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

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Peng Chen ◽  
Cong Yan ◽  
Jian Sun ◽  
Yunpeng Wang ◽  
Shenyang Chen ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Driving Simulator ◽  
Fuel Efficiency ◽  
Signalized Intersections ◽  
Specific Power ◽  
Programming Approach ◽  
Time Signal ◽  
Connected Vehicle ◽  
Dynamic Programming Approach ◽  
Driving Speed

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 CO2 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 CO2 emissions.

scholarly journals Trajectory Planning Method for Mixed Vehicles Considering Traffic Stability and Fuel Consumption at the Signalized Intersection

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shan Fang ◽  
Lan Yang ◽  
Tianqi Wang ◽  
Shoucai Jing
Keyword(s):  
Fuel Consumption ◽  
Trajectory Planning ◽  
Signalized Intersections ◽  
Planning Method ◽  
Signalized Intersection ◽  
Driver Model ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Traffic Lights ◽  
Trigonometric Model

Traffic lights force vehicles to stop frequently at signalized intersections, which leads to excessive fuel consumption, higher emissions, and travel delays. To address these issues, this study develops a trajectory planning method for mixed vehicles at signalized intersections. First, we use the intelligent driver car-following model to analyze the string stability of traffic flow upstream of the intersection. Second, we propose a mixed-vehicle trajectory planning method based on a trigonometric model that considers prefixed traffic signals. The proposed method employs the proportional-integral-derivative (PID) model controller to simulate the trajectory when connected vehicles (equipped with internet access) follow the optimal advisory speed. Essentially, only connected vehicle trajectories need to be controlled because normal vehicles simply follow the connected vehicles according to the Intelligent Driver Model (IDM). The IDM model aims to minimize traffic oscillation and ensure that all vehicles pass the signalized intersection without stopping. The results of a MATLAB simulation indicate that the proposed method can reduce fuel consumption and NOx, HC, CO2, and CO concentrations by 17%, 22.8%, 17.8%, 17%, and 16.9% respectively when the connected vehicle market penetration is 50 percent.

scholarly journals Environmental Impact of Freight Signal Priority with Connected Trucks

2019 ◽  
Vol 11 (23) ◽  
pp. 6819
Author(s):  
Sangjun Park ◽  
Kyoungho Ahn ◽  
Hesham A. Rakha
Keyword(s):  
Fuel Consumption ◽  
Signalized Intersections ◽  
Simulation Software ◽  
Traffic Signal ◽  
Connected Vehicle ◽  
Transit Signal Priority ◽  
Passenger Cars ◽  
Microscopic Traffic Simulation ◽  
Operational Technique ◽  
Fuel Consumption And Emissions

Traffic signal priority is an operational technique employed for the smooth progression of a specific type of vehicle at signalized intersections. Transit signal priority is the most common type of traffic signal priority, and it has been researched extensively. Conversely, the impacts of freight signal priority (FSP) has not been widely investigated. Hence, this study aims to evaluate the energy and environmental impacts of FSP under connected vehicle environment by utilizing a simulation testbed developed for the multi-modal intelligent transportation signal system. The simulation platform consists of VISSIM microscopic traffic simulation software, a signal request messages distributor program, an RSE module, and an Econolite ASC/3 traffic controller emulator. The MOVES model was employed to estimate the vehicle fuel consumption and emissions. The simulation study revealed that the implementation of FSP significantly reduced the fuel consumption and emissions of connected trucks and general passenger cars; the network-wide fuel consumption was reduced by 11.8%, and the CO2, HC, CO, and NOX emissions by 11.8%, 28.3%, 24.8%, and 25.9%, respectively. However, the fuel consumption and emissions of the side-street vehicles increased substantially due to the reduced green signal times on the side streets, especially in the high truck composition scenario.

Application of Box-Behnken Analysis on the Optimisation of Air Intake System for a Naturally Aspirated Engine

2020 ◽  
Vol 17 (2) ◽  
pp. 8029-8042
Author(s):  
N.S. Mustafa ◽  
N.H.A. Ngadiman ◽  
M.A. Abas ◽  
M.Y. Noordin
Keyword(s):  
Fuel Consumption ◽  
Fuel Efficiency ◽  
Engine Performance ◽  
Fuel Price ◽  
Design Expert ◽  
Intake System ◽  
Analysis Technique ◽  
System Components ◽  
Air Intake ◽  
High Influence

Fuel price crisis has caused people to demand a car that is having a low fuel consumption without compromising the engine performance. Designing a naturally aspirated engine which can enhance engine performance and fuel efficiency requires optimisation processes on air intake system components. Hence, this study intends to carry out the optimisation process on the air intake system and airbox geometry. The parameters that have high influence on the design of an airbox geometry was determined by using AVL Boost software which simulated the automobile engine. The optimisation of the parameters was done by using Design Expert which adopted the Box-Behnken analysis technique. The result that was obtained from the study are optimised diameter of inlet/snorkel, volume of airbox, diameter of throttle body and length of intake runner are 81.07 mm, 1.04 L, 44.63 mm and 425 mm, respectively. By using these parameters values, the maximum engine performance and minimum fuel consumption are 93.3732 Nm and 21.3695×10-4 kg/s, respectively. This study has fully accomplished its aim to determine the significant parameters that influenced the performance of airbox and optimised the parameters so that a high engine performance and fuel efficiency can be produced. The success of this study can contribute to a better design of an airbox.

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