Vehicle Safety Communications - Applications: System Design &amp; amp; Objective Testing Results

Ahmed-Zaid, F.; Krishnan, Hariharan; Maile, Michael; Caminiti, L; Bai, Sue; VanSickle, S

doi:10.4271/2011-01-0575

Cited by 12 publications

(14 citation statements)

References 1 publication

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“…In the usage stage, the two lists are no longer updated. Instead, the learned distributions are used to calculate (7). b) Logistic regression: This method assumes that the probability of emergency deceleration, which we use as the relevance function, fits a logistic function as…”

Section: B Machine Learning Methodsmentioning

confidence: 99%

“…The project resulted in a standardization of the SAE J2735 Basic Safety Message (BSM) that contains the vehicle state information (e.g., position, speed, and acceleration), which is important for safety applications [6]. It also identified EEBL as one of the several important safety applications and successfully tested its feasibility [7].…”

Section: Relevant Workmentioning

confidence: 99%

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Estimating Relevance for the Emergency Electronic Brake Light Application

Szczurek

Wolfson

et al. 2012

IEEE Trans. Intell. Transport. Syst.

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In this paper, we compare two methods of estimating relevance for the emergency electronic brake light application: One method uses an analytically derived formula based on the minimum safety gap that is required to avoid a collision, whereas the other method uses a machine learning approach. The application works by disseminating reports about vehicles that perform emergency deceleration in an effort to warn drivers about the need to perform emergency braking. Vehicles that receive such reports have to decide on whether the information contained in the report is relevant to the driver and warn the driver if that is the case. Common ways of determining relevance are based on the lane or direction information, but using only these attributes can lead to many false warnings, which can desensitize the driver. Desensitized drivers may ignore warnings or completely turn off the system, thus eliminating any safety benefits of the application. We show that the machine learning method, compared with the analytically derived formula, can significantly reduce the number of false warnings by learning from the actions that drivers take after receiving a report. The methods were compared using simulated experiments with a range of traffic and communication parameters.

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Section: B Machine Learning Methodsmentioning

confidence: 99%

Section: Relevant Workmentioning

confidence: 99%

Estimating Relevance for the Emergency Electronic Brake Light Application

Szczurek

Wolfson

et al. 2012

IEEE Trans. Intell. Transport. Syst.

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“…In-vehicle crash avoidance systems enabled by wireless communications can significantly reduce the number of collisions on the roads and mitigate the severity when these crashes become unavoidable [1]. The communications system supporting data exchanges among vehicles is known as 5.9 GHz Dedicated Short-Range Communications (DSRC) [2].…”

Section: Introductionmentioning

confidence: 99%

Intersection Collision Avoidance: From Driver Alerts to Vehicle Control

Maile

Chen

Brown

et al. 2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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Intersection Collision Avoidance (ICA) based on Dedicated Short Range Communications (DSRC) is one of the most promising applications for vehicle communications. System implementations based on vehicle sensors suffer from field of view limitations that vehicle communications do not exhibit. This makes particularly interesting the adoption of DSRC in combination with other onboard sensors to address intersection crash scenarios. State-of-theart DSRC-based intersection collision avoidance systems, notably the Intersection Movement Assist (IMA) application, are aimed to issue audible and visual alerts to the driver. This paper describes an implementation of Intersection CollisionAvoidance that extends the IMA concept to cover a wider range of intersection collision scenarios and introduces automated braking as a system response when a high risk of a collision is detected and the driver does not react to the alerts.

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“…Jiang et al [5] propose a specific protocol for safety-related wireless communications between vehicles. The VSC-A report [6] describes an extensive series of experiments testing the performance of wireless V2V communication in a variety of situations that are typically problematic for autonomous vehicle safety systems. Sepulcre and Gozalvez [7] observe that achieving safety in different roadway scenarios could impose very different specifications on the underlying wireless communications system.…”

Section: Related Workmentioning

confidence: 99%

Efficiency analysis of formally verified adaptive cruise controllers

Loos

Witmer

Steenkiste

et al. 2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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Abstract-We consider an adaptive cruise control system in which control decisions are made based on position and velocity information received from other vehicles via V2V wireless communication. If the vehicles follow each other at a close distance, they have better wireless reception but collisions may occur when a follower car does not receive notice about the decelerations of the leader car fast enough to react before it is too late. If the vehicles are farther apart, they would have a bigger safety margin, but the wireless communication drops out more often, so that the follower car no longer receives what the leader car is doing. In order to guarantee safety, such a system must return control to the driver if it does not receive an update from a nearby vehicle within some timeout period. The value of this timeout parameter encodes a tradeoff between the likelihood that an update is received and the maximum safe acceleration. Combining formal verification techniques for hybrid systems with a wireless communication model, we analyze how the expected efficiency of a provablysafe adaptive cruise control system is affected by the value of this timeout.

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Vehicle Safety Communications - Applications: System Design & amp; Objective Testing Results

Cited by 12 publications

References 1 publication

Estimating Relevance for the Emergency Electronic Brake Light Application

Estimating Relevance for the Emergency Electronic Brake Light Application

Intersection Collision Avoidance: From Driver Alerts to Vehicle Control

Efficiency analysis of formally verified adaptive cruise controllers

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