An eco-driving algorithm based on vehicle to infrastructure (V2I) communications for signalized intersections. (November 2022)
- Record Type:
- Journal Article
- Title:
- An eco-driving algorithm based on vehicle to infrastructure (V2I) communications for signalized intersections. (November 2022)
- Main Title:
- An eco-driving algorithm based on vehicle to infrastructure (V2I) communications for signalized intersections
- Authors:
- Sun, Pengyuan
Nam, Daisik
Jayakrishnan, R.
Jin, Wenlong - Abstract:
- Highlights: Based on advanced connected vehicle and vehicle-to-vehicle technologies, we propose an eco-driving algorithm for intersection control and evaluate the effectiveness of the algorithm through a set of simulations. This algorithm considers mixed traffic flow with autonomous and human-driven vehicles; we design a cooperated vehicle behavior with actuated signals with respect to various traffic congestion levels. Autonomous vehicles apply the advisory speed limit approach to enter the intersection with the minimum headway possible, while an alert for each human-driven vehicle reduces the lost time during the yellow intervals. Numerical Examples show that the proposed algorithm could increase the intersection throughput and decrease fuel consumption. Abstract: Efficient operations of traffic signals are of critical importance in urban areas, as signalized intersections prevent the smooth flow of traffic and cause delays. This paper devises an eco-driving algorithm based on connected vehicle technologies, with basic kinematic wave and car-following models. The objectives of the proposed algorithm are to increase the throughput of signal intersections and decrease fuel consumption. Specifically, we focus on a signalized intersection under mixed traffic flows with connected and autonomous vehicles (AVs) and human-driven vehicles (HVs). Through the proposed algorithm, the vehicle speeds at the intersection (i.e., the intersection control speed) and signal timings can beHighlights: Based on advanced connected vehicle and vehicle-to-vehicle technologies, we propose an eco-driving algorithm for intersection control and evaluate the effectiveness of the algorithm through a set of simulations. This algorithm considers mixed traffic flow with autonomous and human-driven vehicles; we design a cooperated vehicle behavior with actuated signals with respect to various traffic congestion levels. Autonomous vehicles apply the advisory speed limit approach to enter the intersection with the minimum headway possible, while an alert for each human-driven vehicle reduces the lost time during the yellow intervals. Numerical Examples show that the proposed algorithm could increase the intersection throughput and decrease fuel consumption. Abstract: Efficient operations of traffic signals are of critical importance in urban areas, as signalized intersections prevent the smooth flow of traffic and cause delays. This paper devises an eco-driving algorithm based on connected vehicle technologies, with basic kinematic wave and car-following models. The objectives of the proposed algorithm are to increase the throughput of signal intersections and decrease fuel consumption. Specifically, we focus on a signalized intersection under mixed traffic flows with connected and autonomous vehicles (AVs) and human-driven vehicles (HVs). Through the proposed algorithm, the vehicle speeds at the intersection (i.e., the intersection control speed) and signal timings can be adjusted in response to the real-time traffic conditions. According to the signal timing and the speed at the intersection, the algorithm estimates the time points of each vehicle entering the intersection. An advisory speed limit approach is formulated for each AV, making the vehicle enter the intersection at the allocated timing with the control speed. An onboard alert is set for each HV to stop or pass through. The algorithm is evaluated under various market penetration rates of AVs, different congestion levels, and with signal actuation. The results indicate that the eco-driving algorithm can increase the throughput and average travel speed at signalized intersections in addition to gaining fuel savings. … (more)
- Is Part Of:
- Transportation research. Volume 144(2022)
- Journal:
- Transportation research
- Issue:
- Volume 144(2022)
- Issue Display:
- Volume 144, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 144
- Issue:
- 2022
- Issue Sort Value:
- 2022-0144-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-11
- Subjects:
- Eco-driving algorithm -- Advisory speed limit -- Signalized intersection -- Connected vehicle -- Traffic throughput -- Fuel consumption
Transportation -- Periodicals
Transportation -- Technological innovations -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0968090X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.trc.2022.103876 ↗
- Languages:
- English
- ISSNs:
- 0968-090X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274620
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