Current Search:  Automobile driving--Lane changing (x)

View All Items

  • CSV Spreadsheet
(1 - 2 of 2)
FIELD EXPERIMENTS ON ADAPTIVE CRUISE CONTROL (ACC) CAR FOLLOWING BEHAVIOR – IMPACT OF LANE CHANGES ON CAPACITY
Title
FIELD EXPERIMENTS ON ADAPTIVE CRUISE CONTROL (ACC) CAR FOLLOWING BEHAVIOR – IMPACT OF LANE CHANGES ON CAPACITY.
Creator
Khan, Md Mahede Hasan, Kan, David, Florida Atlantic University, Department of Civil, Environmental and Geomatics Engineering, College of Engineering and Computer Science
Abstract/Description
Today’s mainstream vehicles are partially automated via an advanced driver assistance feature (ADAS) known as Adaptive Cruise Control (ACC). ACC uses data from on-board sensors to automatically adjust speed to maintain a safe following distance with the preceding vehicle. Contrary to expectations, ICE vehicles equipped with ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. On the...
Show moreToday’s mainstream vehicles are partially automated via an advanced driver assistance feature (ADAS) known as Adaptive Cruise Control (ACC). ACC uses data from on-board sensors to automatically adjust speed to maintain a safe following distance with the preceding vehicle. Contrary to expectations, ICE vehicles equipped with ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. On the other hand, ACC equipped EVs can potentially mitigate this effect for having ready torque and quicker acceleration. However, this has not been investigated for cases when lane changers enter from the adjacent lane. ACC could respond differently under these conditions, and this car following behavior is often referred as receiving lane change car following. Carefully planned field experiments on lane change car following demonstrate that lane changes and the subsequent receiving lane change car following from ICE vehicles equipped with ACC increases the gap unless the lane changer and the target lane traffic have identical or similar speeds for internal combustion engine (ICE) vehicles and ACC in the EVs doesn’t increase the gap after lane change increasing capacity for merging compared to ICE vehicles. For ICE, this trend also correlates with the selected ACC gap, with larger gap selection resulting in longer gap following the lane change maneuver and the receiving lane change car following in response. Larger gap setting shows better results after lane change for EVs.
Show less
Date Issued
2023
PURL
http://purl.flvc.org/fau/fd/FA00014276
Subject Headings
Automated vehicles, Automobile driving--Lane changing
Format
Document (PDF)
THE EFFECT OF LANE CHANGE VOLATILITY ON REAL TIME ACCIDENT PREDICTION
Title
THE EFFECT OF LANE CHANGE VOLATILITY ON REAL TIME ACCIDENT PREDICTION.
Creator
Tesheira, Hamilton, Mahgoub, Imad, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description
According to a March 2019 publication by the National Highway Transportation Safety Administration(NHTSA), 62% of all police-reported accidents in the United States between 2011 and 2015 could have been prevented or mitigated with the use of five groups of collision avoidance technologies in passenger vehicles: (1) forward collision prevention, (2) lane keeping, (3) blind zone detection, (4) forward pedestrian impact, and (5) backing collision avoidance. These technologies work mostly by...
Show moreAccording to a March 2019 publication by the National Highway Transportation Safety Administration(NHTSA), 62% of all police-reported accidents in the United States between 2011 and 2015 could have been prevented or mitigated with the use of five groups of collision avoidance technologies in passenger vehicles: (1) forward collision prevention, (2) lane keeping, (3) blind zone detection, (4) forward pedestrian impact, and (5) backing collision avoidance. These technologies work mostly by reducing or removing the risks involved in a lane change maneuver; yet, the Broward transportation management system does not directly address these risk. Therefore, we are proposing a Machine Learning based approach to real-time accident prediction for Broward I-95 using the C5.1 Decision Tree and the Multi-Layer Perceptron Neural Network to address them. To do this, we design a new measure of volatility, Lane Change Volatility(LCV), which measures the potential for a lane change in a segment of the highway. Our research found that LCV is an important predictor of accidents in an exit zone and when considered in tandem with current system variable, such as lighting conditions, the machine learning classifiers are able to predict accidents in the exit zone with an accuracy rate of over 98%.
Show less
Date Issued
2019
PURL
http://purl.flvc.org/fau/fd/FA00013420
Subject Headings
Traffic accidents, Traffic accidents--Forecasting, Automobile driving--Lane changing, Perceptrons, Neural networks (Computer science)
Format
Document (PDF)