One of the most challenging tasks for drivers is parallel parking, which is why automatic parking systems are becoming a popular feature on some vehicles. However, the cost of designing and implementing such computing-intensive systems can significantly increase a vehicle's price, creating a barrier to adding the feature in many models.
Now researchers have developed a more efficient automated parking guidance control strategy that mimics the approach to parallel parking commonly used by human drivers. This new, simpler automatic parking method has the potential to reduce the computing and storage resources required in the vehicle, which could lead to lower system costs and higher adoption rates by vehicle manufacturers.
The results of the research is published in IEEE/CAA Journal of Automatica Sinica, a joint publication of the Institute of Electrical and Electronics Engineers (IEEE) and the Chinese Association of Automation (CAA).
"We observed the way students typically learn how to parallel park in driving schools and determined that they use a relatively simple three-step process," said Li Li with the Department of Automation at Tsinghua University in Beijing, China. "Unlike conventional approaches to automatic parking, our new method focuses on simplifying control rules and strategies, rather than adding complicated feedback controllers and technical assistance systems."
The three-step guidance control strategy is based on the parallel parking method taught in many driver education classes. First, drivers align their vehicle next to the car in front of the open parking space. Next, the drivers back their vehicle up while making a hard-right turn until reaching a critical angle position. Finally, the drivers turn the steering wheel to a hard-left position and continue backing up until arriving in the parked position.
"By reducing the parking process to three simple steps, we limit the number of variables to five, of which the maximum allowable steering angle and velocity can be determined in advance," said co-author Lingxi Li, associate professor at Indiana University-Purdue University in Indianapolis. "Therefore, we can focus on controlling for just three variables?the starting point, the size of the open parking space and the critical angle position. This greatly simplifies designing and implementing the programming and computational resources for the onboard parking system."
The researchers plan to explore other methods of integrating human driving experiences in hybrid-augmented intelligence systems for future intelligent vehicle applications.
Fulltext of the paper is available: http://www.ieee-jas.org/en/article/doi/10.1109/JAS.2019.1911855
IEEE/CAA Journal of Automatica Sinica aims to publish high-quality, high-interest, far-reaching research achievements globally, and provide an international forum for the presentation of original ideas and recent results related to all aspects of automation. Researchers (including globally highly cited scholars) from institutions all over the world, such as MIT, Yale University, Stanford University, University of Cambridge, Princeton University, select to share their research with a large audience through JAS.
IEEE/CAA Journal of Automatica Sinica is indexed in SCIE, EI, Scopus, etc. The latest CiteScore is 5.31, ranked among top 9% (22/232) in the category of "Control and Systems Engineering", and top 10% (27/269, 20/189) both in the categories of "Information System" and "Artificial Intelligence". JAS has been in the 1st quantile (Q1) in all three categories it belongs to.
Why publish with us:
- Fast and high quality peer review;
- Simple and effective online submission system;
- Widest possible global dissemination of your research; Indexed in SCIE, EI, IEEE, Scopus, Inspec.
JAS papers can be found at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6570654 or http://www.ieee-jas.org
IEEE/CAA Journal of Automatica Sinica