Non-cooperating vehicle tracking in VANETs using the conditional logit model

Vehicular Ad Hoc Networks (VANETs) are widely considered as indispensable elements of the future intelligent transportation systems that are aiming to apply information and communications technologies to improve transportation safety and quality of experience. We present our take on a relatively unexplored problem, exploiting VANETs for on-road surveillance. The proposal is inspired by multi-agent systems intended for surveillance, e.g., a distributed camera network. We propose a tracking system composed of three operational modules, namely, localization, tracking data collection and prediction of future locations of a target. Camera equipped onboard units (OBUs) act as remote mobile sensors. Tracking messages are communicated among the OBUs and roadside units (RSUs). These messages are also triggered in the possible locations of the target in a timely manner. Therefore, it is imperative to scope the search to limit the number of OBUs and RSUs involved in the tracking operation, thus, minimizing the number of tracking messages. To this end, a movement modeling technique utilizes the OBU-observations to classify the target's movement pattern to aid future trajectory prediction. In our previous work, we proposed a Dirichlet-multinomial (D-M) model under the Bayesian estimation framework. In this paper, we present newly identified cues towards improving the movement estimation model. The D-M model is constrained to the assumption that all the choice sets are identical across trials. We demonstrate that this is almost never the case. The improved model exploits a choice model, called the conditional logit. The conditional logit model is attractive when choice sets vary across trials. Additionally, we weight outcome of each trial according to the given choice sets to achieve higher estimation accuracy. We evaluate the new model by means of an experimental analysis and compare results with the D-M model

Why do caterpillars whistle at birds? Insect defence sounds startle avian predators

Many insects produce sounds when attacked by a predator, yet the functions of these signals are poorly understood. It is debated whether such sounds function as startle, warning or alarm signals, or merely serve to augment other defences. Direct evidence is limited owing to difficulties in disentangling the effects of sounds from other defences that often occur simultaneously in live insects. We conducted an experiment to test whether an insect sound can function as a deimatic (i.e. startle) display. Variations of a whistle of the walnut sphinx caterpillar (Amorpha juglandis) were presented to a predator, red-winged blackbirds (Agelaius phoeniceus), when birds activated a sensor while feeding on mealworms (Tenebrio molitor). Birds exposed to whistles played back at natural sound levels exhibited significantly higher startle scores (by flying away, flinching, and hopping) and took longer to return to the feeding dish than during control conditions where no sounds were played. Birds habituated to sounds during a one-hour session, but after two days the startling effects were restored. Our results provide empirical evidence that an insect sound alone can function as a deimatic display against an avian predator. We discuss how whistles might be particularly effective ‘acoustic eye spots’ on avian predators