Browse Topic: Traffic management

Items (481)

CONVOY ACTIVE SAFETY TECHNOLOGY – ENVIRONMENTAL UNDERSTANDING AND NAVIGATION WITH USE OF LOW COST SENSORS

2024-01-3353

To be published on 11/15/2024

ABSTRACT This paper will document the development of the Convoy Active Safety Technology (CAST) program, which was created to design a low cost, optionally manned vehicle (OMV) solution for tactical wheeled vehicle (TWV) fleet. This paper will describe the approach taken to integrate low cost sensors for understanding the environment sufficiently to accomplish convoy missions. This paper will also discuss the approach taken to develop the low cost guidance and navigation solution used in the CAST program

Simon, David, Theisen, Bernard

Contextual Study of Security and Privacy in V2X Communication for Architecture & Networking Products

2024-28-0038

10/17/2024

In recent times there has been an upward trend in “Connected Vehicles”, which has significantly improved not only the driving experience but also the “ownership of the car”. The use of state-of-the-art wireless technologies, such as vehicle-to-everything (V2X) connectivity, is crucial for its dependability and safety. V2X also effectively extends the information flow between the transportation ecosystem pedestrians, public infrastructure (traffic management system) and parking infrastructure, charging and fuel stations, Etc. V2X has a lot of potential to enhance traffic flow, boost traffic safety, and provide drivers and operators with new services. One of the fundamental issues is maintaining trustworthy and quick communication between cars and infrastructure. While establishing stable connectivity, reducing interference, and controlling the fluctuating quality of wireless transmissions, we have to ensure the Security and Privacy of V2I. Since there are multiple and diverse

Sundar, Shyam, Pundalik, Krantiveer, Unnikrishnan, Ushma

Boosting Algorithms for the Accident Severity Classification

12-08-04-0030

10/17/2024

Background: Road accident severity estimation is a critical aspect of road safety analysis and traffic management. Accurate severity estimation contributes to the formulation of effective road safety policies. Knowledge of the potential consequences of certain behaviors or conditions can contribute to safer driving practices. Identifying patterns of high-severity accidents allows for targeted improvements in terms of overall road safety. Objective: This study focuses on analyzing road accidents by utilizing real data, i.e., US road accidents open database called “CRSS.” It employs advanced machine learning models such as boosting algorithms such as LGBM, XGBoost, and CatBoost to predict accident severity classification based on various parameters. The study also aims to contribute to road safety by providing predictive insights for stakeholders, functional safety engineering community, and policymakers using KABCO classification systems. The article includes sections covering

Babaev, Islam, Mozolin, Igor, Garikapati, Divya

Integration of AI-Powered Vehicles with Smart City Infrastructure to Transform the Future of Automotive World

2024-28-0028

10/17/2024

Artificial Intelligence (AI) has emerged as a transformative force across various industries, revolutionizing processes and enhancing efficiency. In the automotive domain, AI's adaption has ushered in a new era of innovation and driving advancements across manufacturing, safety, and user experience. By leveraging AI technologies, the automotive industry is undergoing a significant transformation that is reshaping the way vehicles are manufactured, operated, and experienced. The benefits of AI-powered vehicles are not limited to their manufacturing, operation, and enhancing the user experience but also by integrating AI-powered vehicles with smart city infrastructure can unlock much more potential of the technology and can offer numerous advantages such as enhanced safety, efficiency, growth, and sustainability. Smart cities aim to create more livable, resilient, and inclusive communities by harnessing innovation through technologies like Internet of Things (IoT), devices, data

Shrimal, Harsh

Optimal Eco-Driving with Infrastructure-to-Vehicle Communication for Speed Adaptation Based on Real-Time Dynamic Macroscopic Traffic Conditions

2024-24-0025

09/18/2024

Eco-driving algorithms use the available information about traffic and route conditions to optimize the vehicle speed and achieve enhanced energy consumption while fulfilling a travel time constraint. Depending on what information is available, when it becomes accessible, and the level of automation of the vehicle, different energy savings can be achieved. In their basic formulation, eco-driving algorithms only leverage static information to evaluate the optimal speed, such as posted speed limits and location of stop signs. More advanced algorithms may also consider dynamic information, such as the speed of the preceding vehicle and Signal Phase and Timing of traffic lights, thus achieving higher energy efficiency. The objective of the proposed work is to develop an eco-driving algorithm that can optimize energy consumption by leveraging not only static route information, but also dynamic macroscopic traffic conditions, which are assumed to be available in real-time through

Villani, Manfredi, Shiledar, Ankur, Block, Brian, Spano, Matteo, Rizzoni, Giorgio

The Use and Benefits of Modeling and Simulation with Autonomous Vehicles

2024-01-4106

09/16/2024

Traditional live testing of autonomous ground vehicles can be augmented through use of digital twins of the test environment, the vehicle mobility models, and the vehicle sensors. These digital twins combined with the autonomous software under test allow testers to inject faults, weather, obstacles, find edge case scenarios, and collect information to understand the decision making of the autonomous software under test. With this new capability, autonomous ground vehicles can now be tested in four stages. The first stage is testing the autonomous software using digital twins. In this stage with the help of a High-Performance Computer thousands of scenarios can be run. Once issues are communicated and addressed, stage two, hardware in the loop testing can begin. Hardware in the loop uses simulators that already exist to test systems such as autonomous convoys with a virtual leader and a live follower. Stage three employs a live virtual constructive approach by using one vehicle to test

Whitt, John M., Bounker, Paul J.

Next-gen Urban Buses: Autonomy and Connectivity

EPR2024019

08/26/2024

The deployment of autonomous urban buses brings with it the hope of addressing concerns associated with safety and aging drivers. However, issues related autonomous vehicle (AV) positioning and interactions with road users pose challenges to realizing these benefits. This report covers unsettled issues and potential solutions related to the operation of autonomous urban buses, including the crucial need for all-weather localization capabilities to ensure reliable navigation in diverse environmental conditions. Additionally, minimizing the gap between AVs and platforms during designated parking requires precise localization. Next-gen Urban Buses: Autonomy and Connectivity addresses the challenge of predicting the intentions of pedestrians, vehicles, and obstacles for appropriate responses, the detection of traffic police gestures to ensure compliance with traffic signals, and the optimization of traffic performance through urban platooning—including the need for advanced communication

Hsu, Tsung-Ming

Platooning of Position-Controlled Vehicles on a Curved Path under Communication Losses and Delays

12-07-04-0028

08/21/2024

This article offers an algorithmic solution for moving a homogeneous platoon of position-controlled vehicles on a curved path with varying speeds and in the presence of communication losses and delays. This article considers a trajectory-based platooning with the leader–following communication topology, where the lead vehicle communicates its reference position and orientation to each autonomous follower vehicle. A follower vehicle stores this communicated information for a specific period as a virtual trail of the lead vehicle starting from the lead vehicle’s initial position and orientation. An algorithm uses this trail to find the follower vehicle’s reference position and orientation on that trail, such that the follower vehicle maintains a constant distance from the lead vehicle. The proposed algorithm helps form a platoon where each vehicle can traverse a curve with varying speeds. In contrast, in the existing literature, most of the solutions for vehicle platooning on a curved

Bhaskar, Rintu, Wahi, Pankaj, Potluri, Ramprasad

Lateral Platooning Control with Precise Path Tracking and Strong Disturbance Suppression Performance

2024-01-5074

07/24/2024

There have been numerous studies on stable platooning, but almost all of them have been on the longitudinal stability problem, wherein, without sufficient longitudinal stability, traffic congestion might occur more frequently than in traffic consisting of manually driven vehicles. Failure to solve this problem would reduce the value of autonomous driving. Recently, some researchers have begun to tackle the lateral stability problem, anticipating shortened intervehicle distances in the future. Here, the intervehicle distance in a platoon should be shortened to improve transportation efficiency. However, if an obstacle to be avoided exists, the following vehicles might have difficulty finding it quickly enough if the preceding vehicle occludes it from their sensors. Also, longer platoons improve transportation efficiency because the number of gaps between platoons is reduced. Hence, in this study, the lateral stability of platoons consisting of autonomous vehicles was analyzed for not

Kurishige, Masahiko

Lane-Changing Behavior’s Impact on Platoon Dispersion in Mixed Autonomous Vehicle Traffic: Insights from Simulation

12-08-02-0013

07/01/2024

This research investigates platoon dispersion characteristics in mixed-traffic flow of autonomous and human-driven vehicles. It presents a cellular automata-based platoon dispersion model. The study’s key findings are as follows: platoon dispersion initially increases and then decreases with the rise in autonomous vehicle proportions. When the autonomous vehicle proportion is approaching 100%, platoon dispersion descends rapidly and is completely eliminated while the proportion is 100%. Compared to platoon consisting entirely of human-driven vehicles, the peak value of standard deviation of vehicle speed is 1.71 times and the travel time drops by 38.19% when the proportion is 1. Moreover, the lane-changing behavior enhances platoon speed, acceleration, and space utilization at micro- and macrolevels by optimizing space resource allocation within the platoon. The study employs a two-lane mixed-flow platoon dispersion model that assumes uniform vehicle characteristics and prioritizes

Lu, Ting, Liu, Chenghao, Lin, Sitong, Song, Wenjing

Developing Fuel Savings Performance Function Considering Various Truck Platooning Configurations

04-17-03-0018

06/29/2024

Truck platooning facilitates the operation of trucks in close proximity to one another, resulting in decreased air resistance and improved fuel efficiency. While previous research has mostly focused on the effects of intra-distance on fuel savings, this study aims to develop fuel savings performance functions considering various truck platooning configurations. This article comprehensively investigates the influence of different truck platoon configurations on fuel savings. This analysis focuses on examining the impacts of several variables including inter-vehicle distance, platoon speed, truck weight, number of trucks in the platoon, and the truck’s distinctive design characteristics. Data used in the analysis were collected from 10 different field experiments. Three machine learning techniques—artificial neural networks (ANN), extreme gradient boosting (XGBoost), and K-nearest neighbors (KNN)—alongside the negative binomial regression model were employed. Upon evaluation, the

Mohamed, Mohamed, Hassan, Hany M.

Consensus Based Air Transport System for Strategic Deconfliction for Urban Air Mobility

2024-26-0405

06/01/2024

Urban Air Mobility (UAM) envisions heterogenous airborne entities like crewed and uncrewed passenger and cargo vehicles within, and between urban and rural environment. To achieve this, a paradigm shift to a cooperative operating environment similar to Extensible Traffic Management (xTM) is needed. This requires the blending of traditional Air Traffic Services (ATS) with the new generation UAM vehicles having their unique flight dynamics and handling characteristics. A hybrid environment needs to be established with enhanced shared situational awareness for all stakeholders, enabling equitable airspace access, minimizing risk, optimized airspace use, and providing flexible and adaptable airspace rules. This paper introduces a novel concept of distributed airspace management which would be apt for all kinds of operational scenarios perceived for UAM. The proposal is centered around the efficiency and safety in air space management being achieved by self-discipline. It utilizes

KG, Sreenivasan, Suseelan, SunilRaj, Huncha, Pradeep

Research on Speed Guidance Strategy at Continuous Signal Intersection Based on Vehicle–Road Coordination Technology

12-07-04-0023

04/13/2024

With the rapid growth of automobile ownership, traffic congestion has become a major concern at intersections. In order to alleviate the blockage of intersection traffic flow caused by signals, reduce the length of vehicle congestion and waiting time, and for improving the intersection access efficiency, therefore, this article proposes a vehicle speed guidance strategy based on the intersection signal change by combining the vehicle–road cooperative technology. The randomness of vehicle traveling speed in the road is being considered. According to the vehicle traveling speed, a speed guidance model is established under different conditions. Finally, the effectiveness of the speed guidance strategy in this article is verified through experimental simulation, and the benefits of the intersection with intelligent control and traditional control are compared, and the experimental results show that the intelligent control method in this article can effectively reduce vehicle congestion and

Li, Wenli, Li, An, Ren, Yongpeng, Wang, Kan

A Drag-Reduction Prediction Model for Truck Platoons

2024-01-2548

04/09/2024

Truck platooning is an emerging technology that exploits the drag reduction experienced by bluff bodies moving together in close longitudinal proximity. The drag-reduction phenomenon is produced via two mechanisms: wake-effect drag reduction from leading vehicles, whereby a following vehicle operates in a region of lower apparent wind speed, thus reducing its drag; and base-drag reduction from following vehicles, whereby the high-pressure field forward of a closely-following vehicle will increase the base pressure of a leading vehicle, thus reducing its drag. This paper presents a physics-guided empirical model for calculating the drag-reduction benefits from truck platooning. The model provides a general framework from which the drag reduction of any vehicle in a heterogeneous truck platoon can be calculated, based on its isolated-vehicle drag-coefficient performance and limited geometric considerations. The model is adapted from others that predict the influence of inter-vehicle

McAuliffe, Brian

Evaluation of Difficulty for Autonomous Vehicles Testing Roads based on Multiple Criteria Decision Analysis

2024-01-1983

04/09/2024

Autonomous Vehicles are being widely tested under diverse conditions with expectations that they will soon be a regular feature on roads. The development of Autonomous Vehicles has become an important policy in countries around the world, and the technologies developed by countries and car manufacturers are different, and at the same time to adapt to the road environment and traffic management facilities of different countries, so some countries have built self-driving test sites, and the test content is also different, so it is impossible to compare its relative difficulty. This study surveyed experts and scholars to develop a means of weighting the respective difficulty of various autonomous vehicle testing conditions based on the analytic hierarchy process and fuzzy analytic hierarchy process, applied to a sample of 33 sets of testing conditions based on road type, management actions and operational capabilities. Weights are also adjusted in response to environmental impact factors

Lin, Da-Jie, Liu, Hsin Hsien, CHOU, AI-CHEN, Huang, Pin-Cheng, WU, CHENG HSIN, CHANG, CHUN-YI, CHEN, MING-HSU

Research on Vehicle Type Recognition Based on Improved YOLOv5 Algorithm

2024-01-1992

04/09/2024

As a key technology of intelligent transportation system, vehicle type recognition plays an important role in ensuring traffic safety,optimizing traffic management and improving traffic efficiency, which provides strong support for the development of modern society and the intelligent construction of traffic system. Aiming at the problems of large number of parameters, low detection efficiency and poor real-time performance in existing vehicle type recognition algorithms, this paper proposes an improved vehicle type recognition algorithm based on YOLOv5. Firstly, the lightweight network model MobileNet-V3 is used to replace the backbone feature extraction network CSPDarknet53 of the YOLOv5 model. The parameter quantity and computational complexity of the model are greatly reduced by replacing the standard convolution with the depthwise separable convolution, and enabled the model to maintain higher accuracy while having faster reasoning speed. Secondly, the attention mechanism in

Liu, XinHong

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

Expanding the Use of Vehicle Specific Power in Analysis of Platoon Performance

2024-01-2057

04/09/2024

Platooning is a coordinated driving strategy by which following trucks are placed into the wake of leading vehicles. Doing this leads to two primary benefits. First, the vehicles following are shielded from aerodynamic drag by a “pulling” effect. Secondly, by placing vehicles behind the leading truck, the leading vehicles experience a “pushing” effect. The reduction in aerodynamic drag leads to reduced fuel usage and, consequently, reduced greenhouse gas emissions. To maximize these effects, the inter-vehicle distance, or headway, needs to be minimized. In current platooning strategy iterations, Coordinated Adaptive Cruise Control (CACC) is used to maintain close following distances. Many of these strategies utilize the fuel rate signal as a controller cost function parameter. By using fuel rate, current control strategies have limited applicability to non-conventional powertrains. Vehicle Specific Power (VSP) has shown promise as a metric by which the performance of such controllers

Bentley, John, Stegner, Evan, Bevly, David M., Hoffman, Mark

Biosignal-Based Driving Experience Analysis between Automated Mode and Manual Mode

2024-01-2504

04/09/2024

With the rapid development of intelligent driving technology, there has been a growing interest in the driving comfort of automated vehicles. As vehicles become more automated, the role of the driver shifts from actively engaging in driving tasks to that of a passenger. Consequently, the study of the passenger experience in automated driving vehicles has emerged as a significant research area. In order to examine the impact of automatic driving on passengers' riding experience in vehicle platooning scenarios, this study conducted real vehicle experiments involving six participants. The study assessed the subjective perception scores, eye movement, and electrocardiogram (ECG) signals of passengers seated in the front passenger seat under various vehicle speeds, distances, and driving modes. The results of the statistical analysis indicate that vehicle speed has the most substantial influence on passenger perception. The driving mode has a minor effect on the passenger riding experience

Hu, Hongyu, Zhang, Guojuan, Cheng, Ming, Li, Zhengyi, He, Lei, Su, Lili

Effects of Traffic Control Device and Hazard Location on Fixations During Intersection Navigation: A Simulator Study

2024-01-2465

04/09/2024

Collisions resulting in injuries or fatalities occur more frequently at intersections. This is partly because safe navigation of intersections requires drivers to accurately observe and respond to other road users with conflicting paths. Previous studies have raised questions about how traffic control devices and the positioning of other road users might affect drivers' visual search strategies when navigating intersections. To address these questions, four left-turn-across-path (LTAP) scenarios were created by combining two types of traffic control devices (stop signs and traffic lights) with two hazard starting locations (central and peripheral). Seventy-four licensed drivers responded to all scenarios in a counterbalanced order using a full vehicle driving simulator. Eye-tracking glasses were used to monitor eye movements, both before and after hazard onset. The results revealed that drivers at the signalized intersections took longer to fixate the LTAP hazard before onset, spent

Caren, Brooklin, Ziraldo, Erika, Oliver, Michele

Energy Savings Impact of Eco-Driving Control Based on Powertrain Characteristics in Connected and Automated Vehicles: On-Track Demonstrations

2024-01-2606

04/09/2024

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery. The implemented control is a universal speed planner that solves the eco-driving optimal-control problem within a receding-horizon framework

Jeong, Jongryeol, Kandaswamy, Elangovan, Dudekula, Ahammad Basha, Han, Jihun, Karbowski, Dominik, Naber, Jeffrey

Comparative Analysis of Clustering Algorithms Based on Driver Steering Characteristics

2024-01-2570

04/09/2024

Driver steering feature clustering aims to understand driver behavior and the decision-making process through the analysis of driver steering data. It seeks to comprehend various steering characteristics exhibited by drivers, providing valuable insights into road safety, driver assistance systems, and traffic management. The primary objective of this study is to thoroughly explore the practical applications of various clustering algorithms in processing driver steering data and to compare their performance and applicability. In this paper, principal component analysis was employed to reduce the dimension of the selected steering feature parameters. Subsequently, K-means, fuzzy C-means, the density-based spatial clustering algorithm, and other algorithms were used for clustering analysis, and finally, the Calinski-Harabasz index was employed to evaluate the clustering results. Furthermore, the driver steering features were categorized into lateral and longitudinal categories. Different

Chen, Chen, Zong, Changfu

Cyber Threats and Its Mitigation to Intelligent Transportation System

2024-26-0184

01/16/2024

With the revolutionary advancements in modern transportation, offering advanced connectivity, automation, and data-driven decision-making has put the intelligent transportation systems (ITS) to a high risk from being exposed to cyber threats. Development of modern transportation infrastructure, connected vehicle technology and its dependency over the cloud with an aim to enhance safety, efficiency, reliability and sustainability of ITS comes with a lot more opportunities to protect the system from black hats. This paper explores the landscape of cyber threats targeting ITS, focusing on their potential impacts, vulnerabilities, and mitigation strategies. The cyber-attacks in ITS are not just limited to Unauthorized Access, Malware and Ransomware Attacks, Data Breaches, Denial of Service but also to Physical Infrastructure Attacks. These attacks may result in potentially disrupting critical transportation infrastructure, compromise user safety, and can cause economic losses effecting the

Dewangan, Kheelesh Kumar, Panda, Vibek, Ojha, Sunil, Shahapure, Anjali, Jahagirdar, Shweta Rajesh

A Smart Transportation System for Existing Vehicles and Roads Infrastructure to Ease Traffic and Toll Problems in India

2024-26-0181

01/16/2024

India is a highly populous country. The traffic problems faced by the people here are not uncommon. The increase in traffic leads to increase in accidents, pollution, inconvenience and frustration. It also comes with costs of additional fuel and time. Though public transport is extensively available in India, still it isn't sufficient for the population of India. Especially in Metro cities, public transport services are often crowded. So, to travel peacefully people are opting for commuting in their own vehicles. And as a result, more vehicles are coming on roads. Other major reasons for increasing traffic are lack of proper implementation of traffic rules and traffic signals out of sync. In addition to city traffic, congestion is also seen on highways, mainly at toll plazas. Although implementation of FASTag has reduced it to some extent, some toll plazas still face traffic congestion issues. This paper provides an idea to ease the traffic problems in the city and on the highways too

Jain, Pritesh

Convolutional Neural Networks for Object Detection

2023-36-0097

01/08/2024

Autonomous cars (ACs) and advanced driver-assistance systems (ADAS) have relied on convolutional neural networks (CNNs) for object detection. However, image degradation caused by adverse weather conditions like rain, snow, and fog can decrease the performance of a CNN. So, this paper presents the development of an image-processing technique aimed to mitigate such a problem. First, after an extensive evaluation of models for object detection, YOLOv3 was chosen because of its compromise between precision and inference time. Afterwards, the training and test of a YOLOv3 CNN was investigated for cars, traffic signals, traffic lights, pedestrians, and riders. Performance was evaluated by estimating the average and mean average precision (mAP) for every one of the mentioned object classes. An OpenCV based pre-processing technique to mitigate the degradation imposed by adverse weather conditions was implemented. Specifically, the OpenCV filters of erosion, dilation and joint bilateral filter

Romão, Bruno, Fagotto, Eric

TD3 Tuned PID Controller for Autonomous Vehicle Platooning

2023-01-7108

12/31/2023

The main objective of platoon control is coordinated motion of autonomous vehicle platooning with small intervehicle spacing while maintaining the same speed and acceleration as the leading vehicle, which can save energy consumption and improve traffic throughput. The conventional platoon control methods are confronted with the problem of manual parameter tuning. In order to addres this isue, a novel bifold platoon control approach leveraging a deep reinforcement learning-based model is proposed, which enables the platoon adapt to the complex traffic environment, and guarantees the safety of platoon. The upper layer controller based on the TD3 tuned PID algorithm outputs the desired acceleration. This integration mitigates the inconvenience of frequent manual parameter tuning asociated with the conventional PID algorithm. The lower layer controller tracks the desired acceleration based on the inverse vehicle dynamics model and feedback control. Through this dynamic inverse model, the

Chen, Xinhai, Wang, Rukang, Cui, Yanan, Jin, Xiaoxin, Feng, Chengjun, Xie, Bo, Deng, Zejian, Chu, Duanfeng

Cooperative Lane Change Control Based on Null-Space-Behavior for a Dual-Column Intelligent Vehicle Platoon

2023-01-7064

12/20/2023

With the extension of intelligent vehicles from individual intelligence to group intelligence, intelligent vehicle platoons on intercity highways are important for saving transportation costs, improving transportation efficiency and road utilization, ensuring traffic safety, and utilizing local traffic intelligence [1]. However, there are several problems associated with vehicle platoons including complicated vehicle driving conditions in or between platoon columns, a high degree of mutual influence, dynamic optimization of the platoon, and difficulty in the cooperative control of lane change. Aiming at the dual-column intelligent vehicle platoon control (where “dual-column” refers to the vehicle platoon driving mode formed by multiple vehicles traveling in parallel on two adjacent lanes), a multi-agent model as well as a cooperative control method for lane change based on null space behavior (NSB) for unmanned platoon vehicles are established in this paper. Specifically, a multi-agent

Yan, Danshu, Zhao, Zhiguo, Liang, Kaichong, Yu, Qin

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

A Comparative Study of Longitudinal Vehicle Control Systems in Vehicle-to-Infrastructure Connected Corridor

12-06-04-0025

11/16/2023

Vehicle-to-infrastructure (V2I) connectivity technology presents the opportunity for vehicles to perform autonomous longitudinal control to navigate safely and efficiently through sequences of V2I-enabled intersections, known as connected corridors. Existing research has proposed several control systems to navigate these corridors while minimizing energy consumption and travel time. This article analyzes and compares the simulated performance of three different autonomous navigation systems in connected corridors: a V2I-informed constant acceleration kinematic controller (V2I-K), a V2I-informed model predictive controller (V2I-MPC), and a V2I-informed reinforcement learning (V2I-RL) agent. A rules-based controller that does not use V2I information is implemented to simulate a human driver and is used as a baseline. The performance metrics analyzed are net energy consumption, travel time, and root-mean-square (RMS) acceleration. Two connected corridor scenarios are created to evaluate

King, Brian, Olson, Jordan, Hamilton, Kayla, Fitzpatrick, Benjamin, Yoon, Hwan-Sik, Puzinauskas, Paul

Performance Analysis of Cooperative Truck Platooning under Commercial Operation during Canadian Winter Season

12-07-02-0012

11/14/2023

The cooperative platoon of multiple trucks with definite proximity has the potential to enhance traffic safety, improve roadway capacity, and reduce fuel consumption of the platoon. To investigate the truck platooning performance in a real-world environment, two Peterbilt class-8 trucks equipped with cooperative truck platooning systems (CTPS) were deployed to conduct the first-of-its-kind on-road commercial trial in Canada. A total of 41 CTPS trips were carried out on Alberta Highway 2 between Calgary and Edmonton during the winter season in 2022, 25 of which were platooning trips with 3 to 5 sec time gaps. The platooning trips were performed at ambient temperatures from −24 to 8°C, and the total truck weights ranged from 16 to 39 tons. The experimental results show that the average time gap error was 0.8 sec for all the platooning trips, and the trips with the commanded time gap of 5 sec generally had the highest variations. The average number of disengagements increased when the

Jiang, Luo, Kheyrollahi, Javad, Koch, Charles Robert, Shahbakhti, Mahdi

Performance Requirements for Cooperative Adaptive Cruise Control (CACC) and Platooning

J2945/6_202310 (Current)10/26/2023

This standard provides the guideline for enhancements to adaptive cruise control (ACC) by the addition of wireless communication from relevant vehicles (V2V) and/or the infrastructure (I2V) to augment the ACC active sensing capability. The CACC system operates under driver responsibility and supervision and is limited to the following: Does only longitudinal control of the vehicle. Uses time gap control strategy similar to ACC. Motor vehicles covered in the scope of this document include light and heavy vehicles. The message elements to realize CACC and platooning are part of the scope. The initial release covers definitions for CACC and platooning and requirements for CACC, while a subsequent release will cover the platooning requirements

V2X Vehicular Applications Technical Committee

Performance Requirements for Cooperative Adaptive Cruise Control (CACC) and Platooning™ SET File

J2945/6S_202310 (Current)10/26/2023

This Abstract Syntax Notation (ASN.1) file precisely specifies the structure of the data used to support the implementation of SAE International Standard 2945/6. Using the ASN.1 specification, a compiler tool can be used to produce encodings as required by the encoding rules identified in the standard. Both this file and the SAE J2735 ASN.1 files are necessary to collectively implement the data exchange described in the J2945/6. The combined library can be used by any application (along with the additional logic of the application) to exchange the data over an interface conformant to J2945/6. SAE J2945/6 specifies the interface and requirements for Cooperative Adaptive Cruise Control (CACC) and Platooning. It provides the information necessary to build interoperable systems that support CACC, which rely on the exchange of Cooperative Control Messages. You may also be interested in: Performance Requirements for Cooperative Adaptive Cruise Control (CACC) and Platooning™ the J2945/6 PDF

V2X Vehicular Applications Technical Committee

Performance Requirements for Cooperative Adaptive Cruise Control (CACC) and Platooning™ ASN File

J2945/6A_202310 (Current)10/26/2023

V2X Vehicular Applications Technical Committee

Reference Generator for a Platoon of Position-Controlled Vehicles on a Curved Path

12-07-02-0009

10/06/2023

Vehicular automation in the form of a connected and automated vehicle platoon is demanding as it aims to increase traffic flow and driver safety. Controlling a vehicle platoon on a curved path is challenging, and most solutions in the existing literature demonstrate platooning on a straight path or curved paths at constant speeds. This article proposes an algorithmic solution with leader-following (LF) communication topology and constant distance (CD) spacing for platooning homogeneous position-controlled vehicles (PCVs) on a curved path, with each vehicle capable of cornering at variable speeds. The lead vehicle communicates its reference position and orientation to all the follower vehicles. A follower vehicle stores this information as a virtual trail of the lead vehicle for a specific period. An algorithm uses this trail to find the follower vehicle’s reference path by solving an optimization problem. This algorithm is feasible and maintains a constant inter-vehicle distance. The

Bhaskar, Rintu, Potluri, Ramprasad, Wahi, Pankaj

A Deep Neural Network Attack Simulation against Data Storage of Autonomous Vehicles

12-07-02-0008

09/29/2023

In the pursuit of advancing autonomous vehicles (AVs), data-driven algorithms have become pivotal in replacing human perception and decision-making. While deep neural networks (DNNs) hold promise for perception tasks, the potential for catastrophic consequences due to algorithmic flaws is concerning. A well-known incident in 2016, involving a Tesla autopilot misidentifying a white truck as a cloud, underscores the risks and security vulnerabilities. In this article, we present a novel threat model and risk assessment (TARA) analysis on AV data storage, delving into potential threats and damage scenarios. Specifically, we focus on DNN parameter manipulation attacks, evaluating their impact on three distinct algorithms for traffic sign classification and lane assist. Our comprehensive tests and simulations reveal that even a single bit-flip of a DNN parameter can severely degrade classification accuracy to less than 10%, posing significant risks to the overall performance and safety of

Kim, Insup, Lee, Ganggyu, Lee, Seyoung, Choi , Wonsuk

Effect of Platoon Configurations on the Anti-Disturbing Performance

12-07-01-0003

08/10/2023

In order to promote the actual application of the vehicular platoon, this study investigates the effect of the specific platoon configurations including predecessor following (PF), predecessor–leader following (PLF), and bidirectional following (BD), on the anti-disturbing performance from the linear to nonlinear perspective. First, based on the method of sensitivity of error propagation to the disturbance, a linear platoon model is established by considering an individual vehicle as a lumped-mass point. Then, the transfer function matrix from disturbance to spacing error is derived for sensitivity analysis. Finally, especially considering the inherent vehicle dynamics, the Burckhardt tire force model is adopted to construct a nonlinear platoon dynamics model for the nonlinear dynamics analysis. The results reveal the characteristics of each platoon configuration, as well as the design of control gains in terms of the anti-disturbing performance. The nonlinear dynamics property in high

Wu, Xiangji, Yang, Xiujian, Zhang, Shengbin, Wang, Shenyi

Prediction and Control of Connected Mixed Traffic under Different Information Flow Topologies

12-07-01-0001

07/28/2023

Different platoon controls of connected automated vehicles have been studied to improve the entire fleet’s overall energy efficiency and driving safety. The platoons can be used during highway cruising to reduce unnecessary braking, shorten required headway, and thus improve traffic capacity and fuel economy. They can also be used in urban driving to improve traffic efficiency at intersections. However, there remain two problems that prevent the technology from achieving maximum benefit. First, the presence of human-driven vehicles will change the behavior of the fleet and platoon control of connected mixed traffic. Second, the communication uncertainties impose negative impacts on the dynamics of the platoon. A high-performance state predictor for surrounding vehicles can reduce the human-driven vehicle’s influence and help handle communication uncertainties better. This article proposes a novel inverse model predictive control (IMPC)-based approach to capture and predict longitudinal

Guo, Longxiang, Jia, Yunyi

An Approach to Planning Scenic Routes by Integrating Dynamic Traffic Models with A* Algorithm

13-05-01-0002

04/27/2023

During the entry and exit of attraction viewing, the rapid generation of travel demand and converging traffic flows in a short period can easily pose safety hazards to people due to its complex terrain. This study aims to propose a path planning method that integrates a dynamic traffic model with the A* algorithm for the planning of scenic routes. The study first combines the cellular transport model (CTM) model with the Greenshield model as its dynamic traffic model and then improves the A* algorithm with the Morphin search tree algorithm (Morphin) as its scenic route planning. The results of the study show that the improved A* algorithm reaches the expected error of 10−4 after 21 ms using Matlab tests, and simulation tests are conducted in regular and complex sections of the scenic area. The results show that the improved A* algorithm has a significant improvement over the A* algorithm in node selection, and its performance indexes such as the number of inflection points and

Xiaoling, Ma

Simulating Traffic-wake Effects in a Wind Tunnel

2023-01-0950

04/11/2023

Road-vehicle platooning is known to reduced aerodynamic drag. Recent aerodynamic-platooning investigations have suggested that follower-vehicle drag-reduction benefits persist to large, safe inter-vehicle driving distances experienced in everyday traffic. To investigate these traffic-wake effects, a wind-tunnel wake-generator system was designed and used for aerodynamic-performance testing with light-duty-vehicle (LDV) and heavy-duty-vehicle (HDV) models. This paper summarizes the development of this Road Traffic and Turbulence System (RT2S), including the identification of typical traffic-spacing conditions, and documents initial results from its use with road-vehicle models. Analysis of highway-traffic-volume data revealed that, in an uncongested urban-highway environment, the most-likely condition is a speed of 105 km/h with an inter-vehicle spacing of about 50 m. Probability distributions for spacing and road speed were used to identify a range of suitable inter-vehicle spacings to

McAuliffe, Brian, Barber, Hali

On-Track Demonstration of Automated Eco-Driving Control for an Electric Vehicle

2023-01-0221

04/11/2023

This paper presents the energy savings of an automated driving control applied to an electric vehicle based on the on-track testing results. The control is a universal speed planner that analytically solves the eco-driving optimal control problem, within a receding horizon framework and coupled with trajectory tracking lower-level controls. The automated eco-driving control can take advantage of signal phase and timing (SPaT) provided by approaching traffic lights via vehicle-to-infrastructure (V2I) communications. At each time step, the controller calculates the accelerator and brake pedal position (APP/BPP) based on the current state of the vehicle and the current and future information about the surrounding environment (e.g., speed limits, traffic light phase). The target vehicle is a Chevrolet Bolt, an electric vehicle, which is outfitted with a drive-by-wire (DBW) system that allows external APP/BPP to command the speed of the vehicle, while the operator remains in charge of the

JEONG, Jongryeol, Dudekula, Ahammad Basha, Kandaswamy, Elangovan, Karbowski, Dominik, Han, Jihun, Naber, Jeffrey

New Controller Evaluation Techniques for Autonomously Driven Heavy-Duty Convoys

2023-01-0688

04/11/2023

Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance during operation. Drafting allows following vehicles to increase fuel economy and save money on refueling, whether that be at the pump or at a charging station. However, autonomous solutions are still in infancy, and controller evaluation is an exciting challenge proposed to researchers. This work brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP). Rather than utilize its emissions investigative benefits, the present work applies VSP to heterogeneous Class 8 Heavy-Duty truck platoons as a means of evaluating the efficacy of Cooperative Adaptive Cruise Control (CACC). VSP creates a bridge between types of passenger vehicles to compare

Snitzer, Philip, Stegner, Evan, Bentley, John, Bevly, David M., Hoffman, Mark

Quantifying the Energy Impact of Autonomous Platooning-Imposed Longitudinal Dynamics

2023-01-0896

04/11/2023

Platooning has produced significant energy savings for vehicles in a controlled environment. However, the impact of real-world disturbances, such as grade and interactions with passenger vehicles, has not been sufficiently characterized. Follower vehicles in a platoon operate with both different aerodynamic drag and different velocity traces than while driving alone. While aerodynamic drag reduction usually dominates the change in energy consumption for platooning vehicles, the dynamics imposed on the follow vehicle by the lead vehicle and exogenous disturbances impacting the platoon can negate aerodynamic energy savings. In this paper, a methodology is proposed to link the change in longitudinal platooning dynamics with the energy consumption of a platoon follower in real time. This is accomplished by subtracting a predicted acceleration from measured longitudinal acceleration. The real-time consumption calculation methodology is evaluated using data from simulated and experimental

Stegner, Evan, Snitzer, Philip, Bentley, John, Bevly, David M., Hoffman, Mark

Intersection Signal Control Based on Speed Guidance and Reinforcement Learning

2023-01-0721

04/11/2023

As a crucial part of the intelligent transportation system, traffic signal control will realize the boundary control of the traffic area, it will also lead to delays and excessive fuel consumption when the vehicle is driving at the intersection. To tackle this challenge, this research provides an optimized control framework based on reinforcement learning method and speed guidance strategy for the connected vehicle network. Prior to entering an intersection, vehicles are focused on in a specific speed guidance area, and important factors like uniform speed, acceleration, deceleration, and parking are optimized. Conclusion, derived from deep reinforcement learning algorithm, the summation of the length of the vehicle’s queue in front of the signal light and the sum of the number of brakes are used as the reward function, and the vehicle information at the intersection is collected in real time through the road detector on the road network. Finally, the proposed method is implemented

Lu, Gaohui, Zhan, Zhenfei, Rehman, Hamza, Chen, Xiatong, He, Xin

Effects of Vehicle Numbers and Vehicle Types on Drag Reduction of Platoons with Different Front-Edge Radius

2023-01-0951

04/11/2023

The platoon of intelligent vehicles can significantly reduce the aerodynamic drag, which has broad development prospects. This research numerically studies the effect of Reynolds number (Re = 3.32×105 to 19.94×105), the vehicle numbers (3-, 5-, 8-vehicle), and vehicle types (fastback, notchback, and squareback) on the platoon drag reduction with three different front-edge radius (R*=R/W×100 = 9.36, 4.68 and 2.34). The results show that when the Reynolds number is greater than 9.97×105, the drag coefficient ratio CD/CDi (CDi is the drag coefficient of the isolated vehicle) of each vehicle in the platoon is less affected by the Reynolds number. When R*=9.36, the averaged CD/CDi of the fastback platoon (even above 1) is higher than that of both the notchback platoon and the squareback platoon without front-edge separation at the leading vehicle due to the weakest shielding effect on the following car resulting from the prominent downwash wake. Compared with R*=9.36, when the flow

Wang, Dehua, Xia, Chao, Jia, Qing, Yang, Zhigang

Comparing the Performance of Different Heavy Duty Platooning Control Strategies

2023-01-0895

04/11/2023

Platooning is a promising technology which can mitigate greenhouse gas impacts and reduce transportation energy consumption. Platooning is a coordinated driving strategy where trucks align themselves in order to realize aerodynamic benefits to reduce required motive force. The aerodynamic benefit is seen as either a “pull” effect experienced by the following vehicles or a “push” effect experienced by the leader. The energy savings magnitude increases nonlinearly as headway (following distance) is reduced [1]. In efforts to maximize energy savings, cooperative adaptive cruise control (CACC) is utilized to maintain relatively short headways. However, when platooning is attempted in the real world, small transient accelerations caused by imperfect control result in observed energy savings being less than expected values. This study analyzes the performance of a recently developed nonlinear model predictive control (NMPC) platooning strategy over challenging terrain. The NMPC strategy is

Bentley, John William, Snitzer, Philip, Stegner, Evan, Bevly, David M., Hoffman, Mark

Situational Intelligence-Based Vehicle Trajectory Prediction in an Unstructured Off-Road Environment

2023-01-0860

04/11/2023

Autonomous vehicles (AV) are sophisticated systems comprising various sensors, powerful processors, and complex data processing algorithms that navigate autonomously to their respective goals. Out of several functions performed by an AV, one of the most important is developing situational intelligence to predict collision-free future trajectories. As an AV operates in environments consisting of various entities, such as other AVs, human-driven vehicles, and static obstacles, developing situational intelligence will require a collaborative approach. The recent developments in artificial intelligence (AI) and deep learning (DL) relating to AVs have shown that DL-based models can take advantage of information sharing and collaboration to develop such intelligence. However, most of these developments address only the requirements of urban environments, which are structured, and ignore the more challenging requirements of off-road environments, which are unstructured due to the lack of lane

Prasanna Kumar, Rahul, Jia, Yunyi

Flexible Architecture for Testing Connected Vehicles in Realistic Traffic

2023-01-0218

04/11/2023

Connected vehicles have the potential to transform the way we commute and travel in a multitude of ways. Vehicles will cooperate and coordinate with each other to solve problems appropriate for the environment in which they are operating. In this paper, we focus on the development of test equipment that includes the infrastructure and vehicles to measure and record all of the information necessary to quantify the performance of cooperative driving algorithms in realistic scenarios. The system allows tests to include real vehicles on the track and virtual vehicles in a digital twin. Real and virtual vehicles interact through the road-side units and test facility network, allowing each test vehicle to receive messages from virtual vehicles as well as the infrastructure. Messages transmitted from the test vehicles are received in the digital twin, allowing the real vehicle to interact with virtual vehicles. This provides the capability to test algorithms in congested traffic without the

Buller, William, Chase, Richard, Paki, Joseph E., Dudekula, Ahammad Basha, Naber, Jeffrey, Sarkar, Reuben

Deliver Signal Phase and Timing (SPAT) for Energy Optimization of Vehicle Cohort Via Cloud-Computing and LTE Communications

2023-01-0717

04/11/2023

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques. An emulation-based algorithm is applied to predict the traffic signal state changes to provide adequate prediction horizon (e.g., at minimum 2 minutes) for the

Ma, Jingtao, Bauer, Thomas, Ova, Kiel, Hatcher, Kyle, Robinette, Darrell, Jacquelin, Frederic, Santhosh, Pruthwiraj

Development of Truck Platooning System Including Emergency Braking Function with Vehicle-in-the-Loop (VIL) Testing

2023-01-0571

04/11/2023

Platoon is a system that connects vehicles through vehicle-to-vehicle (V2V) communication technology to maintain a short distance between vehicles while driving on the road. To improve fuel efficiency, many automotive original equipment manufacturers (OEMs) are interested in developing and demonstrating real-world platoon system. However, it is hard for heavy duty trucks to develop this system due to the difficulty of maintaining the targeted intervehicle distance not only for fuel efficiency but also for safety in case of emergency braking. Because of this critical safety issue in the emergency situation, the platoon system for heavy duty trucks can be hardly demonstrated or tested in real vehicle environment. The relatively complex system and the slow response characteristic of commercial vehicles makes this even more difficult. In this paper, focusing on the emergency braking function implemented through the V2V communication interface, we introduce the platoon system developed by

Hong, Jeong-Ki, Kim, Sangjun, Lim, Jong Su, Nam, Joohan, Min, Byeonghyeok, Lee, Chanhwa

An Approach to Model a Traffic Environment by Addressing Sparsity in Vehicle Count Data

2023-01-0854

04/11/2023

For realistic traffic modeling, real-world traffic calibration data is needed. These data include a representative road network, road users count by type, traffic lights information, infrastructure, etc. In most cases, this data is not readily available due to cost, time, and confidentiality constraints. Some open-source data are accessible and provide this information for specific geographical locations, however, it is often insufficient for realistic calibration. Moreover, the publicly available data may have errors, for example, the Open Street Maps (OSM) does not always correlate with physical roads. The scarcity, incompleteness, and inaccuracies of the data pose challenges to the realistic calibration of traffic models. Hence, in this study, we propose an approach based on spatial interpolation for addressing sparsity in vehicle count data that can augment existing data to make traffic model calibrations more accurate. This study will primarily assist in traffic modeling for Fuel

Patil, Mayur, Tulpule, Punit, Midlam-Mohler, Shawn

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