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This paper develops a novel algorithm for tracking closely-spaced road vehicles using a low-density flash lidar. Low-density flash lidars are recent to the automotive market and have attracted attention due to their low cost. However, these sensors have a poor angular resolution which makes tracking the lateral motion of targets challenging. One such challenge, namely unresolved measurements from multiple vehicles, is addressed in this paper. Detections from multiple targets can become unresolved if the targets are closely spaced. Traditional tracking algorithms, which do not account for unresolved measurements, lead to degraded tracking performance in such scenarios. This paper proposes a novel method based on predicting the lateral motion states of targets forward in time, and truncating their probability density functions at points based on the unresolved measurements. The method proposed works with a computationally simple data association algorithm, requires no sensor modeling, and can track more than two closely spaced targets. The proposed algorithm is evaluated using simulations and on-road experiments, and the results demonstrate its capability in maintaining target tracks even in the presence of unresolved detections. Further, a comparison with the well known Joint Probabilistic Data Association-Merged algorithm showed that the proposed algorithm is computationally lighter.

Wheel slip regulation algorithms constitute a significant part of active vehicle safety systems in heavy commercial road vehicles. Any wheel slip regulation algorithm designed for set-point tracking requires a reference operating wheel slip irrespective of its control strategy. This reference slip is unique to each tire-road interface and changes with tire normal load. The present work proposes the optimal reference slip as one that minimizes braking distance, and introduces a recursive algorithm for its estimation. It further proposes a framework for reference slip estimation and wheel slip control. The credibility of the framework was established by testing in a Hardware-in-Loop setup consisting of a pneumatic braking system and IPG TruckMaker ® , a high fidelity vehicle dynamics simulation environment. The algorithm estimated the reference slip corresponding to different tire-road interfaces and resulted in stable braking maneuvers with 7-17% reduction in braking distance.

The cell lines derived from the fall armyworm (FAW), Spodoptera frugiperda, have been widely used for production of recombinant proteins for applications in both basic research and applications in medicine and agriculture. Promoters from the nucleopolyhedrovirus (NPV) are commonly used in these expression systems. These promoters have some limitations, which may be overcome by using promoters of genes from S. frugiperda. However, information on these promoters is not available. We identified several highly expressed genes from the transcriptomes of S. frugiperda midgut, fat body, epidermis, ovarian cell line (Sf9), and a midgut cell line (Sf17). The activity of potential promoters of 21 highly expressed genes was evaluated in Sf9 and Sf17 cells. Two of these promoters, SfHSC70-P1780 and SfPub-P2009, showed higher activity than commonly used hr5/ie1 (baculovirus enhancer element, hr5 and immediate early gene 1, ie1) promoter. Interestingly, the activity of these two promoters increased after adding hr5 enhancer element. The hr5/SfPub-P2009 promoter performance was evaluated by expressing an exogenous P450 protein in Sf9 cells using a plasmid-based expression system. The activity of this promoter was also evaluated in the FAW by expressing green fluorescence protein using the baculovirus expression system. In both cases, the hr5/SfPub-P2009 promoter performed better than the commonly used hr5/ie1 promoter. These strong endogenous promoters will be useful for studies in S. frugiperda and other lepidopteran insects for multiple applications, including protein expression, genome editing, and transgenic insects.

The southern green stink bug (SGSB, Nezara viridula) is an emerging polyphagous pest in many regions of the world. RNA interference (RNAi) is a valuable method for understanding gene function and holds great potential for pest management. However, RNAi efficiency is variable among insects and the differences in transport of double-stranded RNA (dsRNA) are one of the major factors that contribute to this variability. In this study, Cy3 labeled dsRNA was used to track the transport of dsRNA in SGSB tissues. Cy3_dsRNA was detected in the hemocytes, fat body (FB), epidermis, and midgut tissues at 24-72 hr after injection. Orally delivered Cy3_dsRNA or Cypher-5E labeled dsRNA was mostly detected in the midgut and a few signals were detected in parts of the FB and epidermis. Both injected and fed Cy3_dsRNA showed stronger signals in SGSB tissues when compared to Cy3_siRNA (small interfering RNA) or Cy3_shRNA (short hairpin RNA). dsRNA targeting the gene for a vacuolar-sorting protein, SNF7, induced higher knockdown of the target gene and greater SGSB mortality compared to siRNA or shRNA targeting this gene. 32 P-labeled dsRNA injected into SGSB was processed into siRNA, but fed 32 P-labeled dsRNA was not efficiently processed into siRNA. These data suggest that transport of orally delivered dsRNA across the midgut epithelium is not efficient in SGSB which may contribute to variable RNAi efficiency. Targeting genes expressed in the midgut rather than other tissues and using dsRNA instead of siRNA or shRNA would be more effective for RNAi-mediated control of this pest.

The E93 transcription factor is a member of helix-turn-helix transcription factor family containing a Pip-squeak motif. This ecdysone primary response gene was identified as a regulator of cell death in Drosophila melanogaster where it is involved in ecdysone-induced autophagy and caspase activity that mediate degeneration of larval tissues during metamorphosis from larva to pupa. However, its function in adult insects is not well studied. To study E93 function in the red flour beetle, Tribolium castaneum, double-stranded RNA (dsRNA) targeting E93 (dsE93) was injected into newly emerged adults. Knockdown of E93 caused a decrease in the synthesis of vitellogenin (Vg), oocyte development, and egg-laying. Sequencing of RNA isolated from adults injected with dsE93 and control dsmalE (dsRNA targeting Escherichia coli malE gene) followed by differential gene expression analysis showed upregulation of genes involved in the metabolism of reserved nutrients. E93 knockdown induced changes in gene expression resulted in a decrease in Vg synthesis in the fat body and oocyte maturation in ovaries. Mating experiments showed that females injected with dsE93 did not lay eggs. Knockdown of E93 caused a reduction in the number and size of lipid droplets in the fat body when compared with that in control beetles injected with dsmalE. These data suggest that during the first 2-3 days after the emergence of adult females, E93 suppresses genes coding for enzymes that metabolize reserved nutrients until initiation of vitellogenesis and oogenesis.

The cigarette beetle (CB; Lasioderma serricorne) is a pest on many stored products including tobacco. Fumigation is the common control method currently used. However, the options for controlling this pest are limited, due to resistance issues and phasing out of currently used chemical insecticides. Here, we evaluated RNA interference (RNAi) as a potential method for controlling the CB. RNA isolated from different stages was sequenced and assembled into a transcriptome. The CB RNA sequences showed the highest homology with those in the red flour beetle, Tribolium castaneum. Orthologs of proteins known to function in RNAi pathway were identified in the CB transcriptome, suggesting that RNAi may work well in this insect. Also, 32 P-labeled double-stranded RNA (dsRNA) injected into CB larvae and adults was processed to small interference RNAs. We selected 12 genes that were shown to be the effective RNAi targets in T. castaneum and other insects and identified orthologs of them in the CB by searching its transcriptome. Injection of dsRNA targeting genes coding for GAWKY, Kinesin, Sec23, SNF7, and 26S proteasome subunit 6B into the CB larvae caused 100% mortality. Feeding dsRNA targeting SNF7 and 26S proteasome subunit 6B by sucrose droplet assay induced more than 90% mortality, which is 1.8 times higher than the mortality induced by dsGFP control (53%). These data demonstrate an efficient RNAi response in CB, suggesting that RNAi could be developed as an efficient method to control this pest.

RNA interference (RNAi) has become an integral part of mainstream research due to its versatility and ease of use. However, the potential nontarget effects associated with double-stranded RNAs (dsRNA) are poorly understood. To explore this, we used dsRNAs targeting the inhibitor of apoptosis (iap) gene from nine insect species and assayed their possible nontarget effects. For each assay, we used a control (dsRNA targeting the gene coding for green fluorescent protein, GFP) and a species-specific dsRNA targeting nine iap genes in insect species to evaluate target gene knockdown efficiency, apoptosis phenotype in cells and mortality in insects. Our results revealed that dsIAP efficiently knocks down iap gene expression and induces apoptosis phenotype and mortality in target insect species. In contrast, no significant knockdown of the iap gene expression, apoptosis phenotypes, or mortality were detected in cell lines developed from nontarget insects or nontarget insects treated with dsIAPs. Interestingly, even among closely related insects such as stink bugs, Nezara viridula, Halyomorpha halys, and Murgantia histrionica, with substantial sequence similarity among iap genes from these insects, no significant nontarget effects of dsIAP were observed under the conditions tested. These data demonstrate no significant nontarget effects for dsIAPs and suggest that the threat of nontarget effects of RNAi technology may not be substantial.

Fault detection and isolation in brake system is crucial for the safe operation of autonomous vehicles. Failure to detect impending faults may result in component degradation, which leads to vehicle breakdown. In recent years, Machine Learning techniques have been widely used for fault diagnosis in vehicles and hence provide intelligence in fault prediction. This paper proposes a general fault detection and isolation method for air brake system in Heavy Commercial Road Vehicle (HCRV) using machine learning techniques. Decision tree and random forest methods have been used to learn fault patterns that are reflected in the wheel speed sensor data. The training and testing data for the diagnostic scheme were collected from the Hardware-in-Loop (HiL) set up of air brake system. To classify the fault/no-fault conditions of air brake system, a random forest approach gave good prediction accuracy of 94.47 %.

Wheel slip regulation (WSR) is an approach to achieve anti-lock braking, where the parameter, wheel slip ratio, is made to operate around a reference value. WSR algorithms can be rule-based or model-based. Model-based solutions require real-time information on vehicle parameters including tire model parameters that increases the challenge in their real-world implementation. Hence, this work proposes a novel triphase rule-based WSR algorithm for Heavy Commercial Road Vehicles, that employ an electro-pneumatic brake system. Since the direct measurement of wheel slip is not feasible, estimates from an Extended Kalman Filter are used to monitor and regulate slip. A real-time reference adaptation scheme is proposed to detect low friction road surfaces. The proposed algorithm is evaluated in a Hardware-in-Loop experimental setup, and shown to adapt to the road surface, prevent wheel lock, and reduce braking distance up to 19 % compared to the case without control.

Defects are a ubiquitous feature of ordered media. They have certain universal features, independent of the underlying physical system, reflecting their topological origins. While the topological properties of defects are robust, they appear as ‘unphysical’ singularities, with non-integrable energy densities in coarse-grained macroscopic models. We develop a principled approach for enriching coarse-grained theories with enough of the ‘micro-physics’ to obtain thermodynamically consistent, well-set models, that allow for the investigations of dynamics and interactions of defects in extended systems. We also develop associated numerical methods that are applicable to computing energy driven behaviors of defects across the amorphous-soft-crystalline materials spectrum. Our methods can handle order parameters that have a head-tail symmetry, i.e. director fields, in systems with a continuous translation symmetry, as in nematic liquid crystals, and in systems where the translation symmetry is broken, as in smectics and convection patterns. We illustrate our methods with explicit computations.

Background: Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares CVD/stroke risk using the Framingham Risk Score (FRS)-based risk calculator when adapting IVA against VA. Methods: The system follows a four-step process: (I) VA using cIMT based using linear-regression (LR) model and its coefficients; (II) VA prediction using ten CRF using a multivariate linear regression (MLR)based model with gender adjustment; (III) coefficients from the LR-based model and MLR-based model are combined using a linear model to predict the final IVA; (IV) the final step consists of FRS-based risk stratification with IVA as inputs and benchmarked against FRS using conventional method of CA. Area-under-the-curve (AUC) is computed using IVA and benchmarked against CA while taking the response variable as a standardized combination of cIMT and glycated hemoglobin. Results: The study recruited 648 patients, 202 were Japanese, 314 were Asian Indian, and 132 were Caucasians. Both left and right common carotid arteries (CCA) of all the population were scanned, thus a total of 1,287 ultrasound scans. The 10-year FRS using IVA reported higher AUC (AUC =0.78) compared with 10-year FRS using CA (AUC =0.66) by ~18%. © Cardiovascular Diagnosis and Therapy. All rights reserved.

Diabetes and atherosclerosis are the predominant causes of stroke and cardiovascular disease (CVD) both in low- and high-income countries. This is due to the lack of appropriate medical care or high medical costs. Low-cost 10-year preventive screening can be used for deciding an effective therapy to reduce the effects of atherosclerosis in diabetes patients. American College of Cardiology (ACC)/American Heart Association (AHA) recommended the use of 10-year risk calculators, before advising therapy. Conventional risk calculators are suboptimal in certain groups of patients because their stratification depends on (a) current blood biomarkers and (b) clinical phenotypes, such as age, hypertension, ethnicity, and sex. The focus of this review is on risk assessment using innovative composite risk scores that use conventional blood biomarkers combined with vascular image-based phenotypes. AtheroEdge™ tool is beneficial for low-moderate to high-moderate and low-risk to high-risk patients for the current and 10-year risk assessment that outperforms conventional risk calculators. The preventive screening tool that combines the image-based phenotypes with conventional risk factors can improve the 10-year cardiovascular/stroke risk assessment. © 2020 Frontiers in Bioscience. All rights reserved.

We propose a time dependent Eulerian model for sea surface entrainment, buoyancy transport and droplet dynamics of ocean oil. The model captures the microscale vertical oil mass exchanges in the neighborhood of the sea surface. This model is in turn part of an oil fate model designed to capture oil dynamics at large spatio-temporal scales typical of environmental studies. The adiabatic dynamics of the droplets are upscaled by a combination of filtering and stochastic parametrization. The upscaling addresses the computational burden of resolving the microscale. The upscaled droplet dynamics are tested against data and the mass exchange mechanism is incorporated into a nearshore oil transport model in order to highlight the importance of incorporating vertical mass exchanges and droplet distribution dynamics in predicting the distributing of shoaling oil.

Aim: We assessed the extent to which chemotherapy cycles recorded in Hospital Episode Statistics (HES) Admitted Patient Care (APC) were captured in National Cancer Registration & Analysis Service Systemic Anti-Cancer Therapy (SACT) for a cohort of lung cancer patients. Methods: All chemotherapy cycles recorded for linkage eligible lung cancer patients with a National Cancer Registration & Analysis Service diagnosis between 2012 and 2015 were identified in HES APC and SACT. Results: Among a population of 4070 lung cancer patients, 6076 chemotherapy cycles were observed in HES APC data. A total of 61% of cycles were recorded in SACT on the same day, 8% on a different day and 31% were not recorded in SACT. Conclusion: Our results suggest that SACT may not capture all chemotherapy cycles administered to a patient between 2012 and 2016; however, administrative changes mean data after this period may be more complete.

The goal of this paper is to describe the oscillatory microstructure that can emerge from minimizing sequences for nonconvex energies. We consider integral functionals that are defined on real valued (scalar) functions $u(x)$ which are nonconvex in the gradient $\nabla u$ and possibly also in $u$. To characterize the microstructures for these nonconvex energies, we minimize the associated relaxed energy using two novel approaches: i) a semi-analytical method based on control systems theory, ii) and a numerical scheme that combines convex splitting together with a modified version of the split Bregman algorithm. These solutions are then used to gain information about minimizing sequences of the original problem and the spatial distribution of microstructure., 34 pages, 10 figures

This paper analyzes and compares global standards that specify test procedures to evaluate a vehicle powertrain’s performance. For an electric bus, the impact of variation in test conditions permitted by the standards, both on the motor ratings sized to satisfy given performance specifications, and on the performance achieved with given motor ratings, was studied. The impact on motor ratings was determined theoretically, while the impact on performance achieved was determined through simulations using AVL CRUISE™. The variation in motor ratings was proportional to the variation in performance achieved. The observed variation was significant for the maximum acceleration and maximum speed tests.

This paper presents a theoretical sizing framework for torque coupled and speed coupled motor drive configurations for an electric bus using given performance requirements. Either the motors are sized or the coupling mechanism is sized, given specifications of the other. The performance of the coupled configurations was evaluated and compared with a single motor drive configuration, using both theoretical calculations and AVL CRUISETM, for a 10 ton bus. Performance obtained from simulation and theoretical calculations matched closely, which corroborates the sizing framework. The coupled configurations were observed to satisfy all performance requirements, unlike the single motor drive configuration.

Hybrid electric powertrains for military vehicles offer potential for improved performance, enhanced stealth capability and increased on-board electric power. This paper presents a design of a parallel hybrid electric powertrain for a military tracked vehicle by analyzing its mobility attributes. This involved the component sizing of a hybrid electric powertrain with torque and speed coupling. In this study, two different approaches were used for sizing the powertrain components with a planetary gear unit as speed coupling device. After comparing different speed coupling configurations, the powertrain configuration with connections of the motor to the sun gear, engine to the ring gear, and transmission to the planet carrier provided the least component ratings. Between torque coupling and speed coupling, the powertrain with speed coupling satisfied the given performance requirements with lower motor torque ratings.

In heavy commercial road vehicles, the air brake system is a critical vehicle safety system whose performance degradation increases the risk of accidents and hence requires periodic inspection and maintenance. The wear of brake pad lining and brake drum during operation leads to increase in the stroke of a component called pushrod whose ‘out-of-adjustment’ creates severe brake performance degradation. The fact that the driver does not receive a corresponding tactile feedback till it is too severe adds to the complexity of manual detection. Motivated by the increase in onboard sensing, electronics, and computation capabilities, this study proposes an artificial neural network–based approach to predict pushrod stroke based on measurement of brake chamber pressure. Here, a back propagation algorithm was used to train the multilayer feed-forward network. The effect of excessive pushrod stroke on vehicle braking response was first studied using a Hardware-in-Loop system that consists of brake system hardware and a commercial vehicle dynamics simulation software (IPG TruckMaker®). Experimental data collected from this system with manual slack adjuster and automatic slack adjuster have then been used to train and test the artificial neural network for pushrod stroke prediction. The performance of the prediction scheme has been tested over the entire range of brake operating conditions. The prediction error corresponding to manual slack adjuster was found to be within ±15% in 322 out of the entire test set of 328 instances (98.17%) and automatic slack adjuster within ±8% in all 57 test sets (100%). Statistical analysis based on confidence interval revealed a prediction error between −1.62% and −3.05% for manual slack adjuster and 0.43% and −1.62% for automatic slack adjuster for 99% confidence interval, which demonstrated the efficacy of the proposed prediction scheme.

Wheel lock is an undesired phenomenon in Heavy Commercial Road Vehicles (HCRVs) and wheel slip control within a desired range is of crucial importance for stable and effective braking. This study proposes a framework to distribute brake force dynamically between the front and rear wheels, primarily to avoid instability by preventing wheel lock. Further, it ensures the maximum utilization of the available traction force at the tire-road interface that varies during the course of braking due to factors like load transfer. Wheel slip regulation provides an approach to maximize braking performance that subsumes the effects of varying road, load and braking conditions that occur during vehicle deceleration. The methodology proposed consists of a wheel slip controller that calculates the required brake force distribution parameters, which are then provided to the brake controller for control action. Sliding mode control was used because of the nonlinear nature of the longitudinal vehicle dynamic model considered and for robustness towards different parameter variations. The algorithm was implemented on a Hardware-in-Loop test setup consisting of a pneumatic air brake system, interfaced with IPG-TruckMaker® (a vehicle dynamic simulation software), and co-simulated with MATLAB-Simulink®. It was found that this algorithm improved the braking performance of a HCRV both in terms of stopping distance and vehicle stability.

Wheel Slip Regulation (WSR) is one of the Active Vehicle Safety Systems (AVSSs) for maintaining vehicle stability and maneuverability during emergency braking An approach for wheel slip prediction is proposed in this paper, which involves Auto-Regressive (AR) Time-Series modelling of longitudinal vehicle acceleration. This technique allows the usage of linear longitudinal vehicle dynamics for wheel slip estimation. A wheel slip prediction model was developed considering measurements from accelerometer and wheel speed sensor. This modified the Model Predictive Control (MPC) formulation to a univariate control input problem, involving braking torque. The objective function was devised for solving a least-squares reference tracking problem. An analytical solution for the MPC optimization problem was derived and implemented towards WSR. The proposed framework was programmed in MATLAB Simulink® and co-simulated with IPG TruckMaker® (a vehicle dynamic simulation software). The algorithm was tested in a Hardware-in-Loop (HiL) setup consisting of a pneumatic air brake system interfaced with IPG TruckMaker®. Open loop studies from HiL led to the inclusion of Kalman filter for estimate tuning and PID inner loop control for brake pressure transients, which improved wheel slip regulation.

Advanced Driver Assistance Systems in Heavy Commercial Road Vehicles are of increasing importance due to their high potential in reducing road accidents, where human error is the major contributor. A Vehicle-to-Vehicle communication-based Collision Avoidance Algorithm (CAA) can help in reducing these accidents by complementing the onboard sensors and applying brakes automatically upon detecting a threat. However, due to the wireless nature and dynamic topology of this communication network, packet loss is a major challenge for safety-related applications like collision avoidance. Hence, the effect of packet loss on the performance of CAA was investigated using a Hardware-in-Loop experimental platform in this paper. It was observed that the desired final spacing was maintained but, early braking was observed when the host vehicle followed the lead vehicle at close distances.

Significance The RNA interference (RNAi) discovered in nematodes has contributed to major advances in basic and applied sciences. RNAi-based methods are being developed for controlling pests and disease vectors. RNAi is highly efficient and systemic in coleopteran insects, but not in other insects. The lower efficiency of RNAi in economically important insects and concerns about resistance development are hindering the widespread use of this technology. To address these problems, a RNAi-sensitive Colorado potato beetle, Leptinotarsa decemlineata, and a cell line derived from this insect were used to identify a dsRNA-binding protein, StaufenC, as a major contributor to RNAi and its resistance. Interestingly, StaufenC homologs are present in only coleopteran insects and are essential for efficient RNAi response and its resistance in these insects., RNA interference (RNAi) is being used to develop methods to control pests and disease vectors. RNAi is robust and systemic in coleopteran insects but is quite variable in other insects. The determinants of efficient RNAi in coleopterans, as well as its potential mechanisms of resistance, are not known. RNAi screen identified a double-stranded RNA binding protein (StaufenC) as a major player in RNAi. StaufenC homologs have been identified in only coleopteran insects. Experiments in two coleopteran insects, Leptinotarsa decemlineata and Tribolium castaneum, showed the requirement of StaufenC for RNAi, especially for processing of double-stranded RNA (dsRNA) to small interfering RNA. RNAi-resistant cells were selected by exposing L. decemlineata, Lepd-SL1 cells to the inhibitor of apoptosis 1 dsRNA for multiple generations. The resistant cells showed lower levels of StaufenC expression compared with its expression in susceptible cells. These studies showed that coleopteran-specific StaufenC is required for RNAi and is a potential target for RNAi resistance. The data included in this article will help improve RNAi in noncoleopteran insects and manage RNAi resistance in coleopteran insects.

We analyze the effect of adding a weak, localized, inhomogeneity to a two dimensional array of oscillators with nonlocal coupling. We propose and also justify a model for the phase dynamics in this system. Our model is a generalization of a viscous eikonal equation that is known to describe the phase modulation of traveling waves in reaction-diffusion systems. We show the existence of a branch of target pattern solutions that bifurcates from the spatially homogeneous state when $\varepsilon$, the strength of the inhomogeneity, is nonzero and we also show that these target patterns have an asymptotic wavenumber that is small beyond all orders in $\varepsilon$. The strategy of our proof is to pose a good ansatz for an approximate form of the solution and use the implicit function theorem to prove the existence of a solution in its vicinity. The analysis presents two challenges. First, the linearization about the homogeneous state is a convolution operator of diffusive type and hence not invertible on the usual Sobolev spaces. Second, a regular perturbation expansion in $\varepsilon$ does not provide a good ansatz for applying the implicit function theorem since the nonlinearities play a major role in determining the relevant approximation, which also needs to be "correct" to all orders in $\varepsilon$. We overcome these two points by proving Fredholm properties for the linearization in appropriate Kondratiev spaces and using a refined ansatz for the approximate solution, which obtained using matched asymptotics., 39 pages, 1 figure

Hybrid electric technology is becoming important in military vehicles due to its features and benefits such as onboard electric power, silent mobility, and improved performance. The desired mobility attributes of a military tracked vehicle were considered in this study to design a series hybrid electric powertrain for the same. This involved the power and torque analysis of vehicle performance using fundamental governing equations. From analysis of performance requirements, operating terrains and powertrain components characteristics, component sizing of a series hybrid electric powertrain for a military tracked vehicle was done with single drive and dual drive configurations.

This paper focuses on the design of controllers that ensure string stability in Heavy Commercial Road Vehicle (HCRV) platoons. While dealing with controller design for HCRVs, due to the sluggish nature of a pneumatic brake actuation system, the actuator dynamics has to be considered explicitly. Sliding Mode Control (SMC), which is a widely accepted control strategy for string stability has been considered and the effects of actuator dynamics during deceleration as well as acceleration phase were analysed. It was observed that, the actuation delays caused string instability using the designed SMC controller. In this context, a Variable Time Headway (VTH) based controller redesign that is capable of ensuring string stability despite actuation delays is presented. The efficacy of the presented VTH policy has been evaluated through simulations and it was observed that this policy could make the platoon string stable while accounting for real world actuator dynamics.

A rear-end collision avoidance system (RECAS) could reduce accidents by assisting drivers during emergencies through autonomous braking. If the decision to intervene is made too early, the intervention can become a disturbance to the driver and if the decision is made too late, the safety benefits of the system will be reduced. Hence, proper threat assessment is important to make a decision for intervention in a RECAS. In this study, a new threat assessment measure using a varying time headway has been proposed to develop a rear-end collision avoidance algorithm (RECAA) for heavy commercial road vehicles in heterogeneous traffic. The proposed varying time headway depends on the type of lead vehicle, host vehicle load conditions, road conditions and relative longitudinal speed. The developed RECAA was implemented in a hardware-in-loop experimental setup that is equipped with the vehicle dynamic simulation software, IPG/TruckMaker® and tested for vehicle following scenarios using different types of lead vehicles and host vehicle loading conditions. The results showed that the proposed varying time headway improved the RECAA by activating the host vehicle's brake system at different time instants based on the type of lead vehicle and thereby preventing the unintended early brake intervention of RECAS.

Hybrid electric vehicles are emerging technologies that are considered as eco-friendly alternative solutions to internal combustion engine–driven vehicles. This paper proposes a modified hybrid electric vehicle powertrain system that addresses the shortcomings of a series hybrid electric vehicle powertrain. The proposed configuration replaces the conventional generator of a series hybrid electric vehicle with an integrated starter generator that supports the traction motor of the vehicle during acceleration and peak torque requirements and maintains the state of charge of the batteries to provide an extended electric range of the vehicle. The work done in this paper can be categorized into two stages. The first stage is the methodical development of the powertrain in terms of initial parameter matching and sizing of the vehicle components by considering the fundamentals of longitudinal vehicle dynamics. The second stage describes the optimization of the proposed configuration to meet the design objective of maximizing fuel economy subjected to a set of vehicle performance constraints. The performance of the proposed powertrain was evaluated and compared with a series hybrid electric vehicle powertrain for an on-road Indian driving cycle using AVL CRUISE, which is a commercially available software for the study and analysis of road vehicle powertrains. Result analysis during initial parameterization showed a reduction in gross vehicle weight of the proposed configuration by 244 kg (1.5%) and an improvement in the average operating efficiency of the traction motor by around 11%, when compared to a series hybrid electric vehicle. Furthermore, the optimization results for the proposed configuration established an improvement in the fuel economy by 21% while meeting vehicle performance requirements.

With increasing focus on addressing fossil fuel shortage and harmful automotive emissions, there has been a growing interest in hybrid electric and pure electric vehicles. A hybrid electric vehicle is driven by a combination of an internal combustion engine and an electric motor. The changes in the powertrain components result in changes in vehicle mass and mass distribution that affects the location of the vehicle’s centre of gravity amongst other things. Hence, a hybrid vehicle may not possess the same handling performance as a conventional internal combustion engine driven vehicle. This research work focuses on comparing the handling performance of a conventional engine driven vehicle and a hybrid electric vehicle. The bicycle dynamic model has been used to characterize the cornering dynamics of these two vehicles and the Mimuro plot has been used to analyze their handling characteristics. A sensitivity analysis has been carried out with respect to centre of gravity location and the cornering stiffness of the tires. An approach has been proposed to obtain comparable cornering characteristics in the hybrid vehicle as compared to the engine driven vehicle.