Intrusion detection in VANETs through verification of vehicle movement data

On-board sensory systems in autonomous vehicles make it possible to acquire information about the vehicle itself and about its relevant surroundings. With this information the vehicle actuators are able to follow the corresponding control commands and behave accordingly. Localization is thus a critical feature in autonomous driving to define trajectories to follow and enable maneuvers. Localization approaches using sensor data are mainly based on Bayes filters. Whitebox models that are used to this end use kinematics and vehicle parameters, such as wheel radii, to interfere the vehicle’s movement. As a consequence, faulty vehicle parameters lead to poor localization results. On the other hand, blackbox models use motion data to model vehicle behavior without relying on vehicle parameters. Due to their high non-linearity, blackbox approaches outperform whitebox models but faulty behaviour such as overfitting is hardly identifiable without intensive experiments. In this paper, we extend blackbox models using kinematics, by inferring vehicle parameters and then transforming blackbox models into whitebox models. The probabilistic perspective of vehicle movement is extended using random variables representing vehicle parameters. We validated our approach, acquiring and analyzing simulated noisy movement data from mobile robots and vehicles. Results show that it is possible to estimate vehicle parameters with few kinematic assumptions.

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Efficiency Assessment of a Signalized Roundabout and a Traffic Intersection in Baghdad City

Engineering, Technology & Applied Science Research ◽

10.48084/etasr.4564 ◽

2021 ◽

Vol 11 (6) ◽

pp. 7910-7916

Author(s):

H. H. Mohammed ◽

M. Q. Ismail

Keyword(s):

Performance Measures ◽

Road Networks ◽

Signalized Intersection ◽

Movement Data ◽

Efficiency Assessment ◽

Traffic Intersection ◽

Traffic Volumes ◽

Smart Traffic ◽

Vehicle Movement ◽

Better Than

In Baghdad city, Iraq, the traffic volumes have rapidly grown during the last 15 years. Road networks need to reevaluate and decide if they are operating properly or not regarding the increase in the number of vehicles. Al-Jadriyah intersection (a four-leg signalized intersection) and Kamal Junblat Square (a multi-lane roundabout), which are two important intersections in Baghdad city with high traffic volumes, were selected to be reevaluated by the SIDRA package in this research. Traffic volume and vehicle movement data were abstracted from videotapes by the Smart Traffic Analyzer (STA) Software. The performance measures include delay and LOS. The analysis results by SIDRA Intersection 8.0.1 show that the performance of the roundabout is better than the signalized intersection but experiences high delay, and low LOS. Therefore, alternatives are proposed to improve the performance for current and future traffic volumes with low-medium delays.

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Region classification based on livestock vehicle movement data by community detection method

Journal of Preventive Veterinary Medicine ◽

10.13041/jpvm.2020.44.4.161 ◽

2020 ◽

Vol 44 (4) ◽

pp. 161-168

Keyword(s):

Community Detection ◽

Detection Method ◽

Region Classification ◽

Movement Data ◽

Vehicle Movement

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Using Tongue, Lip, and Jaw Movement Data to Improve Diagnostic Accuracy of ALS

10.1044/cred-dsa-bts-004 ◽

2014 ◽

Vol 1 (1) ◽

pp. 1

Author(s):

Jordan Green

Keyword(s):

Diagnostic Accuracy ◽

Jaw Movement ◽

Movement Data

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Age Differences in Eye Movements During Reading: Degenerative Problems or Compensatory Strategy?

European Psychologist ◽

10.1027/1016-9040/a000344 ◽

2019 ◽

Vol 24 (4) ◽

pp. 297-311

Author(s):

José David Moreno ◽

José A. León ◽

Lorena A. M. Arnal ◽

Juan Botella

Keyword(s):

Eye Movements ◽

Eye Movement ◽

Meta Analysis ◽

Age Groups ◽

Behavioral Changes ◽

Aging Effects ◽

Movement Data ◽

Sentence Reading ◽

The Difference ◽

Eye Movements During Reading

Abstract. We report the results of a meta-analysis of 22 experiments comparing the eye movement data obtained from young ( Mage = 21 years) and old ( Mage = 73 years) readers. The data included six eye movement measures (mean gaze duration, mean fixation duration, total sentence reading time, mean number of fixations, mean number of regressions, and mean length of progressive saccade eye movements). Estimates were obtained of the typified mean difference, d, between the age groups in all six measures. The results showed positive combined effect size estimates in favor of the young adult group (between 0.54 and 3.66 in all measures), although the difference for the mean number of fixations was not significant. Young adults make in a systematic way, shorter gazes, fewer regressions, and shorter saccadic movements during reading than older adults, and they also read faster. The meta-analysis results confirm statistically the most common patterns observed in previous research; therefore, eye movements seem to be a useful tool to measure behavioral changes due to the aging process. Moreover, these results do not allow us to discard either of the two main hypotheses assessed for explaining the observed aging effects, namely neural degenerative problems and the adoption of compensatory strategies.

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