IEEE Transactions on Intelligent Transportation Systems
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Year: 2023 | Volume: 24 | Issue: 9
IEEE INTELLIGENT TRANSPORTATION SYSTEMS SOCIETY
Year: 2023 | Volume: 24 | Issue: 9
Scanning the Issue
Year: 2023 | Volume: 24 | Issue: 9
Edge Intelligence in Intelligent Transportation Systems: A Survey
Publication Year: 2023,Page(s):8919 - 8944
Cited by: Papers (49)
Edge intelligence (EI) is becoming one of the research hotspots among researchers, which is believed to help empower intelligent transportation systems (ITS). ITS generates a large amount of data at the network edge by millions of devices and sensors. Data-driven artificial intelligence (AI) is at the core of ITS development. By pushing the AI frontier to the network edge, EI enables ITS AI applic...Show More
A Survey on Privacy-Preserving Electronic Toll Collection Schemes for Intelligent Transportation Systems
Amirhossein Adavoudi Jolfaei;Abdelwahab Boualouache;Andy Rupp;Stefan Schiffner;Thomas Engel
Publication Year: 2023,Page(s):8945 - 8962
Cited by: Papers (6)
As part of Intelligent Transportation Systems (ITS), Electronic toll collection (ETC) is a type of toll collection system (TCS) which is getting more and more popular as it can not only help to finance the government’s road infrastructure but also it can play a crucial role in pollution reduction and congestion management. As most of the traditional ETC schemes (ETCS) require identifying their use...Show More
Uncertainties in Onboard Algorithms for Autonomous Vehicles: Challenges, Mitigation, and Perspectives
Kai Yang;Xiaolin Tang;Jun Li;Hong Wang;Guichuan Zhong;Jiaxin Chen;Dongpu Cao
Publication Year: 2023,Page(s):8963 - 8987
Cited by: Papers (28)
Autonomous driving is considered one of the revolutionary technologies shaping humanity’s future mobility and quality of life. However, safety remains a critical hurdle in the way of commercialization and widespread deployment of autonomous vehicles on public roads. Safety concerns require the autonomous driving system to handle uncertainties from multiple sources that are either preexisting, e.g....Show More
EU ENSEMBLE Project: Reference Design and Implementation of the Platooning Support Function
Antonius J. C. Schmeitz;Dehlia M. C. Willemsen;Simon Ellwanger
Publication Year: 2023,Page(s):8988 - 9003
Cited by: Papers (4)
Platooning is a cooperative driving technology for driving in a longitudinal formation. Vehicle-to-vehicle (V2V) communication is the key enabling technology. Platooning is considered to be a closed application between well-known participants that use V2V data for their operation. For the deployment of platooning, multi-brand, i.e. interoperable, solutions are paramount. To achieve this, the Europ...Show More
A Network Traffic Model for the Control of Autonomous Vehicles Acting as Moving Bottlenecks
Publication Year: 2023,Page(s):9004 - 9015
Cited by: Papers (3)
In this work we present a traffic model to simulate network-level traffic evolution under the impact of controlled autonomous vehicles acting as moving bottlenecks. We first extend the Newell-Daganzo method to track the trajectories of moving bottlenecks and calculate the cumulative number of vehicles passing each moving bottleneck. By integrating the solutions to the cumulative number of vehicles...Show More
Unprotected Left-Turn Behavior Model Capturing Path Variations at Intersections
Publication Year: 2023,Page(s):9016 - 9030
Cited by: Papers (20)
Path dispersion (the spatial distribution of vehicular paths) is an important feature of traffic flow inside intersections and differs from traffic flow running along traffic lanes at road segment, especially under conflicting movements. The path dispersion reflects the operational features of traffic flow and is related to driving behaviour, arrival flow patterns, layout design, and the traffic c...Show More
The Surface Accelerations Reference—A Large-Scale, Interactive Catalog of Passenger Vehicle Accelerations
Publication Year: 2023,Page(s):9031 - 9040
There is a need for a large-scale, real world, diverse, and context rich vehicle acceleration catalog that can be used to design, analyze, and compare various intelligent transportation systems. This paper fulfills three primary objectives. First, it provides such a catalog through the Surface Accelerations Reference, which is openly available as an interactive analytics tool as well as an open an...Show More
Blockchain Empowered Secure Video Sharing With Access Control for Vehicular Edge Computing
Publication Year: 2023,Page(s):9041 - 9054
Cited by: Papers (6)
The dramatically growing trend of vehicles equipped with driving camera recorders has allowed realizing real-time crowdsourced video sharing in vehicular edge computing (VEC). Such cameras can assist in monitoring objects directly in front of and behind the vehicles, enabling them to provide important visual information through real-time video streaming in case of possible accidents. Exploiting th...Show More
Treating Noise and Anomalies in Vehicle Trajectories From an Experiment With a Swarm of Drones
Vishal Mahajan;Emmanouil Barmpounakis;Md. Rakibul Alam;Nikolas Geroliminis;Constantinos Antoniou
Publication Year: 2023,Page(s):9055 - 9067
Cited by: Papers (6)
Unmanned aerial systems, known as “drones,” are relatively new in collecting traffic data. Data from drone videography can have potential applications for traffic research. Drones can record the vehicles from their aerial point-of-view and provide their naturalistic driving behavior. Processing raw data from drones to remove noise and anomalies is crucial to ensure that the data are fit for subseq...Show More
An Intersection-Based QoS Routing for Vehicular Ad Hoc Networks With Reinforcement Learning
Lanlan Rui;Zhibo Yan;Zuoyan Tan;Zhipeng Gao;Yang Yang;Xingyu Chen;Huiyong Liu
Publication Year: 2023,Page(s):9068 - 9083
Cited by: Papers (8)
Vehicular ad hoc networks (VANETs) have the characteristics of high mobility, frequently changing topology and uneven distribution, which made it a challenge to design an efficient and robust routing protocol with low latency and high packet delivery rate. Currently, intersection-based routing method and full-path based routing method are two popular solutions for the packet routing in VANETs. Alt...Show More
Predictive Display With Perspective Projection of Surroundings in Vehicle Teleoperation to Account Time-Delays
Jai Prakash;Michele Vignati;Daniele Vignarca;Edoardo Sabbioni;Federico Cheli
Publication Year: 2023,Page(s):9084 - 9097
Cited by: Papers (14)
Teleoperation provides the human operator with sophisticated perceptual and cognitive skills in an over-the-network control loop. It gives hope of addressing some challenges related to vehicular autonomy which is based on artificial intelligence by providing a fallback plan. Variable network time-delay in data transmission is the major problem in teleoperating a vehicle. On 4G network, variability...Show More
A Network Flow Approach to Battery Electric Bus Scheduling
Justin Whitaker;Greg Droge;Matthew Hansen;Daniel Mortensen;Jacob Gunther
Publication Year: 2023,Page(s):9098 - 9109
Cited by: Papers (6)
A major challenge to adopting battery electric buses into bus fleets is the scheduling of the battery charging while considering route timing constraints and battery charge. This work develops a scheduling framework to balance the use of slow and fast chargers assuming the bus routes and charger locations are fixed. Slow chargers are utilized when possible to lower the cost of charging and fast ch...Show More
Stochastic Linear Quadratic Optimal Control of Speed and Position of Multiple Trains on a Single-Track Line
Chiara Bersani;Matteo Cardano;Stefano Lavaggi;Roberto Sacile;Simona Sacone;Mohamed Sallak;Enrico Zero
Publication Year: 2023,Page(s):9110 - 9120
Cited by: Papers (2)
In the European Rail Traffic Management System (ERTMS), the Route Control Centre System (RCCS) supervises the distance between consecutive trains and generates movement authorities, i.e. the permission for a train to move to a specific location within the constraints of the infrastructure and with supervision of speed. In this work, a control model aimed at determining the speed and position of a ...Show More
Accelerating Two-Phase Multiobjective Evolutionary Algorithm for Electric Location-Routing Problems
Publication Year: 2023,Page(s):9121 - 9136
Cited by: Papers (5)
Electric location-routing problem is a challenging problem consisting of the optimization of electric vehicle routing and charging facility location, simultaneously. Existing algorithms generally adopt the two-phase search strategy to alternately optimize the routing and the location. However, they are usually criticized for the inefficiency as the problem scale increases. In order to improve the ...Show More
Crowd Management Through Optimal Layout of Fences: An Ant Colony Approach Based on Crowd Simulation
Xiao-Cheng Liao;Wei-Neng Chen;Xiao-Qi Guo;Jinghui Zhong;Xiao-Min Hu
Publication Year: 2023,Page(s):9137 - 9149
Cited by: Papers (14)
The increasing population density in public places necessitates urgent attention to address safety concerns via effective crowd management. In many congested scenarios such as peak-hour subway stations, the utilization of fences to guide crowd movement has become a widely adopted approach to alleviate congestion. This work presents a method that combines crowd simulation and management, focusing o...Show More
Enhancing the Efficiency of Electric Vehicles Charging Stations Based on Novel Fuzzy Integer Linear Programming
Shahid Hussain;Reyazur Rashid Irshad;Fabiano Pallonetto;Qasim Jan;Saurabh Shukla;Subhasis Thakur;John G. Breslin;Yun-Su Kim;Muhammad Ahmad Rathore;Hesham El-Sayed
Publication Year: 2023,Page(s):9150 - 9164
Cited by: Papers (11)
The electric vehicles (EVs) charging stations (CSs) at public premises have higher installation and power consumption costs. The potential benefits of public CSs rely on their efficient utilization. However, the conventional charging methods obligate a long waiting time and thereby deteriorate their efficiency with low utilization. This paper suggests a novel fuzzy integer linear programming and a...Show More
Enhancing the Efficiency of Electric Vehicles Charging Stations Based on Novel Fuzzy Integer Linear Programming
Shahid Hussain;Reyazur Rashid Irshad;Fabiano Pallonetto;Qasim Jan;Saurabh Shukla;Subhasis Thakur;John G. Breslin;Yun-Su Kim;Muhammad Ahmad Rathore;Hesham El-Sayed
Year: 2023 | Volume: 24 | Issue: 9
The Static Adjustment Method of Secondary Suspension Load for Six-Axle Locomotives via Modified Mayfly Optimization Algorithm
Publication Year: 2023,Page(s):9165 - 9174
The static distribution of the static secondary suspension load has a significant impact on the adhesion, rim wear and passenger comfort of the locomotive. At present, the locomotive secondary suspension load adjustment is mainly realized by artificial padding to adjust the height of the spring. This process is not predictable, so it is difficult to complete the adjustment at one time, and it is l...Show More
Logistics in the Sky: A Two-Phase Optimization Approach for the Drone Package Pickup and Delivery System
Fangyu Hong;Guohua Wu;Qizhang Luo;Huan Liu;Xiaoping Fang;Witold Pedrycz
Publication Year: 2023,Page(s):9175 - 9190
Cited by: Papers (18)
The application of drones in last-mile distribution has been a contentious research topic in recent years. Existing urban distribution modes mostly depend on trucks. This paper proposes a novel package pickup and delivery mode and system wherein multiple drones collaborate with automatic devices. The proposed mode uses free areas on top of residential buildings to set automatic devices as delivery...Show More
An Optimal Nonlinear Model Predictive Control- Based Motion Cueing Algorithm Using Cascade Optimization and Human Interaction
Mohammad Reza Chalak Qazani;Houshyar Asadi;Yutao Chen;Moloud Abdar;Mansour Karkoub;Shady Mohamed;Chee Peng Lim;Saeid Nahavandi
Publication Year: 2023,Page(s):9191 - 9202
Cited by: Papers (5)
Nonlinear model predictive control has been used in motion cueing algorithms recently to consider the nonlinear dynamics model of the system. The entire motion cueing algorithm indexes, including the physical and dynamical constraints of the actuators and physical constraints of passive joints, can be controlled with precision using nonlinear model predictive control. However, several weighting pa...Show More
Benchmarking Probabilistic Deep Learning Methods for License Plate Recognition
Franziska Schirrmacher;Benedikt Lorch;Anatol Maier;Christian Riess
Publication Year: 2023,Page(s):9203 - 9216
Cited by: Papers (2)
Learning-based algorithms for automated license plate recognition implicitly assume that the training and test data are well aligned. However, this may not be the case under extreme environmental conditions, or in forensic applications where the system cannot be trained for a specific acquisition device. Predictions on such out-of-distribution images have an increased chance of failing. But this f...Show More
The Interacting Multiple Model Smooth Variable Structure Filter for Trajectory Prediction
Publication Year: 2023,Page(s):9217 - 9239
Cited by: Papers (14)
An autonomous vehicle would benefit from being able to predict trajectories of other vehicles in its vicinity for improved safety. In order for the self-driving car to plan safe trajectories, paths of nearby vehicles are required to be predicted for risk assessment, decision making, and motion planning. In this study, a trajectory prediction algorithm based on the Interacting Multiple Model (IMM) ...Show More
CrackFormer Network for Pavement Crack Segmentation
Publication Year: 2023,Page(s):9240 - 9252
Cited by: Papers (23)
In this paper, we rethink our earlier work on self-attention based crack segmentation, and propose an upgraded CrackFormer network (CrackFormer-II) for pavement crack segmentation, instead of only for fine-grained crack-detection tasks. This work embeds novel Transformer encoder modules into a SegNet-like encoder-decoder structure, where the basic module is composed of novel Transformer encoder bl...Show More
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