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Understanding left-turn vehicle-pedestrian accident mechanisms is critical for developing accident-prevention systems. This study aims to clarify the features of driver behavior focusing on drivers’ gaze, vehicle speed, and time to collision (TTC) during left turns at intersections on left-hand traffic roads. Herein, experiments with a sedan and light-duty truck (< 7.5 tons GVW) are conducted under four conditions: no pedestrian dummy (No-P), near-side pedestrian dummy (Near-P), far-side pedestrian dummy (Far-P) and near-and-far side pedestrian dummies (NF-P). For NF-P, sedans have a significantly shorter gaze time for left-side mirrors compared with light-duty trucks. The light-duty truck’s average speed at the initial line to the intersection (L1) and pedestrian crossing line (L0) is significantly lower than the sedan’s under No-P, Near-P, and NF-P conditions, without any significant difference between any two conditions.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Proportional integral derivative (PID) control technique is a famous and cost-effective control strategy, in real implementation, applied in various engineering applications. Also, the ant colony optimization (ACO) algorithm is extensively applied in various industrial problems. This paper addresses the usage of the ACO algorithm to tune the PID controller gains for a semi-active heavy vehicle suspension system integrated with cabin and seat. The magnetorheological (MR) damper is used in main suspension as a semi-active device to enhance the ride comfort and vehicle stability. The proposed semi-active suspension consists of a system controller that calculate the desired damping force using a PID controller tuned using ACO, and a continuous state damper controller that predict the input voltage that is required to track the desired damping force.

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.

Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries.

Determining occupant kinematics in a vehicle crash is essential when understanding injury mechanisms and assessing restraint performance. Identifying contact marks is key to the process. This study was conducted to assess the ability to photodocument the various fluids on different vehicle interior component types and colors with and without the use of ultraviolet (UV) lights. Biological (blood, saliva, sweat and skin), consumable and chemical fluids were applied to vehicle interior components, such as seatbelt webbing, seat and airbag fabrics, roof liner and leather steering wheel. The samples were photodocumented with natural light and UV light (365 nm) exposure immediately after surface application and again 14 days later. The review of the photos indicated that fabric type and color were important factors. The fluids deposits were better visualized on non-porous than porous materials. For example, blood was better documented on curtain airbags than side or driver airbags.

Multiple areas in the U.S. continue to struggle with achieving National Ambient Air Quality Standards for ozone. These continued issues highlight the need for further reductions in NOX emission standards in multiple industry sectors, with heavy-duty on-highway engines being one of the most important areas to be addressed. Starting in 2014, CARB initiated a series of technical demonstration programs aimed at examining the feasibility of achieving up to a 90% reduction in tailpipe NOX, while at the same time maintaining a path towards GHG reductions that will be required as part of the Heavy-Duty Phase 2 GHG program. These programs culminated in the Stage 3 Low NOX program, which demonstrated low NOX emissions while maintaining GHG emissions at levels comparable to the baseline engine.

Reconstruction of inline crashes between vehicles with a low closing speed, so-called “low speed” crashes, continues to be a class of vehicle collisions that reconstructionists require specific methods to handle. In general, these collisions tend to be difficult to reconstruct due primarily to the lack of, or limited amount of, physical evidence available after the crash. Traditional reconstruction methods such as impulse-momentum (non-residual damage based) and CRASH3 (residual damage based) both are formulated without considering tire forces of the vehicles. These forces can be important in this class of collisions. Additionally, the CRASH3 method depends on the use of stiffness coefficients for the vehicles obtained from high-speed crash tests. The question of the applicability of these (high-speed) stiffness coefficients to collisions producing significantly less deformation than experimental crashes on which they are generated, raises questions of the applicability.

The basic needs of people are met by the building, fabric, and farming sectors. In addition, the automobile industry significantly contributes to human mobility and is essential to India’s economic expansion. There are numerous research strategies available to improve the bus body building industries. Several investigative approaches for enhancing bus body building industries are available. However, several of these studies merely look at it from the perspective of shop floor activity. Accordingly, when it comes to the execution of process design approaches, there is little practical evidence for accepting Gemba kaizen’s attitude. Hence, the purpose of this article is to present a continuous improvement redesign framework tailored to a specific bus body building industrial sector. The proposed model is structured after a critical examination of Gemba and Kaizen.

Efficient transportation for carrying heavy loads is a common challenge across various applications, from supermarkets to industrial purposes. Conventional trolleys often fall short when loaded with heavy cargo, resulting in increased exertion and diminished productivity. Moreover, these challenges can adversely affect posture and lumbar spine health, especially for elder people and persons with cervical problems. There is a need for more user-friendly, ergonomic, and space-efficient solutions. This project addresses these challenges through an innovative design that encompasses various aspects of trolley functionality, including the study of comfort, wheel selection, and material considerations, drawing from ergonomic research. Multiple methods are employed to optimize the trolley’s dimensions to improve its overall performance. The trolley’s design features a collapsible basket for the transport of smaller-sized items and a base frame for larger goods and luggage.

An agricultural tractor is often modified for special farming applications such as horticulture where the standard design is not suitable or accessible. In such cases, farm equipment manufacturers are demanded frugal and cost effect Engineered farming solutions. One such design is the innovative High Ground Clearance Tractor (HGCT) kit offered to increase the Tractor height without damaging the crop during farming operations. In this paper, the author proposes a durability assessment method to evaluate the HGCT kit attachments to meet the durability criteria. Road load data acquisition is done to measure the acceleration and strain levels for various horticulture operations such as tillage, spraying and transportation. Actual operating conditions are simulated with the help of four poster durability setups inside the lab which helps to reduce the field testing for design iterations.

For commercial vehicles, reliability is key since the vehicle is typically linked to the daily earnings of the owner. To ensure continuous vehicle operation, early diagnostics of critical issues and proactive maintenance are important. However, an electric vehicle is a complex and dynamic system consisting of numerous components interacting with each other and with external environments such as road conditions, traffic, weather, and driving behavior. Thus, vehicle operation and performance are highly contextual and for identifying an abnormal operation (diagnostics) the solution must consider the conditions under which it is driven. To address this, the paper proposes an AI-based digital twin of an electric three-wheeler vehicle. TabNet a deep-learning based model is used to learn and generate near-ideal vehicle behavior. The focus of the paper is motor subsystem. The model is trained using appx 200 vehicles first 1500 km driven data.

This paper describes the after-treatment technology that could be used to meet a future BS-VII standard, considering close-coupled SCR (cc-SCR) to help start NOx conversion earlier. Both active (Cu/Fe-SCR based) and passive (V-SCR based) systems have the potential to meet emission limits. V-SCR may be considered in the rear position because V-SCR shows a fast response with very low N2O formation. Next-gen V-SCR technology shows significantly improved performance and durability closer to Cu-SCR. The steady-state NOx conversions over Next-Gen V-SCR were better than BS-VI V-SCR in both fresh and aged-580°C/100h conditions. High durability was also observed after engine aging of 1000h (WHTC + high load). Another big challenge in BS VII could be the PN10 requirement. With enhanced filtration coating (EFC) technology, PN emissions drop drastically in comparison to Euro VI reference without EFC to meet a future BS VII.

India striving for carbon neutrality influences futures powertrain architecture of commercial vehicles. The use of CO2-free drives as battery electric have been demonstrated for various applications. The productivity still is a challenge due to missing high power charging infrastructure or limited range. This draws the attention to the use of sustainable fuels due to lower refueling times. The hydrogen engine got highest attention in the last couple of years. For markets as the EU the driver for hydrogen is the CO2 emission reduction, whereas for markets as India hydrogen offers the additional opportunity for more independence from fossil imports. Different OEMs all over the world have converted diesel engines to hydrogen operation with strong focus on performance and emission demonstration, so far with limited technology readiness of different key components.

The commercial vehicle sector (especially trucks) has major role in economic growth of a nation. With improving infrastructure, increasing number of commercial vehicles and growing amount of Vulnerable Road Users (VRUs) on roads, accidents are also increasing. As per RASSI (Road Accident Sampling System India) FY2016-21 database, commercial vehicles are involved in 43% of total accidents on Indian roads. One of the major causes of these accidents is Driver Drowsiness and Inattention (DDI) (approx. 10% contribution in total accidents). This paper describes novel driver-in-loop performance assessment methodology for comprehensive verification of Driver Monitoring System (DMS) for commercial vehicle application. Novelty lies in specification of test subjects, driving styles and variety of road traffic scenarios for verification of DMS system. Test setup is made modular to cater to different platform environments (Heavy, Intermediate, Light) with minor modifications.

For safety towards pedestrians and other road-vehicles, sound alert systems, like horns, have been in use since development of Automobiles. On the same line but with special purpose of preventing a Driver to sleep in a running vehicle, a Driver Monitoring System [DMS] is recently developed. For Electric Vehicles which are very quiet during starting and driving till 20 km/hr, Acoustic Vehicle Alert System (AVAS) is deployed in Europe and likely to be implemented in India soon. For all these Alert Devices, there are Standard Regulations across the world: ECE R-28 for Horns and ECE R-138 for AVAS. They, however, define only lower and upper dBA limits of the sound radiated by them. For DMS, no such regulation exists till today. With this, there has been a long time debate on what an optimal dBA level should be there, for all road-users as well as for vehicle- users inside the cabin.

A bus is integral part of public transportation in both rural and urban areas. It is also used for scheduled transport, tourism, and school transport. Buses are the common mode of transport all over the world. The growth in economy, the electrification of public transport, demand in shared transport, etc., is leading to a surge in the demand for buses and accelerating the overall growth of the bus industry. With the increased number of buses, the issue of safety of passengers and the crew assumes special importance. The comfort of driver and passenger in the vehicle involves the vibration performance and therefore, the structural integrity of buses is critically important. Bus safety act depicts the safety and comfort of bus operations, management of safety risks, continuous improvement in bus safety management, public confidence in the safety of bus transport, appropriate stakeholder involvement and the existence of a safety culture among bus service providers.

Road infrastructure in India is being upgraded at a rapid pace. Quality of life of people has also improved significantly in the last decade. Such trends have significantly impacted design of commercial vehicles and vehicular systems in the country. This paper deals with the design and development of a modern futuristic instrument panel for trucks. Methodology to arrive at product features and solutions which retain their novelty and appeal for a longer term has also been illustrated. Regulatory scenario, modularity, HMI, Perceived Quality, Driver Comforts, evolving technologies, trends and materials are some of the considerations which have discussed in detail. International benchmarks and customer requirement have been analyzed for setting Performance targets. A digital approach for evaluating these considerations evolved during the design and development process has been elaborated in detail.

The automotive world is rapidly moving towards achieving shorter lead time using high-end technological solutions by keeping up with day-to-day advancements in virtual testing domain. With increasing fidelity requirements in test cases and shorter project lead time, the virtual testing is an inevitable solution. This paper illustrates method adopted to achieve best approximation to emulate driver behavior with 1-D (one dimensional) simulation based modeling approach. On one hand, the physical testing needs huge data collection of various parameters using sensors mounted on the vehicle. The vehicle running on road provides the real time data to derive durability test specifications. One such example includes developing duty cycle for powertrain durability testing using Road Torque Data Collection (RTDC) technique. This involves intense physical efforts, higher set-up cost, frequent iterations, vulnerability to manual errors and causing longer test lead-time.

The passive safety performance of a child seat is modulated by the design features of the child seat and the vehicle interior. For example, in the rear-facing configuration, the child seat impacting front structures increases the head injury risk during a frontal crash. Therefore, this study evaluates the effectiveness of the load leg countermeasure in improving the child seat's overall kinematics and its capability to prevent the secondary impact on the vehicle interior structure in a severe frontal crash scenario. An in-depth, real-world crash investigation involving a properly installed rear-facing child seat impacting the center console was selected for the study where the infant sustained a severe brain injury. In addition, this crash is employed to choose the crash parameters for evaluating the effectiveness of the load leg countermeasure in a similar scenario.