Islam Mahmoud Aboelnaga

PPP_Mansoura is a new software that can process multi-GNSS data work on MATLAB environment and linked with C# in the preprocessing stage. It gives highly accurate results and provides a results file for each epoch, and the users can choose the GNSS system they want to run with the primary systems (GPS or GLONASS) and all this with simple MATLAB Code. For testing the software, we processed the raw data (RINEX 3) from 17 MGEX stations for 24 h data during 1-week with a 30-s interval time and submitted it to the new software and PPPH software. The averaged positioning errors obtained from PPP_Mansoura and PPPH were 5.14 mm and 6.9 mm respectively, for the East direction, 11.6 mm and 14 mm for the North direction, and 14.56 mm and 20.4 mm respectively for the Up direction, the averaged convergence time obtained from PPP_Mansoura and PPPH were 35.3 min and 54.47 min, so the results show that PPP_Mansoura give results with high accuracy can be comparable with PPP standards results and PPP software results.

Using Precise point positioning (PPP) technique can help to reach decimeters accuracy for positioning by using one receiver only. Since it set to track Global Navigation Satellite System (GNSS). Recently BeiDou and Galileo systems have been devolved periodically and increasing the number of working satellites. Addition to those all-global Navigation systems is able to receive triple frequency signals. The effect of using Multi constellation of GNSS and combination of different systems with each other’s need to be investigated. In this paper, four Multi GNSS EXPERIMENT (MGEX) stations with 24 hours observation files and 30 second interval time during a 1 week of averaged data of January 2020 (2134 GPS week) are used to investigate the accuracy of using combined solution of GNSS with 12 cases of study. Data were processed by PPPH program. To investigate the effect of using the different GNSS combinations while using the PPP method, contrast experiments have been tested by mixing dual frequency ionospheric-free PPP models in static mode with G only, GLO only, G + GLO, G+ B, GLO+B, G+GAL, GLO+GAL, GLO+B+GAL, GNSS, G +GAL+B, G+GLO+B and G+GLO+GAL combination cases, where G refers to GPS, GLO refers to GLONASS, GAL refers to Galileo and B refers to BeiDou. The results show that the combined GPS and Galileo observation in PPP solution improves the convergence time and gives the shortest convergence time of the 12 study cases with average value 53 minute and with minimum value 35 minute. By comparing the root mean square error (RMS) values, the combination of G+GL+B had the minimum RMS error in North and East direction with minimum value 1.2 cm, maximum value 1.8 cm and average value1.45 cm. And the combination of GLO+GAL+B had the minimum RMS errors in up directions with average value 2.775 cm and minimum 2.775 cm and maximum 4.5 cm. In conclusion, the results indicate that the combination of different GNSS can give more accurate solution of the PPP. The combined PPP has shown an improvement in the convergence time in the case of using combined of G and GAL observation, while the positioning accuracy after convergence has no shown significant improvement. The result of G+GAL+B give the minimum RMS error in North and East direction and the combination of GLO+GAL+B give the minimum RMS errors in up directions.

In pavement construction, the mechanical properties of pavement layers have been a crucial concern. Additions such as lime, organic polymer, and sodium chloride have been used as modifier for enhancing the California Bearing Ratio (CBR) value of the natural dolomite soil. This paper proposed regression models relating the CBR values and percentages increase of CBR to dosages of the used additives. Furthermore, the paper tested the performance of the Generalized Concentration Addition (GCA) analytical modelling of CBR enhancement related to using different mixes of additives. Lime-organic polymers mix has utilized to upgrade the CBR. Percentages of enhancement were measured and employed to assess the GCA model results. Results indicated that the highest CBR value of 136% was noticed at 30% of organic polymer. On the other hand, the lowest value of CBR value of 50.2% was noticed at 3% of lime. Furthermore, percentages of 9% lime, 5% sodium chloride, and 10% organic polymer were recommended to improve the CBR value of the base layer. Regression models showed high representativeness owing factors of correlation of determination (R2) higher than 90%. Moreover, GCA results showed good fit to laboratory measured percentage increase of CBR as R2 higher than 80% is gained with acceptable values of Root Mean Square Error (RMSE), Frictional Biases (FB) and Global Mean Biases (MB). Finally, percentages of 9% lime, 5% sodium chloride, and 10% organic polymer saved about 43.6%, 28.5% and 50% of the base layer thickness for the same materials respectively.

Recently, ridesharing has been noticed as an effective and sustainable mode of transport. In which, each passenger carries out a journey that benefits travelers and society greatly, such as reducing travel costs, reducing journey times, relieving road traffic congestions, preserving fuel and reducing air pollution. While the importance and efficiency of ridesharing, ridesharing among travelers has not been commonly utilized. This paper introduces an upgraded disaggregated utility model for a mode choice step in the four-step traffic demand model for transport of passengers in Tanta city - Gharbiya governorate. For the first time, the analysis in this paper includes ridesharing mode in addition to other three common modes; private vehicle, bus, and taxi . The aim of this research is to involve the ridesharing mode and new parameters in the mode choice analysis of the case study. This is done by including additional parameters such as travel cost and comfortable in addition to travel time. Based on surveys, the developed Multinomial logit utility models have been assessed using the McFadden pseudo R2 values. The values demonstrated high compatibility of results with real data as pseudo R2 values ranges between 0.2 and 0.4. In addition, all utility models developed for modes are found to have P-values less than 0.05 indicating the significance of the considered utility characteristics.