scholarly journals Influence of Variable Speed Limit Control on Fuel and Electric Energy Consumption, and Exhaust Gas Emissions in Mixed Traffic Flows

2022 ◽  
Vol 14 (2) ◽  
pp. 932
Author(s):  
Filip Vrbanić ◽  
Mladen Miletić ◽  
Leo Tišljarić ◽  
Edouard Ivanjko

Modern urban mobility needs new solutions to resolve high-complexity demands on urban traffic-control systems, including reducing congestion, fuel and energy consumption, and exhaust gas emissions. One example is urban motorways as key segments of the urban traffic network that do not achieve a satisfactory level of service to serve the increasing traffic demand. Another complex need arises by introducing the connected and autonomous vehicles (CAVs) and accompanying additional challenges that modern control systems must cope with. This study addresses the problem of decreasing the negative environmental aspects of traffic, which includes reducing congestion, fuel and energy consumption, and exhaust gas emissions. We applied a variable speed limit (VSL) based on Q-Learning that utilizes electric CAVs as speed-limit actuators in the control loop. The Q-Learning algorithm was combined with the two-step temporal difference target to increase the algorithm’s effectiveness for learning the VSL control policy for mixed traffic flows. We analyzed two different optimization criteria: total time spent on all vehicles in the traffic network and total energy consumption. Various mixed traffic flow scenarios were addressed with varying CAV penetration rates, and the obtained results were compared with a baseline no-control scenario and a rule-based VSL. The data about vehicle-emission class and the share of gasoline and diesel human-driven vehicles were taken from the actual data from the Croatian Bureau of Statistics. The obtained results show that Q-Learning-based VSL can learn the control policy and improve the macroscopic traffic parameters and total energy consumption and can reduce exhaust gas emissions for different electric CAV penetration rates. The results are most apparent in cases with low CAV penetration rates. Additionally, the results indicate that for the analyzed traffic demand, the increase in the CAV penetration rate alleviates the need to impose VSL control on an urban motorway.

2021 ◽  
Vol 11 (6) ◽  
pp. 2574
Author(s):  
Filip Vrbanić ◽  
Edouard Ivanjko ◽  
Krešimir Kušić ◽  
Dino Čakija

The trend of increasing traffic demand is causing congestion on existing urban roads, including urban motorways, resulting in a decrease in Level of Service (LoS) and safety, and an increase in fuel consumption. Lack of space and non-compliance with cities’ sustainable urban plans prevent the expansion of new transport infrastructure in some urban areas. To alleviate the aforementioned problems, appropriate solutions come from the domain of Intelligent Transportation Systems by implementing traffic control services. Those services include Variable Speed Limit (VSL) and Ramp Metering (RM) for urban motorways. VSL reduces the speed of incoming vehicles to a bottleneck area, and RM limits the inflow through on-ramps. In addition, with the increasing development of Autonomous Vehicles (AVs) and Connected AVs (CAVs), new opportunities for traffic control are emerging. VSL and RM can reduce traffic congestion on urban motorways, especially so in the case of mixed traffic flows where AVs and CAVs can fully comply with the control system output. Currently, there is no existing overview of control algorithms and applications for VSL and RM in mixed traffic flows. Therefore, we present a comprehensive survey of VSL and RM control algorithms including the most recent reinforcement learning-based approaches. Best practices for mixed traffic flow control are summarized and new viewpoints and future research directions are presented, including an overview of the currently open research questions.


Author(s):  
T. O. Monz ◽  
M. Stöhr ◽  
W. O’Loughlin ◽  
J. Zanger ◽  
M. Hohloch ◽  
...  

A swirl stabilized MGT combustor (Turbec T100) was operated with natural gas and was experimentally characterized in two test rigs, a pressurized and optically accessible MGT test rig and an atmospheric combustor test rig. For the detailed characterization of the combustion processes, planar OH-PLIF and simultaneous 3D-stereo PIV measurements were performed in the atmospheric combustor test rig. Flow fields, reaction zones and exhaust gas emissions are reported for a range of pressure scaled MGT load points. Parameter studies on combustor inlet conditions (e.g. air preheating temperature, air and fuel mass flow rates and fuel split) were conducted in the atmospheric combustor test rig. From the parameters studies the fuel split between the pilot and the main stage and the air preheating temperature were found to have the biggest impact on the flame shape, flame stabilization and exhaust gas emissions. The measurements of the ATM test rig are compared with measurements of the pressurized MGT test rig with and without an optically accessible combustion chamber. Opened and closed conical flame and flow pattern were found in both test rigs. Reasons for the two flame and flow pattern are supposed to be the interaction of pilot stage combustion and flow field and the interaction of the dilution air with the combustion and the flow field. The results are discussed and compared with repect to a transferability of combustion characteristics from the ATM test rig to the MGT test rigs.


2016 ◽  
Author(s):  
Kristin Götz ◽  
Barbara Fey ◽  
Anja Singer ◽  
Juergen Krahl ◽  
Jürgen Bünger ◽  
...  

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