Browse Topic: Roads and highways
Commercial success of the autonomous truck may be closer than we think. The last half decade has brought the best of times and worst of times for the commercial autonomous truck sector. While some perceived pillars of this technology have fallen, others have continued to carry the weight of bringing driverless trucks closer to commercialization. Consolidation was inevitable given the volume of speculative investment that brought a tidal wave of capital to various startups. Even so, some industry experts and Wall Street investors wondered if the autonomous truck sector might collapse entirely.
This paper presents the design and implementation of a Semi-Autonomous Light Commercial Vehicle (LCV) capable of following a person while performing obstacle avoidance in urban and controlled environments. The LCV leverages its onboard 360-degree view camera, RTK-GNSS, Ultrasonic sensors, and algorithms to independently navigate the environment, avoiding obstacles and maintaining a safe distance from the person it is following. The path planning algorithm described here generates a secondary lateral path originating from the primary driving path to navigate around static obstacles. A Behavior Planner is utilized to decide when to generate the path and avoid obstacles. The primary objective is to ensure safe navigation in environments where static obstacles are prevalent. The LCV's path tracking is achieved using a combination of Pure Pursuit and Proportional-Integral (PI) controllers. The Pure Pursuit controller is utilized as lateral control to follow the generated path, ensuring
Higher road noise is perceived in the cabin when the test vehicle encounters road irregularities like bump or pothole in the public roads. The transfer of transient road inputs inside the body caused objectionable cabin noise. Measurements are conducted at different road surfaces to identify the patch where the objective data well correlated with the noise measured at the public road. Wavelet analysis is carried out to identify the frequency zones since the events are transient in nature. TPA is carried out in time domain to identify the nature of the noise and the dominant path through which the transient road forces are transferring inside the body. Based on the outcome of TPA, various countermeasures like reduction of dynamic stiffness of suspension bushes, TMDs on the path are proposed to reduce the structure borne noise. Criteria which need to be considered for reduction of cabin noise due to transient road inputs is also discussed.
Growing population in Indian cities has led to packed roads. People need a quick option to commute for both personal trips and business needs. The 2-3 Wheel Combination Vehicle is a new, modular solution that switches between a two-wheeler (2W) and a three-wheeler (3W). Hero has designed SURGE S32 to be a sustainable and flexible transportation option. It is world’s first class changing vehicle. The idea is to use a single vehicle for zipping through city traffic, making deliveries, or earning an income. Manufactured to deal with the challenges of modern life, this dual-battery convertible vehicle can easily transform from a two-wheeler to a three-wheeler and vice versa within three minutes. The Surge S32 is a versatile vehicle that replaces the need for multiple specialised vehicles. By lowering the number of vehicles on the road, it decreases road congestion, reduces emissions, and improves livelihoods. It powers by electricity, ensuring sustainability in all aspects. The current
With the advent of digital displays in driver cabins in commercial vehicles, drivers are being offered many features that convey some useful or critical information to drivers or prompt the driver to act. Due to the availability of a vast number of features, drivers face decision fatigue in choosing the appropriate features. Many are unaware of all available functionalities displayed in the Human Machine Interface (HMI) System, leading to a bare minimum usage or complete neglect of helpful features. This not only affects driving efficiency but also increases cognitive load, especially in complex driving scenarios. To alleviate the fatigue faced by drivers and to reduce the induced lethargy to choose appropriate features, we propose an AI driven recommendation agent/system that helps the driver choose the features. Instead of manually choosing between multiple settings, the driver can simply activate the recommendation mode, allowing the system to optimize selections dynamically. The
Nowadays, customers expect excellent cabin insulation and superior ride comfort in electric vehicles. OEMs focus on fine tuning the suspension system in electric vehicle to isolate the road induced shocks which finally offers superior ride quality. This paper focuses on enhancing the ride comfort by reducing the road excitation which originates mainly due to road inputs. Higher steering wheel vibration is perceived on the test vehicle on rough road surfaces. To determine the predominant force transfer path, Multi reference Transfer Path Analysis (MTPA) is performed on the front and rear suspension. Based on the finding from MTPA, various recommendations are explored and the effect of each modification is discussed. Apart from this, Operational Deflection Shape (ODS) analysis is used to determine the deflection shape on the entire steering system . Based on ODS findings, recommendations like dynamic stiffness improvements on the steering column and steering wheel are explored and the
Ensuring the safety and efficiency of autonomous vehicles in increasingly complex, dynamic, and structured road environments remains a key challenge. While traditional optimization-based approaches can provide safety guarantees, they often struggle to meet real-time requirements due to high computational complexity. Concurrently, although Control Barrier Functions (CBFs) can ensure instantaneous safety with minimal intervention, their inherent locality makes it difficult to consider global task objectives, potentially leading to mission failure in complex scenarios like lane-change obstacle avoidance. To address this trade-off between safety and mission completion, this paper proposes a hierarchical switching CBF safety framework. The core of this framework is to decompose complex lane-change tasks into multiple logical phases and to activate specialized, pre-designed CBF constraint sets via a top-level logic controller. Finally, we demonstrate the feasibility and safety of the
A smart highway tunnels lighting system based on the technology of cloud platform and Internet of Things(IoTs) has been designed to address the common problems of high energy consumption and low level of intelligence in China's highway tunnel lighting system. The highway tunnel lighting system consists of four layers of architecture: platform management layer, local management layer, middle layer and terminal layer. The system collects real-time brightness, lamp brightness, traffic volume and other data outside the tunnel through various sensors deployed on site, and then uploads the collected data to the main controller through LoRa IoTs. The main controller combines the brightness calculation method of the lighting design rules to control the brightness of the tunnel lighting in real time, achieving real-time adjustment of the brightness of the tunnel LED lights and the brightness outside the tunnel, and realizing a safe and energy-saving lighting effect of "lights on when the car
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