016) suggested several maneuverspecific metrics such as acceleration, jerk, quickness, and headway distance to assess comfort of automated driving style.…”

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

725

383

View full text Add to dashboard Cite

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.

show abstract

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

725

383

View full text Add to dashboard Cite

show abstract

“…The parameters of model (5) are then estimated by nonlinear least squares from data collected on a test vehicle, at various speeds and accelerations. All the data are collected in a proving ground on level roads with homogeneous surfaces, i.e.…”

Section: Preliminaries a Vehicle Modelmentioning

confidence: 99%

“…Specifically, we use 7 datasets for a total duration of about 16 minutes; the predicted data in Fig. 1 are generated simulating model (5) with the identified parameters and the measured input torque from the initial condition to the end of the dataset.…”

Section: Preliminaries a Vehicle Modelmentioning

confidence: 99%

Safe Adaptive Cruise Control with Road Grade Preview and $\mathbf{V}2\mathbf{V}$ Communication

Firoozi

Nazari

Guanetti

et al. 2019

2019 American Control Conference (ACC)

View full text Add to dashboard Cite

We present the design of a safe Adaptive Cruise Control (ACC) which uses road grade and lead vehicle motion preview. The ACC controller is designed by using a Model Predictive Control (MPC) framework to optimize comfort, safety, energy-efficiency and speed tracking accuracy. Safety is achieved by computing a robust invariant terminal set. The paper presents a novel approach to compute such set which is less conservative than existing methods. The proposed controller ensures safe inter-vehicle spacing at all times despite changes in the road grade and uncertainty in the predicted motion of the lead vehicle. Simulation results compare the proposed controller with a controller that does not incorporate prior grade knowledge on two scenarios including car-following and autonomous intersection crossing. The results demonstrate the effectiveness of the proposed control algorithm.

show abstract

“…Existing studies related to in-vehicle navigation mainly focus on the methodology of safety measures [34,35]. For instance, Varhelyi et al considered four types of warnings, namely, speed limit warning, curve road-line warning, forward collision warning, and blind spot warning, in their user-related evaluation study of in-vehicle navigation [36].…”

Section: Introductionmentioning

confidence: 99%

Effects of In-Vehicle Navigation on Perceptual Responses and Driving Behaviours of Drivers at Tunnel Entrances: A Naturalistic Driving Study

Shi-jian

et al. 2019

Journal of Advanced Transportation

View full text Add to dashboard Cite

The perceptual responses and driving behaviours of drivers at tunnel entrances vary, which could cause interference and accidents. This study investigated the effects of in-vehicle navigation on the perceptual responses and driving behaviours and whether these effects are actually valid for safety improvement. For this purpose, a series of naturalistic driving experiments was conducted and a comparative analysis was performed considering two different experiment conditions, control condition and in-vehicle navigation condition. Under each condition, the performances of twenty drivers at seven tunnels were evaluated. The area from 200 m outside the tunnel portal to 200 m inside the tunnel portal was averagely divided into four zones. In each zone, two types of perceptual responses (visual responses and psychological responses) and driving behaviours were analysed using six indicators: number of fixations, average duration of fixations, time interval between continuous R-waves, skin conductance response, speed difference in zones, and maximum deceleration. The results showed that in-vehicle navigation significantly affects the perceptual responses and driving behaviours of drivers, and these effects varied in different zones of the tunnel entrance. Furthermore, in-vehicle navigation was found to be valid for safety improvement because beneficial changes in four of the six indicators proved to be effective at appropriate zones. The remaining two indicators, average duration of fixations and maximum deceleration, were not valid, implying that the difficulty of driving information cognition and driving comfort could not be improved by in-vehicle navigation. Moreover, a negative correlation was discovered between the number of fixations and speed difference in zones. This study provides engineers a new knowledge by extending the quantifiable approaches to the analyses of the effectiveness of the effects of in-vehicle navigation.

show abstract

Coordinated Adaptive Cruise Control System With Lane-Change Assistance

Cited by 98 publications

References 20 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

Safe Adaptive Cruise Control with Road Grade Preview and $\mathbf{V}2\mathbf{V}$ Communication

Effects of In-Vehicle Navigation on Perceptual Responses and Driving Behaviours of Drivers at Tunnel Entrances: A Naturalistic Driving Study

Contact Info

Product

Resources

About