# Compression of GNSS Data with the Aim of Speeding up Communication to Autonomous Vehicles
## 8 Conclusions  
Several compression methods as well as a combination of different compression methods and their results have been presented. Compression using only Zip is about a saving of 90%. This is undoubtedly a substantial compression ratio, but unfortunately with quite a few shortcomings as noted in this work. It is possible to compress with a full method as suggested in this research and obtain a reduction of over 87% of all the raw information. Considering the good error resilience because of Huffman and sometimes sending raw information, it can be concluded that there is an evident trade-off here with a cost of about 3% compared to ZIP. A better compression ratio can be obtained by combining part of the method developed in this paper and then performing compression by ZIP. This algorithm outperforms the two previous and obtains a data reduction of about 94% (3% better than ZIP and 6% better than the Huffman-based method which we suggested here). Nevertheless, it should be noted that in the combined method, there is no good error resilience because Huffman Coding is not used. Our choice and recommendation are to use the difference method together with Huffman rather than a pure ZIP method or other combinations that we mentioned above. Figure 6: Calculation of entropy and average bit per symbols. We prefer the difference method together with Huffman because the other methods do not provide error resilience, even though they can slightly improve the compression ratio. It should also be noted that during the coding, we used static and not dynamic coding tables. This feature has pros and cons. It is common to have a static and known table in advance, because this is efficient and saves the need to update and transfer the compression tables. Everyone has the known tables and there is no need that the transferred information to include new tables each time. Yet, a custom table can generate a shorter average codeword. Therefore, we chose to use static tables as customary in most compression methods such as JPEG, TIFF, MP3 and more. We believe that using the methods presented in this paper can significantly improve the efficiency and speed of information transfer. This is particularly important nowadays since there is no use of NMEA data compression in GNSSes and not enough research and work has been done on this subject. Therefore, further attention should be given to NMEA raw data that is currently transmitted uncompressed. In a future study, we suggest checking how to improve the compression and reach optimal results by using alternative codes for Huffman's. Other methods that can be used without rounding the bits up like Arithmetic Coding should be considered. Also, a possibility of adding error resilience and/or error checking like checksum to the more efficient zip methods presented here (Diff&Mapping&Zip) can be considered. The Huffman code synchronizes after an error with almost 100% probability. That is, after several wrong code words, the Huffman algorithm automatically comes back to itself and starts reading real code words. In contrast, arithmetic coding does not synchronize after an error and all the data that is read and decoded after the error is wrong. The proposal to work with arithmetic coding improves the compression percentages, but it comes at the cost of no synchronization after an error, so a mechanism for synchronization after errors such as a checksum may possibly be considered. We also suggest considering in advance the possibility of not transmitting unchanged information in relation to the previous information (for example, if the vehicle is stopped at traffic lights or in a traffic jam). Conceptualization, Y.W. and A.R. ; methodology, A.R. ; software, A.R. ; validation, A.R. ; formal analysis, A.R. and Y.W. ; investigation, A.R. ; resources, A.R. ; data curation, A.R. ; writing--original draft preparation, A.R. ; writing--review and editing, A.R. and Y.W. ; supervision, Y.W. ; project administration, A.R. and Y.W.