scholarly journals Impact of Partial Penetrations of Connected and Automated Vehicles on Fuel Consumption and Traffic Flow

2018 ◽  
Vol 3 (4) ◽  
pp. 453-462 ◽  
Author(s):  
Jackeline Rios-Torres ◽  
Andreas A. Malikopoulos
Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6533
Author(s):  
A. S. M. Bakibillah ◽  
Md Abdus Samad Kamal ◽  
Chee Pin Tan ◽  
Susilawati Susilawati ◽  
Tomohisa Hayakawa ◽  
...  

Traditional uncoordinated traffic flows in a roundabout can lead to severe traffic congestion, travel delay, and the increased fuel consumption of vehicles. An interesting way to mitigate this would be through cooperative control of connected and automated vehicles (CAVs). In this paper, we propose a novel solution, which is a roundabout control system (RCS), for CAVs to attain smooth and safe traffic flows. The RCS is essentially a bi-level framework, consisting of higher and lower levels of control, where in the higher level, vehicles in the entry lane approaching the roundabout will be made to form clusters based on traffic flow volume, and in the lower level, the vehicles’ optimal sequences and roundabout merging times are calculated by solving a combinatorial optimization problem using a receding horizon control (RHC) approach. The proposed RCS aims to minimize the total time taken for all approaching vehicles to enter the roundabout, whilst minimally affecting the movement of circulating vehicles. Our developed strategy ensures fast optimization, and can be implemented in real-time. Using microscopic simulations, we demonstrate the effectiveness of the RCS, and compare it to the current traditional roundabout system (TRS) for various traffic flow scenarios. From the results, we can conclude that the proposed RCS produces significant improvement in traffic flow performance, in particular for the average velocity, average fuel consumption, and average travel time in the roundabout.


2012 ◽  
Vol 20 (3) ◽  
pp. 203-224 ◽  
Author(s):  
Shon R. Grabbe ◽  
Banavar Sridhar ◽  
Avijit Mukherjee ◽  
Alexander Morando

2021 ◽  
Vol 127 ◽  
pp. 103126
Author(s):  
Hari Hara Sharan Nagalur Subraveti ◽  
Anupam Srivastava ◽  
Soyoung Ahn ◽  
Victor L. Knoop ◽  
Bart van Arem

2017 ◽  
Vol 31 (34) ◽  
pp. 1750324 ◽  
Author(s):  
Hong Xiao ◽  
Hai-Jun Huang ◽  
Tie-Qiao Tang

Electric vehicle (EV) has become a potential traffic tool, which has attracted researchers to explore various traffic phenomena caused by EV (e.g. congestion, electricity consumption, etc.). In this paper, we study the energy consumption (including the fuel consumption and the electricity consumption) and emissions of heterogeneous traffic flow (that consists of the traditional vehicle (TV) and EV) under three traffic situations (i.e. uniform flow, shock and rarefaction waves, and a small perturbation) from the perspective of macro traffic flow. The numerical results show that the proportion of electric vehicular flow has great effects on the TV’s fuel consumption and emissions and the EV’s electricity consumption, i.e. the fuel consumption and emissions decrease while the electricity consumption increases with the increase of the proportion of electric vehicular flow. The results can help us better understand the energy consumption and emissions of the heterogeneous traffic flow consisting of TV and EV.


2020 ◽  
Vol 12 (8) ◽  
pp. 3206
Author(s):  
Roni Utriainen ◽  
Markus Pöllänen

Interaction between drivers and pedestrians enables pedestrians to cross the street without conflicts. When highly automated vehicles (HAVs) become prevalent, interaction will change. Although HAVs manage to identify pedestrians, they may not be able to assess pedestrians’ intentions. This study discusses two different ambitions: Prioritizing pedestrian safety and prioritizing efficient traffic flow; and how these two affect the possibilities to avoid fatal crashes between pedestrians and passenger cars. HAVs’ hypothetical possibilities to avoid different crash scenarios are evaluated based on 40 in-depth investigated fatal pedestrian crashes, which occurred with manually-driven cars in Finland in 2014–2016. When HAVs prioritize pedestrian safety, they decrease speed near pedestrians as a precaution which affects traffic flow due to frequent decelerations. When HAVs prioritize efficient traffic flow, they only decelerate, when pedestrians are in a collision course. The study shows that neither of these approaches can be applied in all traffic environments, and all of the studied crashes would not likely be avoidable with HAVs even when prioritizing pedestrian safety. The high expectations of HAVs’ safety benefits may not be realized, and in addition to safety and traffic flow, there are many other objectives in traffic which need to be considered.


2017 ◽  
Vol 2622 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Da Yang ◽  
Xiaoping Qiu ◽  
Lina Ma ◽  
Danhong Wu ◽  
Liling Zhu ◽  
...  

In recent years, automated vehicles have been developing rapidly, and some automated vehicles have begun to drive on highways. The market share of automated vehicles is expected to increase and will greatly affect traffic flow characteristics. This paper focuses on the mixed traffic flow of manual and automated vehicles. The study improves the existing cellular automaton model to capture the differences between manual vehicles and automated vehicles. Computer simulations are employed to analyze the characteristic variations in the mixed traffic flow under different automated vehicle proportions, lane change probabilities, and reaction times. Several new conclusions are drawn in the paper. First, with the increment of the proportion of automated vehicles, freeway capacity increases; the capacity increment is more significant for single-lane traffic than for two-lane traffic. Second, for single-lane traffic flow, reducing the reaction time of the automated vehicle can significantly improve road traffic capacity—as much as doubling it—and reaction time reduction has no obvious effect on the capacity of the two-lane traffic. Third, with the proportion increment of automated vehicles, lane change frequency reduces significantly. Fourth, when the density is 15 < ρ < 55 vehicles/km, the addition of 20% automated vehicles to a traffic flow that consisted of only manual vehicles can decrease congestion by up to 16.7%.


Author(s):  
Simeon Calvert ◽  
Hani Mahmassani ◽  
Jan-Niklas Meier ◽  
Pravin Varaiya ◽  
Samer Hamdar ◽  
...  

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