Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time

Asadi, Behrang; Vahidi, Ardalan

doi:10.1109/tcst.2010.2047860

Cited by 614 publications

(315 citation statements)

References 12 publications

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“…In this study, the speed limit, acceleration and deceleration limits, and the minimum safe following distance are imposed as pointwise-in-time inequality constraints [21]. These constraints are effective over the future prediction horizon.…”

Section: Objective Function and Constraintsmentioning

confidence: 99%

“…However, it was argued that lowering acceleration/deceleration levels does not necessarily indicate reducing fuel consumption. Asadi and Vahidi [21] used upcoming traffic signal information within the vehicle's adaptive cruise control system to reduce idle time at stop lights and fuel consumption. The control objectives were set as timely arrival at green light with minimal use of braking, maintaining safe distance between vehicles, and cruising at or near set speed.…”

Section: Introductionmentioning

confidence: 99%

“…In the aforementioned studies, the goal of reducing fuel consumption was usually transformed into simple functions of acceleration/deceleration rates [20,22] or the time of arrival at the intersection [10,21,23] (Sun and Henry, 2015; Wu et al, 2015a, 2015b). None of these models used an explicit objective function to minimize the total fuel consumption.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic Eco-Driving Speed Guidance at Signalized Intersections: Multivehicle Driving Simulator Based Experimental Study

Chen

Yan

Sun

et al. 2018

Journal of Advanced Transportation

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Variations in vehicle fuel consumption and gas emissions are usually associated with changes in cruise speed and the aggressiveness of drivers' acceleration/deceleration, especially at traffic signals. In an attempt to enhance vehicle fuel efficiency on arterials, this study developed a dynamic eco-driving speed guidance strategy (DESGS) using real-time signal timing and vehicle positioning information in a connected vehicle (CV) environment. DESGS mainly aims to optimize the fuel/emission speed profiles for vehicles approaching signalized intersections. An optimization-based rolling horizon and a dynamic programming approach were proposed to track the optimal guided velocity for individual vehicles along the travel segment. In addition, a vehicle specific power (VSP) based approach was integrated into DESGS to estimate the fuel consumption and CO 2 emissions. To evaluate the effectiveness of the overall strategy, 15 experienced drivers were recruited to participate in interactive speed guidance experiments using multivehicle driving simulators. It was found that compared to vehicles without speed guidance, those with DESGS had a significantly reduced number of stops and approximately 25% less fuel consumption and CO 2 emissions.

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Section: Objective Function and Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Eco-Driving Speed Guidance at Signalized Intersections: Multivehicle Driving Simulator Based Experimental Study

Chen

Yan

Sun

et al. 2018

Journal of Advanced Transportation

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“…Studies have shown that active safety systems, such as (adaptive) cruise control, electronic stability control or lane keeping, which are already on the automotive market, can improve safety by decreasing the number of traffic accidents (Rieger et al, 2005). More specifically, Adaptive Cruise Control (ACC) as described in (ISO, 2010), can improve traffic flow and driving comfort Ioannou and Chien, 1993); in addition to improving traffic flow and comfort, ACC systems can also reduce fuel consumption (Alam et al, 2010) and trip time (Asadi and Vadihi, 2011). An extensive survey on ACC systems can be found in (Vahidi and Eskandarian, 2003) and (Xiao and Gao, 2010).…”

Section: Introductionmentioning

confidence: 99%

Adaptive Cruise Control with Safety Guarantees for Autonomous Vehicles

Magdici

Althoff

2017

IFAC-PapersOnLine

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This paper addresses the problem of following a vehicle with varying acceleration in a comfortable and safe manner. Our architecture consists of a nominal controller (here: model predictive control) and a safety controller. Although model predictive control attempts to keep a safe distance, it cannot formally guarantee it, due to the assumptions on the behavior of the leading vehicle. We address this problem by holding a formally verified safety controller available. Our novel mechanism gradually engages the safety maneuver since most critical situations resolve quickly. The overall approach is evaluated against real traffic data. The results show good position and velocity tracking performance, while safety and comfort are guaranteed.

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“…The aim of these systems is to control the car's actuators through sensor systems to prevent or mitigate collisions. For example, radar [2], vision-based [3], and differential global positioning system (DGPS) [4] technologies have been used to detect any leading vehicle so as to perform adaptive cruise control (ACC)-a now well-proven technique consisting of speed control to maintain a pre-defined time gap with a leading vehicle. Likewise; these technologies have been used for pre-crash systems development.…”

Section: Introductionmentioning

confidence: 99%

Traffic jam driving with NMV avoidance

Milanés

Alonso

Villagrá

et al. 2012

Mechanical Systems and Signal Processing

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In recent years, the development of advanced driver assistance systems (ADAS) -mainly based on lidar and cameras -has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations-in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuatorsbrake and throttle pedals -were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging.

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Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time

Cited by 614 publications

References 12 publications

Dynamic Eco-Driving Speed Guidance at Signalized Intersections: Multivehicle Driving Simulator Based Experimental Study

Dynamic Eco-Driving Speed Guidance at Signalized Intersections: Multivehicle Driving Simulator Based Experimental Study

Adaptive Cruise Control with Safety Guarantees for Autonomous Vehicles

Traffic jam driving with NMV avoidance

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