Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering

Develop Trip Generation Model for City -

AHMED ELKAFOURY1,*, ABDELAZIM M. NEGM1, MOHAMED H. ALY2, MAHMOUD F. BADY3 1 Environmental Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), P.O. Box 179, New Borg Al-Arab City, 21934 Alexandria, Egypt. 2 Transportation Engineering Department, Faculty of Engineering, University of Alexandria, 11432 Alexandria, Egypt. 3 Energy Resources Engineering Department,, Egypt-Japan University of Science and Technology (E-JUST), P.O. Box 179, New Borg Al-Arab City, 21934 Alexandria, Egypt. * Corresponding author: [email protected]

Abstract— This paper tends to introduce a trip generation model for Alexandria city-Egypt. This model can be implemented in the transportation planning process of the city since the city suffers from harsh transportation and travel problems. The model relates daily exchanged numbers (Q and Z) of trips at different Transportation Analysis Zone (TAZs) to its socio-economic data. Analysis of socio-economic and demographic data of different TAZs has been performed. Zonal data has been involved in Multiple Linear Regression (MLR) technique. Investigate attributes affect each of trip generation and trip attraction, the significant level of individual socio-economic variables for Q and Z has been statistically evaluated. Statistical indicators have been used to assess and verify the performance of the developed trip generation models. The model shows good performance since the models introduced acceptable CR values of 0.55 for Q model and higher value of 0.72 for Z model, NMSE 0.39 and 0.11 for Q and Z models respectively, and MG of 0.73 and 0.85 respectively.

Key-Words—Alexandria, Socio-economic data, Transportation planning, Trip generation model, Multiple Linear Regression (MLR) daily trips is a function of set of independent variables. This 1. Introduction method can be applied to any situation since the data is Thanks to the rapid increase in population numbers and regression analysis provided [4]. associated economic growth, the travel demand in urban areas Alexandria city, second largest city in Egypt after Cairo, is explicitly increasing. Under the umbrella of sustainable and with its 32 km along the coast of Mediterranean, it holds two environmental urban development planning, the role of the major Egyptian seaports named Alexandria seaport and El transportation planner is to manage and introduce different seaport which handles about 80% of the Egyptian transportation policies to give urban authorities the tool to import and export movements. It has suffered from severe cape with this increase in travel demand. This is performed transportation problems. The review showed little number of through modeling the transportation behavior and the research papers and studies related to transportation system transportation system to infer the problem key issues. And analysis of the city. The objective of this research is to consequently, proposing different tested alternatives to relieve develop a trip generation (production / attraction) model for these problems daily trips in Alexandria city. First, the zoning system of the In the four-stage prediction method, trip generation city has been introduced. On Transportation Analysis Zone predictions are the first step of the traffic demand prediction (TAZ) level, socio-economic, demographic, and trip process in the traditional four stage prediction method. It interchange data has been canalized. Multiple linear predicts the number of trips originating in or destined for a Regression (MLR) technique has been incorporated to develop particular traffic analysis zone. Every trip has two ends - trips the trip generation models. Finally, performance of the models origin zone and trips destine zone [1]. The reliability of has been statistically analyzed. This model helps mainly in the forecasting results influences the following steps such as trip urban transportation planning process of the city. distribution, mode split, and traffic assignment. Therefore, 2. Alexandria city transportation zoning improved trip generation models are needed to improve system forecasting precision [2]. To analyze the transportation and traffic situation in the From the transport demand perspective, the users’ most study area, there should be a proper splitting of the area into relevant characteristic is their socioeconomic level [3]. One of traffic analysis zones (TAZ). TAZs are the way to inventories the widely used of these methods makes use of regression the socio-economic, transportation systems, and traffic-related analysis using data collected in travel survey. The number of data of the study area on a geographical scale, aiming to

ISBN: 978-1-61804-358-0 153 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering divide a large set of region information into a number of have an explicit influence on the daily trip production rates. spatially contiguous regions [5]. For Alexandria city as the This is because those two categories represent the student and study area in this research, the system invoked coincide with the employees respectively. the administrative division (zones) of Alexandria city. This As shown in Fig. 1, on the districts scale, a reflection of the means that there are 13 TAZs for Alexandria city. They are, El same age categories trends for the whole city is noticed. Only Monatza, El Raml, , , Bab Sharq, El El Amria district breaks this role as only 16% of its population Atarin, El Manshia, , El Laban, Mina El Basal, is between 35 to 60 years old and about 17% of population is , El Dekhela, and El Amria. The selection of this between 25 to 35 years old. This can be accounted for that this transportation zoning system is to ensure accurate data district is an industrial and hand working area in which these providence since the socio-economic and travel demand data age categories are the power for that type of work. provided is at the nexus of the administrative division scale. 3.3 Income Levels 3. Analysis of socio-economic and The investigation of income level data of population reflects its implication on the quality of life. Usually, as the income demographic data level increases, the trip production rates increase in the sequel. This section analysis the socio-economic characteristics for Old TAZs of Alexandria which have high density population Alexandria city's 13 TAZs in year 2006 Based on data including Moharam Bek, El Manshia, Karmoz, El Laban provided from [6], [7], [8], [9], [10], [11]. besides Mina El Basal zones, are the settle of high proportion of low income households. About 35%, 29%, 64%, 35%, and 3.1 Population 40% of population in those zones respectively represents low In year 2006, Alexandria city holds about 4 million income satisfaction. The biggest portion of population among inhabitants representing 5.6% of total population number of all Alexandria city zones that reported high income level is in Egypt. the analysis of population characteristics in Alexandria Sidi Gaber. In which about 81% of population have high city zones (Table 2) indicates that the most populous zone is income level. Also, big portion of families reside the low El Monatza which holds 1,173,803 inhabitants representing population densities zones (Bab Sharq, El Dekhela, and El % of total population in the city. In the second rank, El Monatza) reports high income level. See Fig. 2. Raml zone holds 19% of the total city population (752,371 inhabitants). The least number of populations among all zones 3.4 Illiterate levels exists in El Manshia which holds only 1% of the city The illiterate levels in Alexandria city districts increases in population (23,616 inhabitants). This can be explained as this western districts than eastern districts. This is clear in Figure 5 zone is a trading zone and did not hold many residential which illustrates the illiterate levels in population with ages buildings. between 15 to 45 years old in different districts for year 2006. As an indicator, high population density areas increase the This reveals the relation between portions of population of low cost of urban transport systems, but for example less for the income level in the district and the illiterate levels. implementation of rail system than other modes [12]. A look on the population density (person/km2) all over the city zones of the zones indicates relatively high gross population density (The number of people inhabiting an urban area / total area of urban land) and residential population density (The number of people living in an urban area divided by the area of residential land). For the whole city, the average gross population density and residential population density are 25,706 (persons/km2) and 125,644 (persons/km2) in order. Old zones including Moharam Bek, El Manshia, Karmoz, El Laban are indicated as high density population zones as these are the origin place of Alexandrian inhabitants of the city. All over Alexandria city, the average annual percentage increase in population numbers is 1.6%. This rate is less than Fig. 1 Distribution of population of different districts among different the yearly national rate of increase in population in the same age groups in year 2006. time period which is 2.05%. In El districts, which contain only 7.42% of the population with low income level, the illiterate level is the 3.2 Age Characteristics smallest among all districts. As the low income portion of The trip production rates distinguish for different age population increases in western districts, the illiterate level categories. For Alexandria city, the majority of the population increases to reach its peak in El Amria district. In which, the (42%) in year 2006 is less than 15 years old. The second illiterate level is about 22% of population with ages between dominating age category in the city is the population who has 15 to 45 years. See Fig. 3. ages between 35 to 60 years old. Former categories properly

ISBN: 978-1-61804-358-0 154 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering

3.5 Employment In order to analyze the employment data, the total number of employees is different zones has been projected based on employment data of year 1996 and year 2002 mentioned in. From which, an average annual growth rate of employment has been derived for different zones and has found to be of 2.2% per year. Based on this rate, the inventory data of employment for different zones in year 2006 have been estimated and results are shown in Table I. El Montaza zone holds the hugest employment power with 173066 employees in year 2006. This is suitable for this zone which holds the highest population number among all zones. The second place is occupied by the holder of second highest population number Fig. 3 Illiterate level in different districts of Alexandria city in year (El Raml zone) which holds 149351 employees. The smallest 2006 number of employees is recorded in El Laban zone with only 24420 employees. Total number of employees in Alexandria 3.7 Land and Building Value city in year 2006 is 1056564. El Dekhela TAZ has the highest land value among all zones. The land value in it is 15 thousand Egyptian pounds per 3.6 Car ownership square meter (L.E/m2). At the nexus, the value of the square The analysis of private cars numbers in the Alexandria meter of buildings is relatively high with a 3250 (L.E/m2) of city illustrates the following facts: building. Sidi Gaber district have the second highest land 1) Total private cars number in Alexandria city in year 2006 value with 8500 (L.E/m2), but it holds the highest building is 334947, value in the city with 4000 (L.E/m2). Old zone in the city 2) The number of private car increase yearly by a rate of which holds high population numbers and high population 6.5% yearly, densities, including El Manshia, El Laban, and Moharam Bek 3) Car ownership is about 84 car/1000 inhabitant, and besides El Gomrok zone, have a relatively convergent land 4) Car ownership per 1000 inhabitants increases by a rate of values. Mina El Basal zone signed the lowest land value 4.1% yearly. and building value of 600(L.E/m2), and 400 (L.E/m2) in order. Land and building values for different zones in illustrated in Fig 4. 3.8 Use of dwelling According to the 2006 Population and Housing Census, most of the dwellings of Alexandria are used for residential purposes. In all zones, residential usage of dwellings shares the biggest percentage among all usage categories. The usage of buildings as for work shares the least percentage in all zones except in El Atarin and El Manshia zones. In these zones, using building for work purposes shares 35,3% and 32,6% of the total buildings number. Distribution of using purposes of buildings in different zones is shown in Fig. 5.

4. Land uses Alexandria city is extended for 32 km parallel to the sea with a narrow costal stretch of a width ranges between 1 to 5 kilometers. As illustrated in Figure 8, the prevailing land use purpose of the urbanized land all over the zones of Alexandria Fig. 2 Distribution of population of Alexandria city TAZs among is the residential purpose. It shares the same percentage in El different income level groups in year 2006. Montaza, El Raml, and El Dekhela zones with about 82% of the zones’ areas. In all zones, except El Montaza, Bab Sharq, and El Gomrok, the second dominating land use purpose is the Economical land use. The second prevailing land use in El Montaza zone is the Educational land use purpose. This is at the nexus of the educational situation analysis mention before which indicated El Montaza as obtaining the highest number of educational places in any district. Utilities occupy the lowest land use purpose in almost all zones. Other services including health, religious, roads, and open areas; which are

ISBN: 978-1-61804-358-0 155 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering indicated in Fig. 6 as (Others) represent high contribution land 2) High population number in El Montana zone (Highest use (33%) in among all TAZs).

Fig. 5 Use of dwelling of different TAZs of Alexandria city.

Fig. 4 Land and building value of different TAZs of Alexandria city in year 2006 El Gomrok zone, while it shows lower contribution in other zones. 5. Travel demand and trip characteristics The Origin-Destination (O/D) matrix describes the travel demand commuted between pairs of transportation zones in the study area. As illustrated in Table 7, in year 2006, the total daily number of trips exchange between all transportation zones in Alexandria city is 4242773 trip/day. From which, 40% are inter-zonal trips and 60% are exchange trips between pairs of zones. Analysis indicates that the maximum number of exchanged trips is 178854 trip/day. This travel demand is generated from El Montaza zone to El Raml zone. This refers Fig. 6 Land use breakdown of different TAZs of Alexandria city. to: 1) The higher attractively between the two zones due to the Fig. 6 Land use breakdown of different TAZs of Alexandria city in year 2006 short travel distance between them. 3) The huge number of employees in El Montana zone (First

TABLE 1. ORIGIN DESTINATION MATRIX OF ALEXANDRIA CITY IN YEAR 2006 Mina Total trip El Sidi Bab Moharam El El El El El El TAZ Elmontazah Karmoz El production Raml Gaber Sharq Bek Atarin Manshia Gomrok Laban Dekhela Amria Basal (Q)

Elmontazah 228303 178854 63206 65750 28916 27098 11069 14950 3341 4528 5735 2891 3296 637937

El Raml 141748 370739 120096 107045 40124 37117 22681 18481 3328 4243 5718 6069 5013 882402

Sidi Gaber 14944 35707 134534 68183 11861 17409 9405 10222 2224 2264 3936 2329 1388 314406

Bab Sharq 15797 33964 60983 195065 70008 64066 44892 15910 4234 3713 6174 3205 2137 520148 Moharam 6690 17116 63325 151894 262013 125027 68886 21810 5710 18964 15640 5788 2246 765109 Bek El Atarin 1410 5806 1572 18937 24248 85072 16437 10890 2054 2807 2942 1274 701 174150

El Manshia 898 3030 1108 9304 4304 10097 45336 14963 3135 1252 2307 670 718 97122

El Gomrok 2133 7685 2505 23416 10151 12842 1564 18688 3776 3837 7849 2491 2565 99502

El Laban 744 2767 1449 7067 7527 7317 6594 9138 13294 3157 7247 1327 1169 68797

Karmoz 3437 9090 5035 23215 32301 30439 20583 45223 56307 142777 71377 13621 7334 460739 Mina El 1800 5574 2885 9541 11424 8543 8718 8342 5215 12803 31140 6038 4059 116082 Basal El Dekhela 180 175 359 1804 1817 1016 10929 12552 7541 8668 12579 32989 11717 102326

El Amria 27 171 31 92 74 57 53 214 105 125 153 701 2250 4053 Total trip 418111 670678 457088 681313 504768 426100 267147 201383 110264 209138 172797 79393 44593 4242773 attracted (Z)

ISBN: 978-1-61804-358-0 156 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering

rank in number of employees among all zones) attributes affect each of trip generation and trip attraction, the 4) High portion of population (about 46% of population) significant level of individual socio-economic variables for Q with and Z has been statistically evaluated to minimize sources of 5) High income level which means more trip production uncertainty in the developed models. This is obtained by rates. estimating both the probability significant value (P-value) and 2 6) The higher economic activity land use in El Raml zone linear coefficient of determination (R ) between individual (About 11% urban land). variables and Q and Z as dependent variables and every socio- economic variable as explanatory variables. The explanatory For more clarification, El Raml zone locates in Sidi variable is considered significant if it has P-value less than or Gaber district which holds main train station in the city equal to the significant level of 0.05 and have high linear represents the port to travel to other cities from Alexandria coefficient of determination with comparison to other city. Big number of faculties of University of Alexandria is variables. This means that changes in the socio-economic located in Sidi Gaber district. This represents attractiveness for variable has significant effect on changing the dependent faculty students from high income level in El Montana zone. variable (Q or Z). On the other hand, it is interesting to shed light upon the As shown in Table 2, population number (X1), highest values of total trip production (Q) and trip attraction employment number (X2), and percentage illiterates of (Z) in the city O/D matrix. El Raml zone recorded the first population (X3) have been found to obtain the highest linear coefficient of determination (R2) with the number of trip rank in total trip production and inter-onal trips with 882402 2 and 370739 trip/day respectively. This coincides with the big production of TAZs. They have R of 0.31, 0.31, and 0.40 number of population in the zone which is an incentive for trip respectively. So, the significance level of each have been production. Also, the zone holds the second biggest number of checked, and have been found significant variables in the trip employees among all zones. This brings forward more daily production in TAZs as they have P-values of 0.047, 0.044, and home-based work trips. Besides, the high value of land in this 0.020 respectively. For trip attraction, the socio-economic zone is amenable for more flee to zones with lower value of variables that have the highest linear coefficient of land for work. This is also clear from the land use purpose determination (R2) with the number of trip attracted to TAZs distribution of El Raml zone. In which, about 82% are for are the employment number (X2), percentage illiterates of residential purpose and only 13% for educational and population (X3) in addition to percentage of population with economical activities which advocate more trips towards other age between 25-35 years old (X4), and percentage of land zones for economic and educational purposes. El Amria zone used for educational purpose (X5). Consequently, the lies in the last rank regarding total trip production and inter- significance level have been checked for those variables. zonal trips with only 4035 and 2250 trip/day respectively. Results indicated significant assurance as they have significant P-values of 0.050, 0.002, 0.050, and 0.042 respectively. Regarding the trip attraction, Bab Sahrq zone occupies the first rank among all zones with attracting 681313 trip/day. Regression work has been operated on the significant This is ascribed to the low value of land and buildings in this variables and number of trips produced and attracted to zone which is suitable for commercial and economical individual transportation zones. The results are two multiple activities. Latter reason is drawn from the land uses in this regression models for both Q and Z as expressed in the zones which have about 6.5% of land is for entertainment land following equations: use. This is the second highest percentage of land use for entertainment purpose among all zones of the city. El Amria (R2= 0.50) (1) also is recorded in the last rank of trips attracted with only 44593 trip/day. (R2= 0.71) (2) With concern to trip characteristics, statistics indicates that 45% of total trip number is a return home trip. While here: about 23% and 16% of the trips are for the purpose of going to Qi : is the number of trips produced from the TAZ I (trip/day), work and going to school. This falls in line with the small student to population ratio in the city which is 21%. Zi : is the number of trips attracted to the TAZ I (trip/day), Recreational and private affairs trips represent only 16% of all X1i : is the population number in TAZ i, trip purposes. The reason refers to overall low income level in the city and also weakness of public transport system. X2i : is the employment number in TAZ i, 6. Trip generation model for Alexandria X3i : is the percentage illiterates of population in TAZ i, city X4i : is the percentage of population with age between 25-35 years old in TAZ i, and To developed trip generation models: trip production and attraction models for the study area thirteen TAZs, zonal data X5i : is the percentage of land used for Educational purpose in has been involved in (MLR) technique. The socio-economic TAZ i. phenomena of different TAZ have been correlated to total number of trips (Q and Z) of zones. Initially, to investigate The analysis of the proposed trip generation models introduces the following facts:

ISBN: 978-1-61804-358-0 157 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering

1) The model coefficients of the socio-economic variables has inferior effect on trip attraction since it has the have signs match with the individual correlation smallest model coefficient among all descriptive variable For trip production model (Q model) in trip attraction model.

TABLE 2. SIGNIFICANT SOCIO-ECONOMIC VARIABLES FOR TRIP PRODUCTION Indication linear coefficient of Individual correlation (Q) AND TRIP ATTRACTION (Z) IN ALEXANDRIA CITY of the determination (R2) coefficient between ) P-value variable in between individual between individual the model variables and Q variables and Q 7. Statistical assessment of developed trip generation model X1 0.047 0.31 0.56 In this step, statistical indicators have been used to assess X2 0.044 0.31 0.56 and verify the performance of the developed trip generation models for Alexandria city. This is to ensure the significance X3 0.020 0.40 -0.63 and agreeability of output values of the developed trip generation models with the dataset on which the modeling For trip Attraction model (Z model) process have been based. The goodness of fit for each model is examined based on the values of the O-D matrix balance error, Indication linear coefficient of Individual correlation correlation coefficient of determination (R2) between modeled of the determination (R2) coefficient between ) P-value and actual base year trip production and attraction values, variable in between individual between individual difference between average monitored and actual average of the model variables and Z variables and Z trip production and attraction values at the base year, X4 0.050 0.26 -0.61 Normalized Mean Square Error (NMSE), Frictional Biases (FB), and Geometrical Mean (MG), and Coincidence Ratio X2 0.050 0.27 0.52 (CR). Calculated Values of the statistical indicators for both models are illustrated in Table 3. Analysis of results indicates X3 0.002 0.56 -0.75 the followings: 1) The O-D matrix balance error (which is the percentage X5 0.042 032 0.57 difference between the sum of total number of trips produced and the sum of total number of trips attracted of all TAZs) indicates the quality of Q and Z models accompanied which forms the base for the trip coefficient of the variable in Table 8 which also match the distribution step of the 4 steps transportation planning engineering judgment. This means that the effect of the process. The ideal situation is when the sum of trip explanatory variable in the model is the same effect of the generated and the sum of trips attracted in the O-D matrix individual relation between the explanatory variable and is equalized. i.e. O-D balance error is zero and no the dependent variable (Q or Z). For example, the model calibration is needed. For the developed Q and Z models coefficients of percentage illiterates of population in TAZ for Alexandria city, the balance error in is only 5.8%. have negative signs in both Q and Z models (-44430.9 2) Percentage relative average error (Percentage difference and -16333.1 respectively). This is at the nexus with the between average actual trip numbers and average negative sign of individual correlation coefficient between modeled trip numbers) is relatively small for both Q the percentage illiterates of population with Q and Z (- model and Z model representing percentages of -0.016% 0.63 and -0.75 respectively). and 5.972% for both models respectively. Such values of 2) The percentage illiterate of population (X3i) has high errors may be neglected as we deal with numbers of trip effect on trip production (Q) since it has the highest thousands trips produced and attracted to transportation absolute model coefficients value (44430.9). The negative zones per day, sign of the coefficient illustrates reduction in trip 3) The NMSE which reflects the overall deviations between production of the TAZ with the increase of percentage modeled and actual trip numbers for both models illiterate of population in the TAZ. The variable that has investigated equals 0.39 and 0.11 for Q and Z models the smallest effect of trip production number is the respectively. Therefore, the performance of the model is population number (X1i) of TAZ which has a model considered acceptable and correctly describes the coefficient of only 0.217365. processes since NMSE is less than 0.5 [13], [14], 3) The percentage of population with age between 25-35 4) FB value for trip production and trip attraction model are years old (X4i) has the highest effect on trip attraction of 0.00016 and -0.06 respectively. Such values are indicating TAZ. It has the biggest absolute model coefficients value small overall overestimation of trip numbers for Q model of (90650.6). The negative sign of the model coefficient and small overall underestimation of trip numbers for Z indicates in trip attraction to the TAZ with the increase of model. Nevertheless, for both models, the FB values are percentage of population with age between 25-35 years acceptable since FB values lays between -0.7 and 0.7 old in the zone. The employment number in TAZ (X2i)

ISBN: 978-1-61804-358-0 158 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering

[14], variables. Regression work has been operated on the 5) MG values for Q and Z models respectively are 0.73 and significant variables and number of trips produced and 0.85 respectively. These values deviate from the ideal attracted to individual transportation zones. The results are value of MG (1.00) [15], [16] with only 0.27 and 0.15 for two multiple regression models for both Q and Z. statistical both models respectively. Such figures of MG indicate indicators have been used to assess and verify the performance small systematic errors and minute relative biases for of the developed trip generation models for Alexandria city. predicted production and attraction TAZ’s trip numbers The O-D matrix balance error is only 5.8%. Percentage with comparison to actual trip numbers, relative average error is relatively small for both Q model and Z model representing percentages of -0.016% and 5.972% for both models respectively. The NMSE equals 0.39 and 0.11 for Q and Z models respectively. FB value for trip production and trip attraction model are 0.00016 and -0.06 respectively. Trip production Trip Attraction Statistical indicators model model Acceptable CR values of 0.55 for Q model and higher value of (Q) (Z) 0.72 for Z model. Therefore, the performance of the model is considered acceptable. This model helps mainly in the urban Mean error -53.8 (trip/day) 19490.3 (trip/day) transportation planning process of the city.

% Relative average error -0.016 5.972 ACKNOWLEDGMENT FB 0.00016 -0.06 NMSE 0.39 0.11 The first author would like to thank Egyptian Ministry of 0.73 0.85 Higher Education (MoHE) for providing him the financial MG support (PhD scholarship) for this research, as well as Egypt CR 0.55 0.70 Japan University of Science and Technology (E-JUST) for (R2) between actual and offering the facility and tools needed to conduct this work. 0.57 0.72 modeled trip numbers REFERENCES [1] A. . Atoyebi, T. . Gbadamosi, I. I. . Nwokoro, and O-D matrix balance error 5.8% F. . Omole, “Analysis of Intra- City Public Transport System of Ojuelegba Park, Lagos State, Nigeria,” Mediterr. J. Soc. Sci., vol. 6, no. 2, pp. TABLE 3. STATISTICAL INDICATORS OF THE DEVELOPED TRIP GENERATION 624–635, 2015. MODEL [2] T. F. Golob, “A simultaneous model of household activity participation and trip chain generation,” 6) CR compares the frequency distributions of estimated and Transp. Res. Part B Methodol., vol. 34, no. 5, pp. observed trip numbers. The ratio measures the analogous 355–376, 2000. pattern between the two distribution curves by estimating [3] A. a. Amavi, J. P. Romero, A. Dominguez, L. percent of area that coincides [17]. CR lies between 0 and dell’Olio, and A. Ibeas, “Advanced Trip 1.0, where a ratio of 1.0 indicates identical distributions. Generation/Attraction Models,” Procedia - Soc. For Alexandria city, developed trip generation models Behav. Sci., vol. 160, no. Cit, pp. 430–439, 2014. introduced acceptable CR values of 0.55 for Q model and [4] S. Goel, “Artificial Neural Network Based Model higher value of 0.72 for Z model, for Traffic Production and Attraction : A Case 7) The relation between monitored and modeled trip generation numbers has a correlation coefficient of Study of All the Zones of Delhi Urban Area,” pp. determination R2 = 0.57 and 0.72 for both Q and Z 202–208, 2014. models respectively. [5] L. Wang, J. Tang, X. Fei, and M. Gong, “A mixed integer programming formulation and solution for traffic analysis zone delineation considering zone 8. Conclusion amount decision,” Inf. Sci. (Ny)., vol. 280, no. May, A trip generation model describes the daily trip production and attraction (Q and Z consequently) interchange pp. 322–337, 2014. between different TAZs in Alexandria city - Egypt has been [6] M. M. Abdo, H. a Ayad, and D. Taha, “% reviewed produced. Based on socio-economic, demographic, travel paper The ‘Open Cities’ Approach: a Prospect for demand data in year 2006, after analysis of collected dated, Improving the Quality of Life in Alexandria City, this model related the trip generation behavior in the city to Egypt Mai M.Abdo, Hany A.Ayad, Dina Taha,” significant parameters. The significance level has been vol. 0, no. May, pp. 899–909, 2012. statistically determined based on the probability significant [7] M. M. M. Abdel-Aal, “Calibrating a trip value (P-value) and linear coefficient of determination (R2) distribution gravity model stratified by the trip between individual variables and Q and Z as dependent variables and every socio-economic variable as explanatory

ISBN: 978-1-61804-358-0 159 Fluids, Heat and Mass Transfer, Mechanical and Civil Engineering

purposes for the city of Alexandria,” Alexandria Eng. J., vol. 53, no. 3, pp. 677–689, 2014. [8] Central Agency for Public Mobilization Statistics CAPMAS, “Yearly Statistics Report,” 2006. [9] P. G. O. F. P. (GOPP), “The General Plan for the City of Alexandria, Cairo, Egypt,” 2006. [10] Central Agency for Public Mobilization Statistics CAPMAS, “Yearly Statistical Book,” 2012. [11] M. of Housing, “National Urban Observatory,” 2010. [12] R. Cervero and E. E. Guerra, “Urban Densities and Transit : A Multi-dimensional Perspective,” no. September, p. 15, 2011. [13] G. Raducan and I. Stefanescu, A Qualitative Study of Air Pollutants from Road Traffic. 2012. [14] D. Bhawna, A. Pal, and G. Singh, “Assessment of Vehicular Pollution In Dhanbad City Using Caline 4 Model,” Int. J. Geol. Earth …, 2013. [15] A. Elkafoury, A. M. Negm, M. H. Aly, M. F. Bady, and T. Ichimura, “Develop dynamic model for predicting traffic CO emissions in urban areas,” Environ. Sci. Pollut. Res., 2015. [16] A. Elkafoury, A. M. Negm, M. F. Bady, and M. H. Aly, “Modeling Vehicular CO Emissions for Time Headway-based Environmental Traffic Management System,” Procedia Technol., vol. 19, pp. 341–348, 2015. [17] J. S. Chang, D. Jung, J. Kim, and T. Kang, “Comparative analysis of trip generation models: results using home-based work trips in the Seoul metropolitan area,” Transp. Lett., vol. 6, no. 2, pp. 78–88, 2014.

ISBN: 978-1-61804-358-0 160