The Impact of HVAC on the Development of Autonomous and Electric Vehicle Concepts

Automation and electrification are changing vehicles and mobility. Whereas electrification is mainly changing the powertrain, automation enables the rethinking of the vehicle and its applications. The actual driving range is an important requirement for the design of automated and electric vehicles, especially if they are part of a fleet. To size the battery accordingly, not only the consumption of the powertrain has to be estimated, but also that of the auxiliary users. Heating Ventilation and Air Conditioning (HVAC) is one of the biggest auxiliary consumers. Thus, a variable HVAC model for vehicles with electric powertrain was developed to estimate the consumption depending on vehicle size and weather scenario. After integrating the model into a tool for autonomous and electric vehicle concept development, various vehicle concepts were simulated in different weather scenarios and driving cycles with the HVAC consumption considered for battery sizing. The results indicate that the battery must be resized significantly depending on the weather scenario to achieve the same driving ranges. Furthermore, the percentage of HVAC consumption is in some cases higher than that of the powertrain for urban driving cycles, due to lower average speeds. Thus, the HVAC and its energy demand should especially be considered in the development of autonomous and electric vehicles that are primarily used in cities.

An Automatic Conflict Detection Framework for Urban Intersections Based on an Improved Time Difference to Collision Indicator

Urban road intersections are one of the key components of road networks. Due to complex and diverse traffic conditions, traffic conflicts occur frequently. Accurate traffic conflict detection allows improvement of the traffic conditions and decreases the probability of traffic accidents. Many time-based conflict indicators have been widely studied, but the sizes of the vehicles are ignored. This is a very important factor for conflict detection at urban intersections. Therefore, in this paper we propose a novel time difference conflict indicator by incorporating vehicle sizes instead of viewing vehicles as particles. Specially, we designed an automatic conflict recognition framework between vehicles at the urban intersections. The vehicle sizes are automatically extracted with the sparse recurrent convolutional neural network, and the vehicle trajectories are obtained with a fast-tracking algorithm based on the intersection-to-union ratio. Given tracking vehicles, we improved the time difference to the conflict metric by incorporating vehicle size information. We have conducted extensive experiments and demonstrated that the proposed framework can effectively recognize vehicle conflict accurately.

Nanosuspension a Promising Tool for Solubility Enhancement: A Review

Nanotechnology is the science that manages the interaction that happens at sub-atomic level and of nano length scale size. Nano alludes to the molecule size in between of 1-1000nm. Nanosuspensions are going under nanotechnology. A drug Nanosuspension is characterized as finely colloid, biphasic, scattered strong medication particles in a fluid vehicle, size under 1 μm settled by surfactants and polymers arranged by reasonable techniques for drug conveyance applications. It gives effective conveyance of hydrophobic drugs and expands the bioavailability. Nanosuspension is an alluring and promising innovation to improve helpless solvency and bioavailability of the drugs. This survey article depicts the strategies for development, techniques and stability related study of nanosuspensions in the field of drug sciences.

SAV Operations on a Bus Line Corridor: Travel Demand, Service Frequency, and Vehicle Size

Before shared automated vehicles (SAVs) can be widely adopted, they are anticipated to be implemented commercially in confined regions or fixed routes where the benefits of automation can be realized. SAVs have the potential to operate in a traditional transit corridor, replacing conventional transit vehicles, and have frequent interactions with riders and other vehicles sharing the same right of way. This paper microsimulates SAVs’ operation on a 6.5-mile corridor to understand how vehicle size and attributes of such SAV-based transit affect traffic, transit riders, and system costs. The SUMO (Simulation of Urban MObility) platform is employed to model microscopic interactions among SAVs, transit passengers, and other traffic. Results show that the use of smaller, but more frequent, SAVs leads to reduced passenger waiting times but increased vehicle travel times. More frequent services of smaller SAVs do not, in general, significantly affect general traffic due to shorter dwell times. Overall, using smaller SAVs instead of the large 40-seat SAVs can reduce system costs by up to 4% while also reducing passenger waiting times, under various demand levels and passenger loading factors. However, the use of 5-seat SAVs does not always have the lowest system costs.

The Pragmatic Meanings of Car Stickers in Jordan

This study is aimed at investigating the illocutionary forces of car stickers in Jordan as an under-researched area of Arabic pragmatics. The study is based on authentic data collected over a year as found displayed on cars in the south, mid and north of Jordan. The data collected were found to display a wide range of social, romantic and economic functions including displaying vehicle size and brand, protection against envy, disappointment and betrayal, giving advice, displaying love and romantic challenges, crises and car stickers aimed at attracting others’ attention. Stickers used as a protective measure against evil eye were found to be the most frequently used stickers in our data (32.65%). Though car stickers are equated with amusement and humor, they are used nowadays as a tool to indirectly criticize social, economic and political crises, and this could reflect the social and economic challenges of life. The overwhelmingly rhythmic car stickers examined in the study were found to be instances of decodable expressions whose overall meanings could be recovered by sticker readers.

Genetic Algorithm-Based Optimal Design of a Rolling-Flying Vehicle

This work describes a design optimization framework for a rolling-flying vehicle consisting of a conventional quadrotor configuration with passive wheels. For a baseline comparison, the optimization approach is also applied for a conventional (flight-only) quadrotor. The vehicle range is maximized using a hybrid multi-objective genetic algorithm in conjunction with multi-physics system models. A low Reynolds-number blade element momentum theory aerodynamic model is used with a brushless DC motor model, a terramechanics model, and a vehicle dynamics model to simulate the vehicle range under any operating angle-of-attack and forward velocity. To understand the tradeoff between vehicle size and operating range, variations in Pareto-optimal designs are presented as functions of vehicle size. A sensitivity analysis is used to better understand the impact of deviating from the optimal vehicle design variables. This work builds on current approaches in quadrotor optimization by leveraging a variety of models and formulations from literature and demonstrating the implementation of various design constraints. It also improves upon current ad-hoc rolling-flying vehicle designs created in previous studies. Results show the importance of accounting for oft-neglected component constraints in the design of high range quadrotor vehicles. The optimal vehicle mechanical configuration is shown to be independent of operating point, stressing the importance of a well-matched, optimized propulsion system. By emphasizing key constraints that affect the maximum and nominal vehicle operating points, an optimization framework is constructed that can be used for RFVs and conventional multi-rotors.

Assessment of Discretionary Lane-Changing Decisions using a Random Parameters Approach with Heterogeneity in Means and Variances

Lane-changing maneuvers on highways may cause capacity drops, create shock waves, and potentially increase collision risks. Properly managing lane-changing behavior to reduce these adverse impacts requires an understanding of their determinants. This paper investigates the determinants of lane changing in congested traffic using a next generation simulation dataset. A random parameters binary logit model with heterogeneity in means and variances was estimated to account for unobserved heterogeneity in lane-changing behavior across vehicles. Estimation results show that average headway, the original lane of the vehicle, driver acceleration/deceleration behavior, and vehicle size all significantly influence lane-changing probabilities. It was further found that the effect of vehicle size varied significantly across observations, that the mean of this variation decreased with increasing average headway, and the variance increased with increasing driver acceleration/deceleration. These empirical findings provide interesting new evidence on the determinants of lane changing, which can be used in traffic flow models to better replicate and predict traffic flow.

Statistical analysis of the vehicles main dimensions variability on public roads

The aim of the study is to obtain the parameters of vehicle size variability and evaluate the convergence of empirical data with the modeling results using distribution functions. The main results of the study consist in obtaining statistical parameters that characterize the variability of vehicle sizes, and testing hypotheses about whether the empirical distribution belongs to one of the theoretical distribution functions. The significance of the obtained results lies in the possibility of using the most suitable theoretical functions of probability distributions of random variables that characterize the variability of vehicle sizes in algorithms for estimating the resource parameters of steel spans of road bridges.