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.

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.

scholarly journals A NEW CAR-FOLLOWING MODEL CONSIDERING ACCELERATION OF LEAD VEHICLE

Transport ◽  
2014 ◽  
Vol 31 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Bingrong Sun ◽  
Na Wu ◽  
Ying-En Ge ◽  
Taewan Kim ◽  
Hongjun Michael Zhang
Keyword(s):  
General Motors ◽  
Weighted Sum ◽  
Relative Speed ◽  
New Model ◽  
Car Following ◽  
Stimulus Response ◽  
The Road ◽  
Car Following Model ◽  
On The Road ◽  
Lead Vehicle

For decades, the general motors (gm) car following model has received a great deal of attention and provided a basic framework to describe the interactions between vehicles on the road. It is based on the stimulus-response assumption that the following vehicle responds to the relative speed between the lead vehicle and itself. However, some of the empirical findings show that the assumption of gm model is not always true and need some modification. For example, the acceleration of the following vehicle is very sensitive to the sign of the relative speed and because of no term in the model that directly represents the leader’s acceleration, the follower’s response to the leader’s acceleration can be retarded. This paper offers a new car-following model that can be considered as a variant of the gm model that can better capture car following behavior. The new model treats the follower’s acceleration as a proportion of a weighted sum of the leader’s acceleration and the relative speed between the lead and following vehicles. This paper compares the new model with the original gm model numerically and the characteristics of the new parameters in the model are investigated. It is also shown that the new model overcomes the shortcomings of the original gm model identified in this paper and gives us more instruments to capture the real-world car-following behavior.

scholarly journals A Forward-Collision Warning System for Electric Vehicles: Experimental Validation in Virtual and Real Environment

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4872
Author(s):  
Nicola Albarella ◽  
Francesco Masuccio ◽  
Luigi Novella ◽  
Manuela Tufo ◽  
Giovanni Fiengo
Keyword(s):  
Electric Vehicles ◽  
Low Cost ◽  
Warning System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driver Behaviour ◽  
Collision Warning ◽  
Fast Development ◽  
Assistance Systems ◽  
Forward Collision Warning

Driver behaviour and distraction have been identified as the main causes of rear end collisions. However a promptly issued warning can reduce the severity of crashes, if not prevent them completely. This paper proposes a Forward Collision Warning System (FCW) based on information coming from a low cost forward monocular camera for low end electric vehicles. The system resorts to a Convolutional Neural Network (CNN) and does not require the reconstruction of a complete 3D model of the surrounding environment. Moreover a closed-loop simulation platform is proposed, which enables the fast development and testing of the FCW and other Advanced Driver Assistance Systems (ADAS). The system is then deployed on embedded hardware and experimentally validated on a test track.

Incorporating Instantaneous Reaction Delay in Car-Following Models: A Hybrid Approach

2021 ◽  
pp. 036119812110152
Author(s):  
Mehdi Rafati Fard ◽  
Saeed Rahmani ◽  
Afshin Shariat Mohaymany
Keyword(s):  
Reaction Time ◽  
Road Safety ◽  
Statistical Tests ◽  
Hybrid Approach ◽  
Car Following ◽  
Driving Behaviors ◽  
Proposed Model ◽  
Traffic Performance ◽  
Fixed Parameter ◽  
Car Following Model

Car-following is considered as one of the most prevalent fundamental driving behaviors that substantially influences traffic performance as well as road safety and capacity. Drivers’ car-following behavior is affected by numerous factors. However, in practice, very few of these factors have been scrutinized, because of their latent essence and unavailability of appropriate data. Owing to its importance, drivers’ reaction time has attracted the attention of many researchers; nevertheless, it is considered as a fixed parameter in car-following models, which is far from reality. To take the variability of drivers’ reaction time into account, a flexible hybrid approach has been suggested in the present study. In the proposed structure, in the first step, the desirable acceleration of the driver is estimated by applying an equation-based car-following model. In the next step, the driver’s reaction delay in applying the calculated acceleration is estimated by an artificial neural network. The corresponding parameters are jointly estimated by applying an estimated distribution algorithm. Statistical tests indicate better performance of the hybrid model, which considers the variations of the driver’s reaction time, compared with a traditional model with fixed reaction time. Furthermore, the cross-validation results indicate better generalizability and transferability of the proposed model in action.

scholarly journals Subcritical Hopf bifurcations in a car-following model with reaction-time delay

2006 ◽  
Vol 462 (2073) ◽  
pp. 2643-2670 ◽  
Author(s):  
Gábor Orosz ◽  
Gábor Stépán
Keyword(s):  
Hopf Bifurcation ◽  
Reaction Time ◽  
Time Delay ◽  
Hopf Bifurcations ◽  
Highway Traffic ◽  
Subcritical Case ◽  
Car Following ◽  
Car Following Model ◽  
Flow Equilibrium ◽  
The Stability

A nonlinear car-following model of highway traffic is considered, which includes the reaction-time delay of drivers. Linear stability analysis shows that the uniform flow equilibrium of the system loses its stability via Hopf bifurcations and thus oscillations can appear. The stability and amplitudes of the oscillations are determined with the help of normal-form calculations of the Hopf bifurcation that also handles the essential translational symmetry of the system. We show that the subcritical case of the Hopf bifurcation occurs robustly, which indicates the possibility of bistability. We also show how these oscillations lead to spatial wave formation as can be observed in real-world traffic flows.

scholarly journals Experimental Analysis of Reaction Time of Car-Following Model

2002 ◽  
Vol 19 ◽  
pp. 861-868 ◽  
Author(s):  
Jun SUZUKI ◽  
Takashi NAKATSUJI ◽  
Yoichi AZUTA ◽  
Ranjitkar PRAKASH
Keyword(s):  
Reaction Time ◽  
Experimental Analysis ◽  
Car Following ◽  
Car Following Model

The Potential Value of a Front-to-Rear-End Collision Warning System Based on Factors of Driver Behavior, Visual Perception and Brake Reaction Time

1992 ◽  
Vol 36 (13) ◽  
pp. 1003-1005 ◽  
Author(s):  
Daniel V. McGehee ◽  
Thomas A. Dingus ◽  
Avraham D. Horowitz
Keyword(s):  
Reaction Time ◽  
Visual Perception ◽  
Motor Vehicle ◽  
Driver Behavior ◽  
Warning System ◽  
Comfort Level ◽  
Collision Warning ◽  
Potential Value ◽  
Driver Performance ◽  
Performance Issues

The potential value of a front-to-rear-end collision warning system based on factors of driver behavior, visual perception and brake reaction time is examined in this paper. Twenty-four percent of all motor vehicle crashes involving two or more vehicles are front-to-rear-end collisions. These collisions demonstrate that several driver performance factors are common. The literature indicates that drivers use the relative size and the visual angle of the vehicle ahead when making judgments regarding depth. In addition, drivers often have difficulty gauging velocity differences and depth cues between themselves and the vehicle they are following. Finally, drivers often follow at distances that are closer than brake-reaction time permits for accident avoidance. It is apparent that the comfort level of close following behavior increases over time due to the rarity of consequences. Experience also teaches drivers that the vehicle in front does not suddenly slow down very often. On the basis of these driver behavior and human performance issues, a front-to-rear-end collision warning system that provides headway/following distance and velocity change information is considered. Based on the driver performance issues, display design recommendations are outlined. The value of such a device may be demonstrated by the added driver safety and situation awareness provided. The long-term goal would ultimately be the reduction of one of the most frequent type of automobile crashes.

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