Prediction of rear-end conflict frequency using multiple-location traffic parameters

Katrakazas, Christos; Theofilatos, Athanasios; Islam, Ashraful; Papadimitriou, Eleonora; Dimitriou, Loukas; Antoniou, Constantinos

doi:10.1016/j.aap.2021.106007

Cited by 34 publications

(11 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The brake light is one such visual cue, and has an important impact on the deceleration of the vehicle. It affects both the speed and flow of traffic, and may cause rear-end collisions and other traffic conflicts [ 33 , 34 , 35 ]. Therefore, in order to further understand the impact of flashing brake lights on driving safety, further exploration of the issue in several research directions considering the limitations of this study is necessary.…”

Section: Discussionmentioning

confidence: 99%

A Simulation-Based Study of the Effect of Brake Light Flashing Frequency on Driver Brake Behavior from the Perspective of Response Time

Hsieh

Chen

Lee

et al. 2022

Behavioral Sciences

View full text Add to dashboard Cite

To prevent vehicle crashes, studies have proposed the use of flashing signals (brake lights or other light indicators) to improve the driver’s response time when the leading vehicle is braking. However, there are no consistent results on the ideal flashing frequency of the brake lights. This study aimed to investigate different brake light flashing frequencies to assess their impact on braking response time. Twenty-four participants aged 25 to 30 were recruited. Two driving speed environments (50 and 80 km/h), three deceleration rates (0.25, 0.6, and 1 g), and four brake light flashing frequencies (0, 2, 4, and 7 Hz) were examined. Braking response time, average braking force, and braking response time ratio were used to evaluate the driving behavior. The results showed that the braking response time and average braking force were affected by the deceleration rate in the 50 km/h driving environment. In the 50 and 80 km/h driving environments, although there were no significant differences among the three deceleration rates, the braking response time decreased by 3–7% under the flashing brake light condition. These findings can be used as a reference for safety designs as well as future studies on driving behavior.

show abstract

Section: Discussionmentioning

confidence: 99%

A Simulation-Based Study of the Effect of Brake Light Flashing Frequency on Driver Brake Behavior from the Perspective of Response Time

Hsieh

Chen

Lee

et al. 2022

Behavioral Sciences

View full text Add to dashboard Cite

show abstract

“…According to Minderhoud's statistics on driver's lane changing data and driver's subjective acceptable safety limit [ 26 ], the 5% quantile (2.6 s) and 25% quantile (5 s) of TTC were taken as the boundary value. It means that

where v 3 and v 4 are the opposite number of v 2 and v 1 , respectively.…”

Section: Vehicle Cluster Situation Model and Recognition Methodsmentioning

confidence: 99%

Recognition Method of Vehicle Cluster Situation Based on Set Pair Logic considering Driver’s Cognition

Liu

Wang

Chen

et al. 2021

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

The recognition of vehicle cluster situations is one of the critical technologies of advanced driving, such as intelligent driving and automated driving. The accurate recognition of vehicle cluster situations is helpful for behavior decision-making safe and efficient. In order to accurately and objectively identify the vehicle cluster situation, a vehicle cluster situation model is proposed based on the interval number of set pair logic. The proposed model can express the traffic environment’s knowledge considering each vehicle’s characteristics, grouping relationships, and traffic flow characteristics in the target vehicle’s interest region. A recognition method of vehicle cluster situation is designed to infer the traffic environment and driving conditions based on the connection number of set pair logic. In the proposed model, the uncertainty of the driver’s cognition is fully considered. In the recognition method, the relative uncertainty and relative certainty of driver’s cognition, traffic information, and vehicle cluster situation are fully considered. The verification results show that the proposed recognition method of vehicle cluster situations can realize accurate and objective recognition. The proposed anthropomorphic recognition method could provide a basis for vehicle autonomous behavior decision-making.

show abstract

“…Each experiments calculated the risk values of all vehicles within 20 minutes. And draw the risk evolution curve of ten following vehicles from the moment of accident ( 0) t = to the moment after accident ( 8) t = . In order to reduce the page size occupied by the picture, we only show the experimental results of six traffic states for analysis and explanation.…”

Section: Analysis Of Risk Propagation Characteristics 1) Risk Micro P...mentioning

confidence: 99%

“…Therefore, in order to improve the collision discrimination effect, some scholars used multiple indicators to distinguish. For example, Christos combined TTC and DRAC to distinguish vehicle collision [8]. In previous studies, conflict indicators were often used to assess historical vehicle collision risk, and only in a few studies were used to assess real-time vehicle collision risk.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Bayesian Network Model for Real-Time Risk Propagation of Secondary Rear-End Collision Accident Using Driving Risk Field

2022

View full text Add to dashboard Cite

In order to take more active measures to prevent and control secondary accidents, it is necessary to describe risk propagation process after the accident. To this end, this paper deeply analyzed the risk propagation mechanism between vehicles and proposed a novel secondary rear-end collision accident risk propagation model, which could real-time evaluate vehicle rear-end collision risk. The research scene of the paper is a single-lane road rear-end collision scene, so a driving risk field model suitable for this scene is first established. Based on this, the vehicle operation interaction risk field force is calculated. Then, the risk field force is converted into risk probability through the hyperbolic tangent function, and the vehicle operation interaction risk model is obtained. In addition, a risk propagation framework based on dynamic Bayesian network is constructed to describe the propagation process of rear-end collision risk from the accident vehicle to following vehicles. Finally, according to the probabilistic reasoning process of the framework, combined with the accident vehicle risk, a secondary rearend collision accident risk propagation model is established. Simulation experiments show that the paper model can describe the evolution trend of rear-end risk and the risk assessment results are more accurate. And after the accident, the rear-end collision risk propagation speed will increase with the increase of traffic flow, and the number of secondary rear-end vehicles will also increase with the increase of traffic speed. These conclusions are of great significance in formulating vehicle anti-collision strategies and deploying risk management and control facilities.INDEX TERMS Secondary rear-end collision; Risk propagation; Driving risk field; Dynamic Bayesian network

show abstract

Prediction of rear-end conflict frequency using multiple-location traffic parameters

Cited by 34 publications

References 64 publications

A Simulation-Based Study of the Effect of Brake Light Flashing Frequency on Driver Brake Behavior from the Perspective of Response Time

A Simulation-Based Study of the Effect of Brake Light Flashing Frequency on Driver Brake Behavior from the Perspective of Response Time

Recognition Method of Vehicle Cluster Situation Based on Set Pair Logic considering Driver’s Cognition

A Dynamic Bayesian Network Model for Real-Time Risk Propagation of Secondary Rear-End Collision Accident Using Driving Risk Field

Contact Info

Product

Resources

About