DEVELOPMENT OF AUTONOMOUS VEHICLE MOTION PLANNING AND CONTROL ALGORITHM WITH D* PLANNER AND MODEL PREDICTIVE CONTROL IN A DYNAMIC ENVIRONMENT

The research in this report incorporates the improvement in the autonomous driving capability of self-driving cars in a dynamic environment. Global and local path planning are implemented using the D* path planning algorithm with a combined Cubic B-Spline trajectory generator, which generates an optimal obstacle free trajectory for the vehicle to follow and avoid collision. Model Predictive Control (MPC) is used for the longitudinal and the lateral control of the vehicle. The presented motion planning and control algorithm is tested using Model-In-the-Loop (MIL) method with the help of MATLAB® Driving Scenario Designer and Unreal Engine® Simulator by Epic Games®. Different traffic scenarios are built, and a camera sensor is configured to simulate the sensory data and feed it to the controller for further processing and vehicle motion planning. Simulation results of vehicle motion control with global and local path planning for dynamic obstacle avoidance are presented. The simulation results show that an autonomous vehicle follows a commanded velocity when the relative distance between the ego vehicle and an obstacle is greater than a calculated safe distance. When the relative distance is close to the safe distance, the ego vehicle maintains the headway. When an obstacle is detected by the ego vehicle and the ego vehicle wants to pass the obstacle, the ego vehicle performs obstacle avoidance maneuver by tracking desired lateral positions

Statistics of the epoch of reionization (EoR) 21-cm signal -- II. The evolution of the power spectrum error-covariance

The EoR 21-cm signal is expected to become highly non-Gaussian as reionization progresses. This severely affects the error-covariance of the EoR 21-cm power spectrum which is important for predicting the prospects of a detection with ongoing and future experiments. Most earlier works have assumed that the EoR 21-cm signal is a Gaussian random field where (1) the error variance depends only on the power spectrum and the number of Fourier modes in the particular $k$ bin, and (2) the errors in the different $k$ bins are uncorrelated. Here we use an ensemble of simulated 21-cm maps to analyze the error-covariance at various stages of reionization. We find that even at the very early stages of reionization ($\bar{x}_{\rm HI} \sim 0.9$) the error variance significantly exceeds the Gaussian predictions at small length-scales ($k > 0.5 \,{\rm Mpc}^{-1}$) while they are consistent at larger scales. The errors in most $k$ bins (both large and small scales), are however found to be correlated. Considering the later stages ($\bar{x}_{\rm HI} = 0.15$), the error variance shows an excess in all $k$ bins within $k \ge 0.1 \, {\rm Mpc}^{-1}$, and it is around $200$ times larger than the Gaussian prediction at $k \sim 1 \, {\rm Mpc}^{-1}$. The errors in the different $k$ bins are all also highly correlated, barring the two smallest $k$ bins which are anti-correlated with the other bins. Our results imply that the predictions for different 21-cm experiments based on the Gaussian assumption underestimate the errors, and it is necessary to incorporate the non-Gaussianity for more realistic predictions.Comment: Published in Monthly Notices of the Royal Astronomical Society (MNRAS). Available at "this URL http://dx.doi.org/10.1093/mnras/stw2599

The effect of non-Gaussianity on error predictions for the Epoch of Reionization (EoR) 21-cm power spectrum

The Epoch of Reionization (EoR) 21-cm signal is expected to become increasingly non-Gaussian as reionization proceeds. We have used semi-numerical simulations to study how this affects the error predictions for the EoR 21-cm power spectrum. We expect $SNR=\sqrt{N_k}$ for a Gaussian random field where $N_k$ is the number of Fourier modes in each $k$ bin. We find that non-Gaussianity is important at high $SNR$ where it imposes an upper limit $[SNR]_l$. For a fixed volume $V$, it is not possible to achieve $SNR > [SNR]_l$ even if $N_k$ is increased. The value of $[SNR]_l$ falls as reionization proceeds, dropping from $\sim 500$ at $\bar{x}_{HI} = 0.8-0.9$ to $\sim 10$ at $\bar{x}_{HI} = 0.15$ for a $[150.08\, {\rm Mpc}]^3$ simulation. We show that it is possible to interpret $[SNR]_l$ in terms of the trispectrum, and we expect $[SNR]_l \propto \sqrt{V}$ if the volume is increased. For $SNR \ll [SNR]_l$ we find $SNR = \sqrt{N_k}/A$ with $A \sim 0.95 - 1.75$, roughly consistent with the Gaussian prediction. We present a fitting formula for the $SNR$ as a function of $N_k$, with two parameters $A$ and $[SNR]_l$ that have to be determined using simulations. Our results are relevant for predicting the sensitivity of different instruments to measure the EoR 21-cm power spectrum, which till date have been largely based on the Gaussian assumption.Comment: Accepted for publication in MNRAS Letters. The definitive version is available at http://mnrasl.oxfordjournals.org/content/449/1/L4

The impact of non-Gaussianity on the error covariance for observations of the Epoch of Reionization 21-cm power spectrum

For abstract see published article

The young cluster NGC 2282 : a multi-wavelength perspective

We present the analysis of the stellar content of NGC~2282, a young cluster in the Monoceros constellation, using deep optical $BVI$ and IPHAS photometry along with infrared (IR) data from UKIDSS and $Spitzer$-IRAC. Based on the stellar surface density analysis using nearest neighborhood method, the radius of the cluster is estimated as $\sim$ 3.15\arcmin. From optical spectroscopic analysis of 8 bright sources, we have classified three early B-type members in the cluster, which includes, HD 289120, a previously known B2V type star, a Herbig Ae/Be star (B0.5 Ve) and a B5 V star. From spectrophotometric analyses, the distance to the cluster has been estimated as $\sim$ 1.65 kpc. The $K$-band extinction map is estimated using nearest neighborhood technique, and the mean extinction within the cluster area is found to be A$_V$ $\sim$ 3.9 mag. Using IR colour-colour criteria and H$_\alpha$-emission properties, we have identified a total of 152 candidate young stellar objects (YSOs) in the region, of which, 75 are classified as Class II, 9 are Class I YSOs. Our YSO catalog also includes 50 H$_\alpha$-emission line sources, identified using slitless spectroscopy and IPHAS photometry data. Based on the optical and near-IR colour-magnitude diagram analyses, the cluster age has been estimated to be in the range of 2 $-$ 5 Myr, which is in agreement with the estimated age from disc fraction ($\sim$ 58\%). Masses of these YSOs are found to be $\sim$ 0.1$-$2.0 M$_\odot$. Spatial distribution of the candidate YSOs shows spherical morphology, more or less similar to the surface density map.Comment: 16 pages, 19 Figure