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.

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.

Idling fuel consumption and emissions of air pollutants at selected signalized intersections in Delhi

2019 ◽  
Vol 212 ◽  
pp. 8-21 ◽  
Author(s):  
Niraj Sharma ◽  
PV Pradeep Kumar ◽  
Rajni Dhyani ◽  
Ch Ravisekhar ◽  
K. Ravinder
Keyword(s):  
Fuel Consumption ◽  
Air Pollutants ◽  
Signalized Intersections ◽  
Fuel Consumption And Emissions

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 Delay-based Passenger Car Equivalent at Signalized Intersections in Iran

2017 ◽  
Vol 29 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Habibollah Nassiri ◽  
Sara Tabatabaie ◽  
Sina Sahebi
Keyword(s):  
Signalized Intersections ◽  
Simulation Software ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
Highway Capacity ◽  
Passenger Car ◽  
Highway Capacity Manual ◽  
Operational Characteristics ◽  
Passenger Car Equivalent ◽  
Traffic Operation

Due to their different sizes and operational characteristics, vehicles other than passenger cars have a different influence on traffic operations especially at intersections. The passenger car equivalent (PCE) is the parameter that shows how many passenger cars must be substituted for a specific heavy vehicle to represent its influence on traffic operation. PCE is commonly estimated using headway-based methods that consider the excess headway utilized by heavy vehicles. In this research, the PCE was estimated based on the delay parameter at three signalized intersections in Tehran, Iran. The data collected were traffic volume, travel time for each movement, signalization, and geometric design information. These data were analysed and three different models, one for each intersection, were constructed and calibrated using TRAF-NETSIM simulation software for unsaturated traffic conditions. PCE was estimated under different scenarios and the number of approach movements at each intersection. The results showed that for approaches with only one movement, PCE varies from 1.1 to 1.65. Similarly, for approaches with two and three movements, the PCE varies from 1.07 to 1.99 and from 0.76 to 3.6, respectively. In addition, a general model was developed for predicting PCE for intersections with all of the movements considered. The results obtained from this model showed that the average PCE of 1.5 is similar to the value recommended by the HCM (Highway Capacity Manual) 1985. However, the predicted PCE value of 1.9 for saturated threshold is closer to the PCE value of 2 which was recommended by the HCM 2000 and HCM 2010.

Safety Evaluation of the Advanced Stop Assist System in Connected Vehicle Environment

2018 ◽  
Vol 2672 (22) ◽  
pp. 47-57 ◽  
Author(s):  
Gwamaka Njobelo ◽  
Thobias Sando ◽  
Soheil Sajjadi ◽  
Enock Mtoi ◽  
Eren Erman Ozguven ◽  
...  
Keyword(s):  
Safety Evaluation ◽  
Signalized Intersections ◽  
Simulation Software ◽  
Sensitivity Analyses ◽  
Dominant Factor ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Test Bed ◽  
Dilemma Zone ◽  
Advisory Speed

Although traffic signals are installed to reduce the overall number of collisions at intersections, certain types, in particular, rear-end collisions are increasing due to signalization. One dominant factor associated with rear-end crashes is the indecisiveness of the driver, especially in the dilemma zone. An advisory system to help the driver make the stop-or-pass decision would greatly improve intersection safety. This study proposes and evaluates an Advanced Stop Assist System (ASAS) at signalized intersections by using Vehicle-to-Infrastructure (V2I) communication. The proposed system utilizes communication data, received from roadside equipment, to provide approaching vehicles with vehicle-specific advisory speed messages to prevent vehicle hard-braking at a yellow or red signal. A simulation test bed was modeled using VISSIM, a microscopic simulation software, to evaluate the effectiveness of the proposed system. The results demonstrate that at full market penetration (100% saturation of vehicles equipped with on-board communication equipment), the proposed system reduces the number of hard-braking vehicles by nearly 50%. Sensitivity analyses of market penetration rates also show a degradation in safety conditions at penetration rates lower than 40%. The results suggest that a penetration rate of at least 60% is required for the proposed system to minimize rear-end collisions and improve safety at the signalized intersections.

scholarly journals Dynamic Eco-Driving on Signalized Arterial Corridors during the Green Phase for the Connected Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiangmo Zhao ◽  
Xia Wu ◽  
Qi Xin ◽  
Kang Sun ◽  
Shaowei Yu
Keyword(s):  
Fuel Consumption ◽  
Field Experiments ◽  
Connected Vehicle ◽  
Position Information ◽  
Distance Information ◽  
Multi Stage ◽  
Rolling Optimization ◽  
The One ◽  
Optimal Approach ◽  
Fuel Consumption And Emissions

Inappropriate driving behaviours can result in additional fuel consumption and emissions. Drivers can be informed of the accurate signal phase and timing (SPaT) and distance information of the current intersection and downstream intersections via vehicle-to-everything (V2X) communications. The real-time information has been utilized to assist drivers in taking reasonable manoeuvres and gain lots of benefits on fuel consumption and emissions in some existing studies. In order to cooperatively address the optimization problem on the signalized arterial corridors, this paper presents an eco-driving optimization model considering preceding SPaT and position information. This model can be applied to pass two successive traffic signals cooperatively during green phase. In this study, a multi-stage optimal approach is proposed to minimize the fuel consumption. Field experiments are carried out for comparative analysis between the connected vehicle with speed advisory and the uninformed vehicle without speed advisory. The results indicate that the fuel saving of the connected vehicle guided by the dynamic optimization algorithm shows significant improvement. In addition, the rolling optimization among three signalized intersections is conducted and the results show that a considerable improvement can be obtained compared with the one-by-one optimization.

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