In recent years, autonomous vehicles (AVs) have been receiving increasing attention from investors, automakers, and academia due to the envisioned potentials of AVs in enhancing safety, reducing emissions, and improving comfort. The crucial task in AV development boils down to perception and navigation. The research is underway, in both academia and industry, to improve AV’s perception and navigation and reduce the underlying computation and costs. This article proposes a model predictive control (MPC)-based local path-planning method in the Cartesian framework to overcome the long computation time and lack of smoothness of the Frenet method. A new equation is proposed in the MPC cost function to improve the safety in path planning. In this regard, an AV is built based on a 2015 Nissan Leaf S by modifying the drive-by-wire function and installing environment perception sensors and computation units. The custom-made AV then collected data in Norman, Oklahoma, and assisted in the

Arjmandzadeh, Ziba, Abbasi, Mohammad Hossein, Wang, Hanchen, Zhang, Jiangfeng, Xu , Bin

Discretization-Based Semi-Active Suspension Control Using Road Preview Data

2024-01-5087

08/30/2024

While semi-active suspensions help improve the ride comfort and road-holding capacity of the vehicle, they tend to be reactive and thus leave a lot of room for improvement. Incorporating road preview data allows these suspensions to become more proactive rather than reactive and helps achieve a higher level of performance. A lot of preview-based control algorithms in literature tend to require high computational effort to arrive at the optimal parameters thus making it difficult to implement in real time. Other algorithms tend to be based upon lookup tables, which classify the road input into different categories and hence lose their effectiveness when mixed types of road profiles are encountered that are difficult to classify. Thus, a novel MPC (model predictive control)-based algorithm is developed which is easy to implement online and more responsive to the varying road profiles that are encountered by the vehicle. The efficacy of the algorithm is tested against a numerical methods

Thamarai Kannan, Harish Kumar, Ferris, John B.

A Multi-Target Urban Transportation Structure Model under the Optimal Capacity Limitation of Road Networks

13-06-01-0003

08/10/2024

The construction of urban transportation infrastructures on the supply side is severely limited due to the extensive development of central urban land. Therefore, optimizing the traffic structure with limited resources is particularly important. The work used the optimum capacity of the road network as one of the constraints. Multi-objective linear programming was used to establish the traffic structure model. The total travel volume, energy consumption, travel quality, and social cost were selected as the optimization objectives of the urban transportation structure. The influencing factors of infrastructure capacity (e.g., total travel demand, optimal capacity of road network, slow traffic capacity, and parking lot capacity) were selected as the constraint conditions in optimizing urban transportation structure. The objective was to develop an optimization model considering the constraints of urban infrastructure. Finally, the optimal traffic structure was compared with the actual

Zhang, Jinwei, Gao, Jianping

Optimization of Dynamic Wireless Charging Systems and Economic Feasibility Assessment of Electrified Roads

14-14-01-0001

06/12/2024

Dynamic wireless charging (DWC) systems can make up electrified roads (eRoads) on which electricity from the grid is supplied to electric vehicles (EVs) wirelessly while the EVs travel along the roads. Electrification of roads contributes to decarbonizing the transport sector and offers a strong solution to high battery cost, range anxiety, and long charging times of EVs. However, the DWC eRoads infrastructure is costly. This article presents a model to minimize the infrastructure cost so that the deployment of eRoads can be economically more feasible. The investment for eRoad infrastructure consists of the costs of various components including inverters, road-embedded power transmitter devices, controllers, and grid connections. These costs depend on the traffic flow of EVs. The configuration and deployment strategy of the proposed eRoads in Southeastern Canada are designed with optimized charging power and DWC coverage ratio to attain the best cost-effectiveness. Well-designed

Qiu, Kuanrong, Ribberink, Hajo, Entchev, Evgueniy

Infrastructure Enablers for Automation: Vol. 2

EPRCOMPV102023

05/03/2024

Coyner, Kelley, Bittner, Jason, Lambermont, Serge, De Boer, Niels

Driving Behavior during Left-Turn Maneuvers at Intersections on Left-Hand Traffic Roads

2023-22-0007

04/17/2024

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. The TTC for sedans is significantly shorter than that for

Matsui, Yasuhiro, Narita, Masashi, Oikawa, Shoko

Control Strategy of Semi-Active Suspension Based on Road Roughness Identification

10-08-02-0013

04/13/2024

Taking the semi-active suspension system as the research object, the forward model and inverse model of a continuous damping control (CDC) damper are established based on the characteristic test of the CDC damper. A multi-mode semi-active suspension controller is designed to meet the diverse requirements of vehicle performance under different road conditions. The controller parameters of each mode are determined using a genetic algorithm. In order to achieve automatic switching of the controller modes under different road conditions, a method is proposed to identify the road roughness based on the sprung mass acceleration. The average of the ratio between the squared sprung mass acceleration and the vehicle speed within a specific time window is taken as the identification indicator for road roughness. Simulation results show that the proposed road roughness identification method can accurately identify smooth roads (Class A–B), slightly rough roads (Class C), and severely rough roads

Feng, Jieyin, Yin, Zhihong, Xia, Zhao, Wang, Weiwei, Shangguan, Wen-Bin, Rakheja, Subhash

Regenerative Energy Control Technology of Charging Vehicles in Electric Road System

2024-01-2171

04/09/2024

This Electric Road System was devised that would provide electric power to EVs directly from the infrastructure so that EVs could undergo intermittent charging while driving. This system is a conductive dynamic charging system that operates from the side of the vehicle (roadside), and research has been underway on the application of this approach to passenger cars and race cars. This paper focused on resolving issues with freight vehicles, which account for most of the CO2 emissions in the transportation sector. This Electric Road System that operates by contact from the roadside was applied to heavy-duty trucks, which have been considered a challenge to convert to EVs, and at the same time the infrastructure technology was also expanded and evolved. And verification tests using actual vehicles were conducted for regenerative energy absorption control of a charging vehicle while driving. The results confirmed that this control system appropriately controls the distribution of power

Tajima, Takamitsu, Abe, Hiroyuki

Signal Control of Urban Expressway Ramp Based on Reinforcement Learning

2024-01-2875

04/09/2024

With economic development and the increasing number of vehicles in cities, urban transport systems have become an important issue in urban development. Efficient traffic signal control is a key part of achieving intelligent transport. Reinforcement learning methods show great potential in solving complex traffic signal control problems with multidimensional states and actions. Most of the existing work has applied reinforcement learning algorithms to intelligently control traffic signals. In this paper, we investigate the agent-based reinforcement learning approach for the intelligent control of ramp entrances and exits of urban arterial roads, and propose the Proximal Policy Optimization (PPO) algorithm for traffic signal control. We compare the method controlled by the improved PPO algorithm with the no-control method. The simulation experiments used the open-source simulator SUMO, and the results showed that the reinforcement learning control ramp technique increases the average

Ouyang, Chen, Zhan, Zhenfei, Qian, Liuzhu, Zou, Jie

Study of Indian Road Traffic Accident Characteristics Using Clustering Analysis

2024-01-2754

04/09/2024

In 2021, 412,432 road accidents were reported in India, resulting in 153,972 deaths and 384,448 injuries. India has the highest number of road fatalities, accounting for 11% of the global road fatalities. Therefore, it is important to explore the underlying causes of accidents on Indian roads. The objective of this study is to identify the factors inherent in accidents in India using clustering analysis based on self-organizing maps (SOM). It also attempts to recommend some countermeasures based on the identified factors. The study used Indian accident data collected by members of ICAT-ADAC (International Centre for Automotive Technology - Accident Data Analysis Centre) under the ICAT-RNTBCI joint project approved by the Ministry of Heavy Industries, Government of India. 210 cases were collected from the National Highway between Jaipur and Gurgaon and 239 cases from urban and semi-urban roads around Chennai were used for the analysis. Based on this study, the following results were

Vimalathithan, Kulothungan, Rao K M, Pranesh, Vallabhaneni, Pratapnaidu, Selvarathinam, Vivekraj, Manoharan, Jeyabharath, Pal, Chinmoy, Padhy, Sitikantha, Joshi, Madhusudan

Game-Theoretic Lane-Changing Decision-Making Methods for Highway On-ramp Merging Considering Driving Styles

2024-01-2327

04/09/2024

Driver's driving style has a great impact on lane changing behavior, especially in scenarios such as freeway on-ramps that contain a strong willingness to change lanes, both in terms of inter-vehicle interactions during lane changing and in terms of the driving styles of the two vehicles. This paper proposes a study on game-theoretic decision-making for lane-changing on highway on-ramps considering driving styles, aiming to facilitate safer and more efficient merging while adequately accounting for driving styles. Firstly, the six features proposed by the EXID dataset of lane-changing vehicles were subjected to Principal Component Analysis (PCA) and the three principal components after dimensionality reduction were extracted, and then clustered according to the principal components by the K-means algorithm. The parameters of lane-changing game payoffs are computed based on the clustering centers under several styles. Secondly, a neural network model is designed based on the Matlab

Du, Hang, Xu, Nan, Zhang, Zeyang

Integrated Road Information Perception Framework for Road Type Recognition and Adaptive Evenness Assessment

2024-01-2041

04/09/2024

With the rapid advancement in intelligent vehicle technologies, comprehensive environmental perception has become crucial for achieving higher levels of autonomous driving. Among various perception tasks, monitoring road types and evenness is particularly significant. Different road categories imply varied surface adhesion coefficients, and the evenness of the road reflects distinct physical properties of the road surface. This paper introduces a two-stage road perception framework. Initially, the framework undergoes pre-training on a large annotated drivable area dataset, acquiring a set of pre-trained parameters with robust generalization capabilities, thereby endowing the model with the ability to locate road areas in complex regions. Subsequently, guided by a mask attention mechanism, the model undergoes fine-tuning on a smaller dataset annotated with road type regions using a weighted joint loss function, effectively addressing issues of class imbalance and limited labeled samples

Wei, Kai, Yu, Liangyao, xu, Feng

Testing and Analysis of Riding a Road Bicycle over an Artificial Pothole

2024-01-2755

04/09/2024

Whenever bicyclists ride on public roads, they ride through roadway defects which occasionally causes them to lose control of their bicycles and/or damage components. Previous research has quantified the forces experienced during general road and offroad riding, but did not study the specific influences of variables such as pothole geometry, riding speed, etc. To begin quantifying these effects, a road bike was equipped with a triaxial accelerometer and ridden over poor roadway conditions around an industrial park in Southern California. Next, in a laboratory setting, an artificial pothole was constructed that was 12 inches long and either 1 or 1.65 inches deep. A force plate was placed at the far edge to measure the horizontal loads induced by the bicycle tire riding over the edge and high-speed camera was positioned perpendicular to the path of travel to measure the speed and vertical drop of the front wheel. Lastly, two riders of differing weights rode the same road bicycle over the

Sweet, David Michael, Bretting, Gerald, Wilhelm, Christopher

Research on Garbage Recognition of Road Cleaning Vehicle Based on Improved YOLOv5 Algorithm

2024-01-2003

04/09/2024

As a key tool to maintain urban cleanliness and improve the road environment, road cleaning vehicles play an important role in improving the quality of life of residents. However, the traditional road cleaning vehicle requires the driver to monitor the situation of road garbage at all times and manually operate the cleaning process, resulting in an increase in the driver 's work intensity. To solve this problem, this paper proposes a road garbage recognition algorithm based on improved YOLOv5, which aims to reduce labor consumption and improve the efficiency of road cleaning. Firstly, the lightweight network MobileNet-V3 is used to replace the backbone feature extraction network of the YOLOv5 model. The number of parameters and computational complexity of the model are greatly reduced by replacing the standard convolution with the deep separable convolution, which enabled the model to have faster reasoning speed while maintaining higher accuracy. Secondly, the attention mechanism in

Liu, XinHong, Wen, Zihao, Kang, Kailei, Liu, Xingchen

Digital Twin Based Multi-Vehicle Cooperative Warning System on Mountain Roads

2024-01-1999

04/09/2024

Compared with urban areas, the road surface in mountainous areas generally has a larger slope, larger curvature and narrower width, and the vehicle may roll over and other dangers on such a road. In the case of limited driver information, if the two cars on the mountain road approach fast, it is very likely to occur road blockage or even collision. Multi-vehicle cooperative control technology can integrate the driving data of nearby vehicles, expand the perception range of vehicles, assist driving through multi-objective optimization algorithm, and improve the driving safety and traffic system reliability. Most existing studies on cooperative control of multiple vehicles is mainly focused on urban areas with stable environment, while ignoring complex conditions in mountainous areas and the influence of driver status. In this study, a digital twin based multi-vehicle cooperative warning system was proposed to improve the safety of multiple vehicles on mountain roads. First, implement

Tian, Liheng, Yu, Zirui, Chen, Xinguo

Fitting Laplace Process Parameters for Non-equidistant Road Roughness Data

2024-01-2298

04/09/2024

Road roughness is the most important source of vertical loads for road vehicles. To capture this during durability engineering, various mathematical models for describing road profiles have been developed. The Laplace process has turned out to be a suitable model, which can describe road profiles in a more flexible way than e.g., Gaussian processes. The Laplace model essentially contains two parameters called C and ν (to be explained below), which need to be adapted to represent a road with certain roughness properties. Usually, local road authorities provide such properties along a road on sections of constant length, say, 100 m. Often the ISO 8608 roughness coefficient or the IRI (International Roughness Index) are used. In such cases, there are well known explicit formulas for finding the parameters C and ν of the Laplace process, which best fits the road under certain assumptions. Besides local road authorities there are also other sources of roughness data, for instance commercial

Speckert, Michael, Dahlheimer, Thorsten, Fiedler, Jochen

Road Recognition Technology Based on Intelligent Tire System Equipped with Three-Axis Accelerometer

2024-01-2295

04/09/2024

Under complex and extreme operating conditions, the road adhesion coefficient emerges as a critical state parameter for tire force analysis and vehicle dynamics control. In contrast to model-based estimation methods, intelligent tire technology enables the real-time feedback of tire-road interaction information to the vehicle control system. This paper proposes an approach that integrates intelligent tire systems with machine learning to acquire precise road adhesion coefficients for vehicles. Firstly, taking into account the driving conditions, sensor selection is conducted to develop an intelligent tire hardware acquisition system based on MEMS (Micro-Electro-Mechanical Systems) three-axis acceleration sensors, utilizing a simplified hardware structure and wireless transmission mode. Secondly, through the collection of real vehicle experiment data on different road surfaces, a dataset is gathered for machine learning training. This dataset is subsequently analyzed to discern the tire

Han, Zongzhi, Liu, Weidong, Liu, Dayu, Gao, Zhenhai, Zhao, Yang

Road Profile Reconstruction Based on Recurrent Neural Network Embedded with Attention Mechanism

2024-01-2294

04/09/2024

Recognizing road conditions using onboard sensors is significant for the performance of intelligent vehicles, and the road profile is a widely accepted representation both in the temporal and frequency domains, greatly influencing driving quality. In this paper, a recurrent neural network embedded with attention mechanisms is proposed to reconstruct the road profile sequence. Firstly, the road and vehicle sensor signals are obtained in a simulated environment by modeling the road, tire, and vehicle dynamic system. After that, the models under different working conditions are trained and tested using the collected data, and the attention weights of the trained model are then visualized to optimize the input channels. Finally, field experiments on the real vehicle are conducted to collect real road profile data, combined with vehicle system simulation, to verify the performance of the proposed method

Shi, Runwu, Yang, Shichun, Lu, Jiayi, Chen, Yuyi, Wang, Rui, Cao, Rui, Li, Zhuoyang

Developing dynamic driver head envelope for passenger cars considering real-time road conditions

2024-01-2493

04/09/2024

Ergonomics plays an important role in automobile design to achieve optimal compatibility between occupants and vehicle components. The overall goal is to ensure that the vehicle design accommodates the target customer group, who come in varied sizes, preferences and tastes. Headroom is one such metric that not only influences accommodation rate but also conveys a visual perception on how spacious the vehicle is. An adequate headroom is necessary for a good seating comfort and a relaxed driving experience. Headroom is intensely discussed in magazine tests and one of the key deciding factors in purchasing a car. SAE J1100 defines a set of measurements and standard procedures for motor vehicle dimensions. H61, W27, W35, H35 and W38 are some of the standard dimensions that relate to headroom and head clearances. While developing the vehicle architecture in the early design phase, it is customary to specify targets for various ergonomic attributes and arrive at the above-mentioned

Rajakumaran, Sriram, S, Rahul, Vasireddy, Rakesh Mitra, Nair, Suhas

Design and Application of Electronic Toll Collection Special Situation Processing System

12-07-03-0018

04/01/2024

In 2018, the state explicitly proposed to “promote the cancellation of expressway toll stations at provincial boundaries.” Electronic toll collection (ETC) has become the main toll collection method on expressways. With the construction of ETC toll lanes, the proportion of ETC vehicles in the expressway traffic flow is increasing, and the rapid processing of vehicle special situations is facing challenges. At present, various provinces have adopted various methods to improve the traffic efficiency and transaction success rate of ETC from the issuance link, customer service link, and lane transaction link. According to statistical data, the average transaction success rate of ETC lane is not higher than 99% at present. As of October 2021, the number of ETC users nationwide has reached 256 million, and there are an average of 40 million ETC transactions per day across the network, that is, about 400,000 special cases need to be processed. How to efficiently deal with special vehicles in

Guo, Xiaohui, Guo, Fengbin, Zhang, Mengwei, Zheng, Fengfei, Liu, Chunya

Minimum Requirements for Road Geometry and Attributes Definition

J2945/A_202404 (Current)04/01/2024

This report specifies the minimum requirements for the Road Geometry and Attributes (RGA) data set (DS) to support road geometry related motor vehicle safety applications. Contained in this report are a concept of operations, requirements, and design, developed using a detailed systems engineering process. Utilizing the requirements, the RGA DS is defined, which includes the DS Abstract Syntax Notation One (ASN.1) format, data frames, and data element definitions. The requirements are intended to enable the exchange of the messages and their DS information to provide the desired interoperability and data integrity to support the applications considered within this report, as well as other applications which may be able to utilize the DS information. System requirements beyond this are outside the scope of this report

V2X Core Technical Committee

Minimum Requirements for Road Geometry and Attributes Definition™ ASN File

J2945/AA_202404 (Current)04/01/2024

SAE J2945/A and this Abstract Syntax Notation (ASN.1) file precisely define the structure of the data used to implement applications conformant to the Recommended Practice. Using the ASN.1 specification, a compiler tool can be used to produce encodings using encoding rules identified in J2945/A. Both this ASN.1 file and the SAE J2735 ASN.1 files are necessary to collectively implement the data structures described in the J2945/A. The combined library can be used by any receiving application (along with the additional logic of the application). SAE J2945/A also provides recommendations for the interface for sending and receiving Road Geometry and Attributes (RGA) messages. It provides the information necessary to build interoperable applications that rely on RGA messages. You may also be interested in: Minimum Requirements for Road Geometry and Attributes Definition™ the J2945/A PDF. Minimum Requirements for Road Geometry and Attributes Definition™ SET File that includes the J2945/AA

V2X Core Technical Committee

Minimum Requirements for Road Geometry and Attributes Definition™ SET File

J2945/AS_202404 (Current)04/01/2024

V2X Core Technical Committee

Integrated Four-Wheel Steering and Direct Yaw-Moment Control for Autonomous Collision Avoidance on Curved Road

02-17-01-0007

01/25/2024

An automatic collision avoidance control method integrating optimal four-wheel steering (4WS) and direct yaw-moment control (DYC) for autonomous vehicles on curved road is proposed in this study. Optimal four-wheel steering is used to track a predetermined trajectory, and DYC is adopted for vehicle stability. Two single lane change collision avoidance scenarios, i.e., a stationary obstacle in front and a moving obstacle at a lower speed in the same lane, are constructed to verify the proposed control method. The main contributions of this article include (1) a quintic polynomial lane change trajectory for collision avoidance on curved road is proposed and (2) four different kinds of control method for autonomous collision avoidance, namely 2WS, 2WS+DYC, 4WS, and 4WS+DYC, are compared. In the design of DYC controller, two different feedback control methods are adopted for comparison, i.e., sideslip angle feedback and yaw rate feedback. The simulation results demonstrate significant

Lai, Fei

Road User Charging™ ASN File

J3217/RA_202401 (Current)01/25/2024

This Abstract Syntax Notation (ASN.1) file precisely specifies the structure of the data used to support implementation of SAE International Standard J3217/R. Using the ASN.1 specification, a compiler tool can be used to produce encodings as required by the encoding rules identified in the standard (SAE J3217/R messages are encoded with UPER encoding). Both this file and the SAE J2735 ASN.1 files are necessary to collectively implement the data exchanges described in SAE J3217/R. The combined library can be used by any application (along with the additional logic of that application) to exchange the data using interfaces conformant to J3217/R. SAE J3217/R specifies interface requirements and message exchanges for configuration and reporting in road use charging systems

Tolling Applications Technical Committee

Road User Charging

J3217/R_202401 (Current)01/25/2024

The scope of this document is the concept of operations including reference system architecture, the user needs, the system functional and performance requirements, the messages, the corresponding data frames and elements, and other related functionality to enable road user charging

Tolling Applications Technical Committee

Road User Charging™ Set

J3217/RS_202401 (Current)01/25/2024

Tolling Applications Technical Committee

The Scope of Autonomous Vehicle Mobility with an Indian Context

2024-26-0087

01/16/2024

The advent of autonomous vehicles promises to revolutionize the transportation sector globally, and India, as one of the world's fastest-growing economies, stands at the forefront of this transformative technology. This paper presents a brief overview of the current state and potential implications of autonomous vehicles in the Indian context. With its densely populated cities, diverse traffic conditions, and complex road infrastructure, India presents unique challenges and opportunities for the deployment of autonomous vehicles. This technology has the potential to address critical issues such as road safety, congestion, and pollution while transforming the mobility experience for millions of people. However, several hurdles must be overcome to fully harness its benefits. The paper explores key considerations for the implementation of autonomous vehicles in India. These include adapting the technology to navigate chaotic traffic scenarios, addressing infrastructure limitations, and

Shetty, Sharan Harish

Regulatory Framework of Construction Equipment Vehicles in India

2024-26-0089

01/16/2024

The Construction & Mining field is continuously upgrading, reshaping under the stimulus of technical enhancement. India is considered one of fastest growing country in the word. Requirement for Construction Equipment Vehicles in India is continuously growing due increased rate infrastructure development. To promote development of the Construction Equipment Vehicles (CEV’s) manufacturing sector it was also necessary to build a new governance architecture. Every vehicle plying on road has to comply with Central Motor Vehicle Regulatory requirements as per CMVR act 1989. Earlier 2021 CEV’s were required to go through performance trials like brake, steering effort, turning circle measurement, speedometer calibration as dynamic tests as per regulations. It was need of the time to come with stringent norms or for better safety of operators & take CEV compatible international regulation. this paper puts forward the basic principles & safety requirements improved for CEV’s over the time

Babar, Sagar, Akbar Badusha, A

Vehicle Trajectory Prediction in Highway Merging Area Using Interactive Graph Attention Mechanism

2023-01-7110

12/31/2023

Accurately predicting the future trajectories of surrounding traffic agents is important for ensuring the safety of autonomous vehicles. To address the scenario of frequent interactions among traffic agents in the highway merging area, this paper proposes a trajectory prediction method based on interactive graph attention mechanism. Our approach integrates an interactive graph model to capture the complex interactions among traffic agents as well as the interactions between these agents and the contextual map of the highway merging area. By leveraging this interactive graph model, we establish an agent-agent interactive graph and an agent-map interactive graph. Moreover, we employ Graph Attention Network (GAT) to extract spatial interactions among trajectories, enhancing our predictions. To capture temporal dependencies within trajectories, we employ a Transformer-based multi-head self-attention mechanism. Additionally, GAT are utilized to model the interactions between traffic agents

Wu, Xigang, Chu, Duanfeng, Deng, Zejian, Xin, Guipeng, Liu, Hongxiang, Lu, Liping

Analysis of the Game-Based Human-Machine Co-steering Control on Low-Adhesion Road Surfaces

2023-01-7086

12/31/2023

With the progressing autonomy of driving technology, machine is assuming greater responsibility for driving tasks to enhance safety. Leveraging this potential, this paper introduces a novel human-machine co-steering control strategy based on model predictive control. The strategy is designed to address the difficulties faced by drivers when driving on surfaces with low adhesion. Firstly, the proposed strategy utilizes a parallel human-machine co-steering framework with a weight allocation concept between the controller and the driver. Moreover, the nonlinear controller dynamics model and linear driver dynamics model are developed to characterize the interaction behaviors between human and machine under low-adhesion road surface conditions. And a nonlinear game optimization problem is formulated to capture the cooperative interaction relationship between human and machine. Finally, to solve the nonlinear game optimization problem, piecewise affine linearization method is employed to

Guo, Hongyan, Hu, Shibo, Shi, Wanqing, Liu, Jun

Real-Time Road Slope Estimation Based on GNSS/INS Fusion System Considering Slope Change

2023-01-7043

12/20/2023

For intelligent vehicles, a fast and accurate estimation of road slope is of great significance for many aspects, including the steering comfort, fuel economy, vehicle stability control, driving decision-making, etc. But the commonly used estimation methods nowadays usually demand additional sensors or complex dynamic models, causing increase in system complexity as well as decrease in accuracy. To solve these problems, this paper puts forward a real-time road slope estimation algorithm leveraging the relationship between pitch angle and road slope, which only requires low sensors cost and computational complexity. Firstly, a GNSS/INS fusion system is established to obtain the pitch angle with respect to the navigation frame, which couples the vehicle’s pitch angle in vehicle frame and road slope angle. Then, based on the different characteristics in frequency domain of the two components, frequency domain analysis is conducted and low-pass filter is used to separate out road slope

Chen, Mengyuan, Xiong, Lu, Gao, Letian

Synthetic Data for 2D Road Marking Detection in Autonomous Driving

2023-01-7046

12/20/2023

The development of autonomous driving generally requires enormous annotated data as training input. The availability and quality of annotated data have been major restrictions in industry. Data synthesis techniques are then being developed to generate annotated data. This paper proposes a 2D data synthesis pipeline using original background images and target templates to synthesize labeled data for model training in autonomous driving. The main steps include: acquiring templates from template libraries or alternative approaches, augmenting the obtained templates with diverse techniques, determining the positioning of templates in images, fusing templates with background images to synthesize data, and finally employing the synthetic data for subsequent detection and segmentation tasks. Specially, this paper synthesizes traffic data such as traffic signs, traffic lights, and ground arrow markings in 2D scenes based on the pipeline. The effectiveness of this pipeline was verified on the

Bie, Xiaofang, Zhang, Song, Meng, Chao, Mei, Jinren, Li, Jian, He, Xin

The New Mobility Handbook, 2024 Edition

R-56512/13/2023

Are new mobility technologies the key to unlocking the future of urban living, or do they pose a threat to established public transit systems? Dive into this groundbreaking book that unveils the potential for a harmonious coexistence. The New Mobility Handbook, 2024 Edition challenges the belief that ride services, autonomous vehicles, and micromobility are at odds with public transit in a zero-sum transportation game. Discover how new mobility options, immensely popular and fostering multimodal travel, can be paired with classic urban planning principles to offer attractive alternatives to personal car use. Learn how road pricing, road space reallocation, and innovative policies can transform cities when new mobility technologies turn detractors into allies. Ride services and micromobility emerge not as adversaries to transit, but as advocates for a smarter, more inclusive urban ecosystem. Part I sparks a paradigm shift, advocating to change how we use cars through fair pricing and

Kyrouz, Michele

Enhancing Autonomous Vehicle Safety in Cold Climates by Using a Road Weather Model: Safely Avoiding Unnecessary Operational Design Domain Exits

15-17-01-0004

10/28/2023

This study investigates the use of a road weather model (RWM) as a virtual sensing technique to assist autonomous vehicles (AVs) in driving safely, even in challenging winter weather conditions. In particular, we investigate how the AVs can remain within their operational design domain (ODD) for a greater duration and minimize unnecessary exits. As the road surface temperature (RST) is one of the most critical variables for driving safety in winter weather, we explore the use of the vehicle’s air temperature (AT) sensor as an indicator of RST. Data from both Road Weather Information System (RWIS) stations and vehicles measuring AT and road conditions were used. Results showed that using only the AT sensor as an indicator of RST could result in a high number of false warnings, but the accuracy improved significantly with the use of an RWM to model the RST. ROC-curve analysis resulted in an AUC value of 0.917 with the AT sensor and 0.985 with the RWM, while the true positive rate

Almkvist, Esben, David, Mariana Alves, Pedersen, Jesper Landmér, Lewis-Lück, Rebecca, Hu, Yumei

Improvement of Quietness in the Cabin by Engine Control based on Road Noise Estimation for New Series Hybrid System

2023-32-0174

09/29/2023

Engine start timing of series hybrid system is important for quietness in the cabin and comfortable because its engine operation timing is not restricted by vehicle speed and acceleration. There is an opportunity to operate the engine without spoiling quietness if engine sounds could be covered by road noise. Discovering the correlation between road noise and variance of wheel angular acceleration using wheel speed sensor made it possible to estimate road noise. Engine start control based on this road noise estimation algorithm contributes to cabin quietness performance improvement as the result of less frequency of engine operating during smooth road driving

Sawada, Takanobu, Yamauchi, Yasuhiro, Teraji, Atsushi, Gotou,, Masaya, Aizumi, Sho, Matsuoka, Hisayoshi, Enomoto, Toshio

Concept, Implementation, and Performance Comparison of a Particle Filter for Accurate Vehicle Localization Using Road Profile Data

10-07-03-0025

08/25/2023

A precise knowledge of the road profile ahead of the vehicle is required to successfully engage a proactive suspension control system. If this profile information is generated by preceding vehicles and stored on a server, the challenge that arises is to accurately determine one’s own position on the server profile. This article presents a localization method based on a particle filter that uses the profile observed by the vehicle to generate an estimated longitudinal position relative to the reference profile on the server. We tested the proposed algorithm on a quarter vehicle test rig using real sensor data and different road profiles originating from various types of roads. In these tests, a mean absolute position error of around 1 cm could be achieved. In addition, the algorithm proved to be robust against local disturbances, added noise, and inaccurate vehicle speed measurements. We also compared the particle filter with a correlation-based method and found it to be advantageous

Anhalt, Felix, Hafner, Simon

Optimizing Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy-Duty Fuel Cell Electric Vehicles

13-05-01-0008

08/12/2023

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen-based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This article introduces the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy-duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional-specific vehicle fuel economy and weight, vehicle origin and destination (O-D), and vehicle volume by class and infrastructure costs to characterize in-mission refueling

Siekmann, Adam, Sujan, Vivek, Uddin, Majbah, Liu, Yuandong, Xie, Fei

Longitudinal and Lateral Dynamics Simulation of an 11-Axle, 91-Ton Vehicle Combination for the Sugarcane Industry

2023-36-0360

07/25/2023

The sugarcane industry holds the second largest share of production value in the Brazilian agricultural sector, with Brazil responsible for more than 20% of the world’s production. Therefore, the increase of efficiency in the production process of sugarcane is an object of interest for producers, with transportation playing an important role in the process, both economically and environmentally. Intending to improve the efficiency in the transportation of sugarcane between cultivation and processing facilities, this work uses simulations to analyze safety aspects of a vehicle combination with 11 axles and 91ton capacity, new to the Brazilian transportation system. Several procedures were performed in a virtual environment to evaluate the vehicle longitudinal and lateral dynamics, including weight distribution, overtaking performance, rollover threshold, rearward amplification, braking and gradeability. The study is focused on providing information about the feasibility and safety of

de Oliveira, Paulo Ricardo Araujo, de Almeida Lima, Vinicius, Bougo, José Igor Calsavara

SAE TOMORROW TODAY: Is The Rise of Evs The End of the Gas Tax

1339305/17/2023

With more and more consumers plugging in their cars instead of filling up their tanks, the gas tax is slowly eroding--just like many of our roads and bridges across the country. Less fuel tax means less money for repairing our decaying infrastructure, but Road Usage Charges (RUC) can change that. RUC -- also referred to as a vehicle miles traveled (VMT) fee, a distance-based user fee (DBF), or a mileage-based user fee (MBUF) -- charges motorists based on the number of miles they drive instead of the number of gallons of fuel they put into their vehicles. This evolution to a more usage-based model provides sustainability and fairness in paying for our roads and bridges as more and more consumers move to EVs. As a leading global engineering and professional services firm, WSP USA has led some of the largest and most successful RUC pilots in the country. These efforts have led to wider state consideration and enhanced regional interest in RUC as a viable future transportation funding

Hineman, Marcie

Decelerations for Vehicles with Anti-lock Brake Systems (ABS) on Dry Asphalt and Concrete Road Surfaces

2023-01-0616

04/11/2023

Anti-lock brake systems (ABS) produce high levels of vehicle deceleration under emergency braking conditions by modulating tire slip. Currently there are limited data available to quantify the mean, variance, and distribution of vehicle deceleration levels for modern ABS-equipped vehicles. We conducted braking tests using twenty (20) late-model vehicles on contiguous dry asphalt and concrete road surfaces. All vehicles were equipped with a 5th wheel sampled at 200 Hz, from which vehicle speed and deceleration as a function of time were calculated. Eighteen (18) tests were conducted for each vehicle and all tests were conducted from a targeted initial speed of 65 km/h (40 mph). Overall, we found that late-model ABS-equipped vehicles can decelerate at average levels that vary from about 0.871g to 1.081g across both surfaces, and that deceleration levels were on average about 0.042g higher on asphalt than on concrete. We also found that the passenger cars decelerated about 0.087g higher

Miller, Ian, King, David, Wilkinson, Craig, Siegmund, Gunter P.

Intersection Traffic Safety Evaluation Using Potential Energy Filed Method

2023-01-0855

04/11/2023

The intersection is recognized as the most dangerous area because of the restricted road structures and indeterminate traffic regulations. Therefore, according to the Vehicle-to-everything (V2X) communication, Intelligent Transportation Systems (ITS), and Digital Twin data, we present a potential energy field method to establish the general characteristics of intersection traffic safety, evaluate the safety situation of intersection and assist intersection traffic participants in passing through the intersection safer and more efficient. The resulting potential energy field method is established by the contour line of traffic participants' potential energy, which is constructed as a superposition of disparate energies, such as boundary potential energy, body potential energy, and velocity potential energy. The intersection traffic safety is evaluated by the potential energy field characteristic of simultaneous intersection traffic participants. The correctness and effectiveness of the

Wu, Biao, Zhu, Xichan, Ma, Zhixiong, Zhou, Xiaojun

A Road Roughness Estimation Method based on PSO-LSTM Neural Network

2023-01-0747

04/11/2023

The development of intelligent and networked vehicles has enhanced the demand for precise road information perception. Detailed and accurate road surface information is essential to intelligent driving decisions and annotation of road surface semantics in high-precision maps. As one of the key parameters of road information, road roughness significantly impacts vehicle driving safety and comfort for passengers. To reach a rapid and accurate estimation of road roughness, in this study, we develop a neural network model based on vehicle response data by optimizing a long-short term memory (LSTM) network through the particle swarm algorithm (PSO), which fits non-linear systems and predicts the output of time series data such as road roughness precisely. We establish a feature dataset based on the vehicle response time domain data that can be easily obtained, such as the vehicle wheel center acceleration and pitch rate. A PSO-LSTM network is built to achieve road roughness estimation and

Li, Zhuoyang, Yang, Shichun, Chen, Yuyi, Nan, Zhaobo, Shi, Runwu, Wang, Rui, Zhang, Mengyue

The Methodology of the System-Level Topology Optimization for Road Booming Noise

2023-01-0027

04/11/2023

Most sub-compact vehicles with the rear multi-link system have road booming noise issues due to bending modes in the rear cross-member. Many engineers in the vehicle industry solve this problem by implementing a dynamic damper on the rear cross-member. However, the additional component of the rear cross-member increases cost and weight. This paper presents the methodology of the system-level optimization for rear cross-member structures to improve road booming noise. A feature extraction methodology is introduced. This method makes possible the application of topology optimization results to real design, rather than the results just being used as a concept suggestion

Park, Jong Ho, Hwang, Kwang Hyeon

Unstructured Road Region Detection and Road Classification Algorithm Based on Machine Vision

2023-01-0061

04/11/2023

Accurate sensing of road conditions is one of the necessary technologies for safe driving of intelligent vehicles. Compared with the structured road, the unstructured road has complex road conditions, and the response characteristics of vehicles under different road conditions are also different. Therefore, accurately identifying the road categories in front of the vehicle in advance can effectively help the intelligent vehicle timely adjust relevant control strategies for different road conditions and improve the driving comfort and safety of the vehicle. However, traditional road identification methods based on vehicle kinematics or dynamics are difficult to accurately identify the road conditions ahead of the vehicle in advance. Therefore, this paper proposes an unstructured road region detection and road classification algorithm based on machine vision to obtain the road conditions ahead. Firstly, a vehicle data acquisition platform is built based on a Logitech HD camera, which is

XIE, Fei, Zhang, Jian, Wang, Chao, Liu, Qiuzheng, Hong, Ri, Yanchen, Liu

Anti-Skid System for Ice-Snow Curve Road Surface Based on Visual Recognition and Vehicle Dynamics

2023-01-0058

04/11/2023

Preventing skidding is essential for studying the safety of driving in curves. However, the adhesion of the vehicle during the driving process on the wet and slippery road will be significantly reduced, resulting in lateral slippage due to the low adhesion coefficient of the road surface, the speed exceeding the turning critical, and the turning radius being too small when passing through the corner. Therefore, to reduce the incidence of traffic accidents of passenger cars driving in curves on rainy and snowy days and achieve the purpose of planning safe driving speed, this paper proposes a curve active safety system based on a deep learning algorithm and vehicle dynamics model. First,we a convolutional neural network (CNN) model is constructed to extract and judge the characteristics of snow and ice adhesion on roads. By training the residual network, the road surface can be identified and classified under 7 different weather conditions, and the adhesion coefficient of the road

Pang, Chenghui, Zhu, Haotian, Lin, Zhenmao

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