Collision Avoidance Behavior of Unalerted Drivers Using a Front-to-Rear-End Collision Warning Display on the Iowa Driving Simulator

1997 ◽  
Vol 1573 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Jaesik Lee ◽  
Daniel V. McGehee ◽  
Thomas A. Dingus ◽  
Terry Wilson
Keyword(s):  
Collision Avoidance ◽  
Driving Simulator ◽  
Avoidance Performance ◽  
Warning System ◽  
Baseline Condition ◽  
General Motors ◽  
Collision Warning ◽  
Time To Collision ◽  
Six Degree Of Freedom ◽  
Lead Vehicle

This study investigated whether drivers who operate a vehicle equipped with a front-to-rear-end collision warning system can avoid crashing when a lead vehicle brakes at its maximum potential (e.g., -0.85 g). Drivers in the experimental condition drove a 1993 General Motors Saturn mounted on the Iowa Driving Simulator’s six-degree-of-freedom motion base. The simulator cab was equipped with a collision warning display that provided a primary auditory warning and secondary visual warning based on a time-to-collision algorithm between the subject’s vehicle and the lead vehicle. Two headway distances were tested (2.7 sec and 3.2 sec). The collision avoidance performance of subject drivers was compared to the behavior of drivers in a baseline condition where no collision warning display was present. Relative to the baseline condition, results indicate that drivers using the collision warning display ( a) showed significantly fewer crashes in the shorter headway condition, ( b) collided with the lead vehicle at significantly slower impact speeds, ( c) released the accelerator significantly faster, and ( d) had longer headways both at accelerator release and brake initiation.

scholarly journals Development Of Framework For In-Vehicle Rear-End Collision Warning System Considering Driver Characteristics

2021 ◽  
Author(s):  
Atif Mehmood
Keyword(s):  
Reaction Time ◽  
Warning System ◽  
Situational Factors ◽  
Driver Behaviour ◽  
Collision Warning ◽  
Car Following ◽  
Deceleration Rate ◽  
Car Following Model ◽  
And Gender ◽  
Lead Vehicle

Rear-end collisions are one of the serious traffic safety problems. These collisions occur when the following vehicle driver is inattentive or could not judge a potential rear-end collision situation. The use of rear-end collision warning systems (RECWS) may help drivers to avoid rear-end collision. The existing systems assumed constant driver reaction time for all driver population in their design and evaluation. They also ignore variations in driver characteristics, such as age and gender. The objectives of this thesis research are: (1) to develop reaction-time models that incorporate driver characteristics, (2) to develop a car-following simulation model that represents driver behaviour, and (3) to develop a rear-end collision warning system that accounts for driver characteristics and produces reliable collision warnings. In the human-factors study, four driver reaction-time models are developed for four different car-following scenarios: lead vehicle decelerating with normal deceleration rate, lead vehicle decelerating with emergency deceleration rate, lead vehicle stationary, and car-following acceleration regime. These models describe how the driver and situational factors affect reaction-time. The driver factors include age and gender, and the situational factors include speed and spacing between the following and lead vechiles. The developed car-following model assumes that drivers adjust their speeds based on information of both the lead and the back vehicles. The model also assumes that the driver reaction-time varies based on driver characteristics and kinematics. The proposed model represents driver behaviour in acceleration, deceleration, and steady state regimes of the car-following scenarios. Another unique feature of the model is that it explicitly considers information on the back vehicle. The model is calibrated and validated using vehicle tracking database. The driver reaction-time models and other kinematics constraints were integrated to develop a driver-sensitive rear-end collision warning system algorithm (RECWA). The developed car-following model is used to evaluate and validate the performance of the proposed RECWA. The results show that the proposed RECWA is functioning and producing reliable results. With further research and development, the proposed algorithm can be integrated into driving simulators or real vehicles to further evaluate and examine its benefits.

Development of Warning System and Driving Model for Overtaking Trucks on Two-Lane Highways

2019 ◽  
Vol 2673 (11) ◽  
pp. 1-12 ◽  
Author(s):  
Udai Hassein ◽  
Maksym Diachuk ◽  
Said Easa
Keyword(s):  
Traffic Safety ◽  
Human Error ◽  
Driving Simulator ◽  
Real Life ◽  
Warning System ◽  
Steering Control ◽  
Collision Warning ◽  
Radar Sensors ◽  
Sight Distance ◽  
The Impact

Passing collisions are one of the most serious traffic safety problems on two-lane highways. These collisions occur when a driver overestimates the available sight distance. This paper presents a framework for a passing collision warning system (PCWS) that assists drivers in avoiding passing collisions by reducing the likelihood of human error. The system uses a combination of a camera and radar sensors to identify the impeding vehicle type and to detect the opposing vehicles traveling in the left lane. The study involved the development of a steering control model providing lane-change maneuvers, the design of a driving simulator experiment that allows for the collection of data necessary to estimate passing parameters, and the elaboration of the algorithm for the PCWS based on sensor signals to detect impeding vehicles such as trucks. Simulation tests were carried out to confirm the effectiveness of the proposed PCWS algorithm. The impact of driver behavior on passing maneuvers was also investigated. Mathematical and imitation models were enhanced to implement Simulink for replications of real-life driving scenarios. The different factors that affect system accuracy were also examined.

Examining Speech-Based Auditory Alerts for Intersection Collision Warning Systems using a Driving Simulator

2018 ◽  
Vol 62 (1) ◽  
pp. 1939-1943
Author(s):  
West M. O’Brien ◽  
Xingwei Wu ◽  
Linda Ng Boyle
Keyword(s):  
Driving Simulator ◽  
Red Light ◽  
Warning System ◽  
Warning Systems ◽  
Safety Hazards ◽  
Collision Warning ◽  
Potential Safety ◽  
Auditory Alerts ◽  
Forward Collision Warning ◽  
Collision Warning Systems

Collision warning systems alert drivers of potential safety hazards. Forward collision warning (FCW) systems have been widely implemented and studied. However, intersection collision warning systems (ICWS), such as intersection movement assist (IMA), are more complex. Additional studies are needed to identify the best alert for directing the driver toward the hazard. A driving simulator study with 48 participants was conducted to examine three speech-based auditory alerts (general, directional, and command) in a simulated red light running (RLR) collision scenario. The command alert that informed the drivers to brake was the most effective in reducing the number of collisions. The post-drive questionnaire showed that drivers also rated the brake alert to be best in terms of interpretation (based on the Kruskal Wallis test). This study provides insight into the performance of different types of speech-based alerts for an intersection collision warning system and can provide guidance for future studies.

scholarly journals Fuzzy-Based Adaptive Cruise Controller with Collision Avoidance and Warning System

2013 ◽  
Vol 3 (1) ◽  
pp. 143 ◽  
Author(s):  
Wafa Batayneh ◽  
Omar Al-Araidah ◽  
Khaled Bataineh ◽  
Adnan Al-Ghasem
Keyword(s):  
Control System ◽  
Collision Avoidance ◽  
Adaptive Cruise Control ◽  
Warning System ◽  
Cruise Control ◽  
Collision Warning ◽  
Adaptive Cruise Control System ◽  
Cruise Control System ◽  
Control Scheme ◽  
Simulation Results

The paper presents a Fuzzy-based adaptive cruise control system with collision avoidance and collision warning (ACC/CA/CW). The proposed control scheme aims to improve driver's comfort while keeping him/her safe by avoiding possible collisions. Depending on inputs from both the driver and the installed sensors, the controller accelerates/decelerates the vehicle to keep its speed at the desired limit. In case of a possible collision, the controller decelerates (accelerates) the vehicle to prevent possible crash with the vehicle ahead (behind). Moreover, the controller issues visual and/or audio alerts for the driver in order to warn him/her in case of the need for applying an uncomfortable deceleration level and/or to warn the driver for risky situations where he/she might need to change the lane. Simulation results illustrate the robustness of the proposed system over various ranges of inputs.

Research on Driving Simulator in early Warning System of Vehicle Rear-End Collisions

2013 ◽  
Vol 380-384 ◽  
pp. 581-585
Author(s):  
Jing Ming Yan
Keyword(s):  
Real Time ◽  
Road Safety ◽  
Driver Assistance System ◽  
Driving Simulator ◽  
Warning System ◽  
Driver Assistance ◽  
Safe Distance ◽  
Collision Warning ◽  
Safety Technology ◽  
True Condition

Road safety has drawn wide attention from the whole society in recent years. The system of collision warning and anti-collision as an emerging vehicle safety technology can effectively help drivers avoid rear-end accident. This paper uses driver assistance system to analogously simulate true condition of driving and road. By real-time monitoring safe distance between two vehicles under the condition of following, this paper optimizes and adjusts the existing simulator. Drivers can avoid some untimely happening or unnecessary warning through improved and optimized simulator, which provides crucial technical conditions for producing more controlled and real-time interactive simulator.

Normal and Hard Braking Behavior at Stop Signs and Traffic Signals

2005 ◽  
Vol 49 (22) ◽  
pp. 1897-1901 ◽  
Author(s):  
Suzanne E. Lee ◽  
Sarah B. Brown ◽  
Miguel A. Perez ◽  
Zachary R. Doerzaph ◽  
Vicki L. Neale
Keyword(s):  
Collision Avoidance ◽  
Warning System ◽  
Traffic Signals ◽  
Performance Tests ◽  
Algorithm Development ◽  
Intersection Problem ◽  
Collision Warning ◽  
And Performance ◽  
Forward Collision Warning

A testbed intersection violation warning system was developed to address the problem of intersection crashes. The effectiveness of such systems is fundamentally dependent on the driver-braking model used to decide if a warning should be issued to the driver. If the model is unrealistic, drivers can either be annoyed due to assumed braking levels that are too low, or can be warned too late if braking expectations are too high. Initial algorithm development relied on data from the Collision Avoidance Metrics Partnership (CAMP) Forward Collision Warning (FCW) project. However, it was unknown whether the CAMP data (collected in the presence of stopped lead vehicles) would be applicable to the intersection problem (e.g., will drivers respond similarly to red traffic signals and stopped lead vehicles). Braking profile and performance tests were thus conducted to determine the applicability of the CAMP FCW results to the intersection violation warning.

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