Recent Advances in Autonomous Vehicles

Dear Colleagues,

Autonomous vehicles have attracted a wide array of attention from engineers and researchers in recent years. Many works have been conducted; as a consequence, we can now use a driverless car named Waymo in several cities in America. In addition, autonomous vehicles used to deliver goods are also in development. However, we have still not achieved commercial certificated autonomous vehicles that can be used in an open environment.

The main objective of driving is to keep traffic safe and fluid. The term “safe traffic” includes infrastructure, goods, and traffic users being safe, including passengers in the subject vehicle. Safe autonomous driving is a task that combines many well-trained capacities, such as the capacity of observing, analyzing, predicting, anticipating, deciding, and acting at any time in order to adapt the dynamics of the vehicle to the traffic situation in terms of cancelling disturbances from the environment. Thus, the development of autonomous vehicles requires many advances in technology and efforts in the development of driving strategies and the management of fleets of autonomous vehicles.

We expect that autonomous vehicles will be popular in the very near future, meaning that everybody can profit from this safe, stressless means of transport with all the required comfort of private cars.

This Special Issue focuses on recent advances in research and practice for the development of autonomous vehicles. Submissions to this Special Issue are welcome to focus on, but not be limited to, the following topics:

• Advances in intelligent sensors: cameras, radars, and lidars;
• Advances in data fusion for sensors to build an efficient perception system;
• Advances in decision-making;
• Integration of situation awareness and anticipation in the driving algorithm;
• Integration of disturbance cancellation;
• Integration of V2X, V2V, and X2V communication to increase driving capacity as well as the safety of traffic;
• Advances in the management of fleets of autonomous vehicles;
• Advances in itinerary creation for the autonomous vehicle;
• Advances in trajectory calculation for autonomous control;
• Methods of verification and validation of autonomous driving by simulation or from the data collection during the ride;
• Scenarios for the test and validation of autonomous vehicles.

Dr. Soualmi Boussaad
Dr. Duc-Thang Nguyen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. World Electric Vehicle Journal is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• autonomous driving
• actuator control scheme
• sensor data processing
• data fusion
• V2V and V2X communication
• collective perception
• digital maps
• localization
• trajectory calculation
• path planning
• decisions
• distributed decision making
• central decision making
• reasoning
• problem solving
• experience-oriented artificial intelligence
• human-like intelligence
• machine learning and deep learning
• behavior verification and validation
• fleet management