VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY CHU ANH TUAN ASSOCIATION OF BUILT ENVIRONMENT WITH WALKING DISTANCE TO PUBLIC TRANSIT STOPS IN HANOI MASTER'S THESIS MASTER OF INFRASTRUCTURE ENGINEERING Hanoi, 2019 VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY CHU ANH TUAN ASSOCIATION OF BUILT ENVIRONMENT WITH WALKING DISTANCE TO PUBLIC TRANSIT STOPS IN HANOI MAJOR: INFRASTRUCTURE ENGINEERING CODE: PILOT RESEARCH SUPERVISOR: ANNEX LIST OFHIRONORI FORMS FOR MANAGEMENT Prof KATO Dr PHAN LE BINH Hanoi, 2019 ACKNOWLEDGMENT This research would not have been possible without the support, contribution and collaboration of others First of all, I would like to convey my greatest appreciation and deepest attitude to my supervisors, Prof Hironori Kato and Dr Phan Le Binh for their support and constant supervision which contributed immensely to my personal development for his precious advice and helpful guidance in research work Without their patience and continuous support, I cannot fulfil my research I sincerely thank to Prof Nguyen Dinh Duc - the Program Director of Infrastructure Engineering Program of Vietnam- Japan University (VJU) who always has encouraged and deeply care about me In addition, I sincerely thank to all members in MIE’s office Specially, I would like to give my greatest thanks to Dr Nguyen Tien Dung and Mr Bui Hoang Tan who always give me strong support and insightful advice My deep thank to Mrs Nguyen Thi Mai Chi about her precious support for my data collection Furthermore, I sincerely thank to the rest of the teachers and staffs of Vietnam Japan University for their support and guidance which has inspired me and helped me to overcome the challenges I faced during the period of study at Vietnam Japan University To all of you, I extend my deepest gratitude Finally, I would like to send my deepest love and gratitude to my family, who always love, support and encourage me every time Sincerely, Chu Anh Tuan i ABTRACT Similar to many other developing cities, Hanoi, the capital city of Vietnam, has also faced many serious problems caused by spontaneous urban development and massive private vehicles As a part of solutions, public transportation systems in Hanoi were paid attention to be invested and developed However, Public transportation meets only partially the travelling demand of urban people Even recent years, the productivity of buses in Hanoi tends to be restrain and even going down in some years Therefore, how to encourage and attract people to use public transportation modes is a more and more urgent topic This research focuses on a key factor which greatly influences the use of transit services This is Walking distance to transit stop and impacts of built environment on this walking distance of riders A Poison Regression model is estimated to analyze the associations of built environment and walking distance to public transit stop using a dataset collected from a questionnaire-based Onboard survey in May 2019 with the geospatial data of BE variables where the dataset contains 609 respondents of the Hanoi Metropolitan Area The results unveiled that: (1) Walking is the majority mode of both bus trips from home to transit stop and from transit stop to final destination; (2) The assumptions about walking distance to public stops (threshold of 400 meters) that planners have given are consistent with the Hanoi context; (3) BE variables may have both positive/ negative impacts on walking distance to public transit stops Finally, some policy recommendations were produced to support for the use of the public transportation modes in Hanoi Keywords: Walking; Walking distance; Built environment; Transit stop ii TABLE OF CONTENTS ACKNOWLEDGMENT i TABLE OF CONTENTS ii LIST OF FIGURES v LIST OF TABLES vi LIST OF ABBREVIATIONS vii CHAPTER INTRODUCTION .1 CHAPTER LITERATURE REVIEW 2.1 The relationship between walking and BE .6 2.2 Distance walking and walking to public transit 2.3 Studies on walking distance and built environment in the world and Vietnam .10 CHAPTER DATA 13 3.1 Survey Questionnaire 13 3.1.1 Survey area .13 3.1.2 Survey implemention 15 3.2 GIS-based database 20 3.3 Measurement of walking distance to public transit 20 3.4 Measurement of BE variable 22 CHAPTER WALKING DISTANCE MODEL DEVELOPMENT 27 4.1 Overview 27 4.2 Explanatory variables .27 4.3 Methodology 33 CHAPTER ESTIMATION RESULTS 35 5.1 Estimation results of access trip .35 5.2 Estimation results of egress trip 40 CHAPTER DISCUSSION AND CONCLUSION .41 6.1 Walking distance to public transit 41 6.2 Association between BE and walking distance 42 6.3 Limitations 43 iii REFERENCES 45 APPENDIX .48 A set of survey questionnaire in English .48 A set of survey questionnaire in Vietnamese 55 Correlation between potential explanatory variables 62 iv LIST OF FIGURES Page Figure 1.1: Bus passenger ridership in Hanoi Figure 1.2: Flow of Research .5 Figure 3.1: Survey bus route in Hanoi .14 Figure 3.2: A group of the survey and an interview on a bus route 16 Figure 3.3: An illustration in the survey questionnaire 16 Figure 3.4: Locations of respondents .21 Figure 3.5: Population density by ward 23 Figure 3.6: Job density by ward .24 Figure 3.7: Current bus network and bus stops distribution 26 v LIST OF TABLES Page Table 2.1: Access modes from home to bus stops in Sydney Table 3.1: The descriptive statistics of attributes of respondents (N=609) .18 Table 4.1: Potential explanatory variables for walking distance model 28 Table 4.2: Descriptive statistics of variables for access trip (N=290) .31 Table 4.3: Descriptive statistics of variables for egress trip (N=299) .32 Table 5.1: Estimation result of Poisson model for walking distance of access trip 38 Table 5.2: Estimation result of Poisson model for walking distance of egress trip 39 Table 6.1: Access modes from home to bus stops and from final stops to destinations in Hanoi 41 Table 6.2: Statistics on walking distances for access trip and egress trip 42 vi LIST OF ABBREVIATIONS BE Built Environment BRT Bus Rapid Transit GIS Geographic Information System TRAMOC Hanoi urban transport management and operation center TOD Transit-oriented development vii CHAPTER INTRODUCTION 1.1 Introduction Over the years, Hanoi has witnessed a rapid development of the urbanization that leads to the increasing demand in travelling, thus to the rapid increase of the transportation means, in particular private vehicles In December 2015, it was reported that the total of private vehicles in Hanoi was 5.8 million units including 376,417 cars and 5.4 million motorbikes (Ngoc, 2016), with the exception of the large number of vehicles from other provinces going in and out the city during the day Such a massive private vehicles population has caused various transportation issues such as road traffic accidents, traffic jam, and air pollution To deal with those problems, Public transportation systems in Hanoi were paid attention to be invested and developed, focusing on buses (only one bus rapid transit (BRT) route is operating and urban railway are under construction in Hanoi) However, public transportation meets only partially the travelling demand of urban people, specifically, public transportation system transports only less than 10 percent demand in Hanoi city (World Bank, 2018) Even recent years, the productivity of buses in Hanoi tends to be restrain and even going down in some years (reduced 0,35 percent in 2015 compared to that of 2014) (Figure 1.1) In particular, the progress of construction and operation for the Mass Rapid Transit system (BRT, urban railway) in Hanoi missed the deadline Therefore, how to encourage and attract people to use public transportation modes is a more and more urgent topic There are various factors that influence the use of public transportation modes, including cost, level of service of the existing system, physical accessibility, spatial access, etc all of which contribute to each person’s motivation and ability to decide to use public transportation This research focuses on walking distance to transit stop because understanding influences on walking distance to transit stops of riders is an important indicator of a transit system’s ability to attract people The public transportation services are widely used when more and more people live and/or work 56 57 58 59 60 61 Correlation between potential explanatory variables Correlations of buffer 100 - Access trip Senior_p Young_p eople eople Senior_people Young_people M ale Low_income M id_income High_income Car_driver_lisence M ain_tr Number Number Number Conflict M otorcy Bus_freq Entropy Step_up Walking Populati Private_ ansporta Car_driv _of_publ _of_inter _of_bus Job_Den _with_ot Cleanline Level_ro cross the Total_bu cle Low_inc M id_inc High_inc uency_1 _Index_1 Drainage _and_do _ameniti on_Dens vehicles_ tion_mo er_lisenc ic_faciliti section_ _stop_1 sity_100 street ad ss her_mod ses _driver_l ome ome ome 00 00 ity _100 es wn available de_M ot e 100 es_100 00 e isence orbike M ale -.588 ** -.588 -.031 -.008 -.008 -.181** 058 207** 065 -.007 -.167** 062 014 017 -.031 -.077 022 -.088 013 037 026 018 029 125* 137* ** ** ** ** -.098 ** -.097 -.172** -.011 -.046 -.031 -.054 -.057 * -.013 -.010 026 012 077 -.014 -.029 -.074 ** * ** 279 ** 191 -.053 110 -.049 -.087 -.134 007 -.051 * -.022 014 * -.028 044 082 -.184 -.021 -.143* 045 -.103 -.149* -.146* -.060 -.215** -.067 -.045 -.085 -.005 -.027 106 126 044 039 456 ** -.116 -.106 026 035 083 052 -.105 -.078 ** ** ** -.004 -.060 -.030 052 121* 008 ** -.181** 058 207** 065 ** -.342 -.342 115 -.203 -.016 -.261 -.816 ** ** 115 -.816 -.338** -.186** 063 1 456 -.103 -.203** -.016 -.338** ** * ** -.268** 063 141 -.186 ** -.268 ** 208 -.016 -.007 -.261 -.098 279** -.149* 162** M ain_transportation_mode_M otorbike Total_buses -.167** 062 -.156** -.097 191** -.053 -.146* -.060 210** -.009 -.100 Private_vehicles_available -.172** -.046 -.011 110 -.054 -.049 -.215** -.067 158** 084 014 -.057 -.087 -.045 017 M otorcycle _driver_lisence Conflict_with_other_mode Cleanliness Level_road 208** 084 050 060 073 -.025 055 -.060 020 113 158 101 121* -.057 -.026 -.007 045 057 049 -.044 -.078 -.106 -.109 -.051 -.041 -.037 129* -.034 ** 263 -.027 083 -.080 -.007 025 004 011 -.018 051 -.020 071 096 000 025 093 262** -.037 137* 035 -.103 -.043 -.058 057 -.052 053 073 028 -.054 -.010 -.043 021 120* -.053 031 042 -.029 -.017 047 000 092 ** 315 ** 184 -.014 ** 210 044 178** -.004 116* 060 -.043 181** 089 -.152** 049 -.012 -.087 -.115 -.089 -.027 -.004 020 195** 161** 081 174** 095 137* -.002 046 -.098 -.066 065 -.123* 029 -.068 027 167** 374** 277** 150* 051 065 -.112 030 -.039 -.026 004 299** 261** 031 -.078 028 -.004 -.015 269** 262** 034 269** 081 162 -.016 210 -.100 -.009 ** 246 246** 113 263** -.027 262** -.037 101 083 -.080 181** 021 089 -.026 137* 035 315** 195** 050 -.007 -.007 -.103 120* 049 184** -.014 161** 081 401 ** 401 ** 167** 313** 313** -.053 210** 044 174** 095 374** 299** 196** 196** 277** 261** 150* 262** 081 269** 034 375** 040 * ** 007 -.085 060 045 025 -.106 073 057 004 -.152** -.043 -.013 -.116* 026 -.005 -.025 049 011 -.058 031 cross the street -.031 -.134* -.051 Drainage -.077 Step_up_and_down 141 -.156 022 -.010 -.022 -.027 055 -.044 -.018 057 026 014 106 -.060 -.078 051 -.052 178** 042 -.004 -.088 -.012 137* -.002 Population_Density _100 013 012 044 020 -.106 -.020 053 -.029 -.087 046 Job_Density_100 037 077 126* 039 -.109 071 073 -.017 -.115 -.098 026 -.014 -.028 121* 035 -.057 Entropy_Index_100 -.004 -.051 096 028 047 -.089 -.066 Number_of_bus_stop_100 018 -.029 044 083 -.060 -.041 000 -.054 000 -.027 065 030 -.163 028 Bus_frequency_100 029 -.074 082 052 -.030 -.037 025 -.010 092 029 -.039 -.004 125* -.184** -.021 -.105 -.034 093 -.068 -.026 * 045 -.078 046 * 116* 008 060 * 129* 052 -.123* -.004 -.007 020 027 004 -.054 -.079 026 090 -.100 -.129* -.059 -.095 -.157** Walking_amenities Number_of_public_facilities_1 00 Number_of_intersection_100 Walking_distance_for_access_tr ip_meter 137 -.034 -.143 073 121 -.114 ** 121* 010 -.046 078 040 260** -.052 -.031 -.083 135* 096 -.144* 009 066 -.018 035 290** 067 -.041 -.034 -.050 -.074 -.004 -.102 -.087 134* 134* -.088 007 061 047 073 -.086 004 ** 067 -.042 -.006 023 033 030 -.069 009 146* 042 072 235** -.100 332** 091 159** 210** 175** ** ** ** 178** 375** 121 010 260 -.052 290 -.041 -.088 -.042 065 -.078 -.046 -.031 -.034 007 -.006 219** 219** -.112 ** 074 -.083 -.050 061 023 * * 135 078 096 -.074 047 033 146 042 ** 332 091 066 -.004 073 030 072 -.144* -.015 009 -.018 -.102 -.086 -.069 043 035 -.087 004 009 -.096 -.084 -.130* -.100 -.038 -.134* ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 62 -.007 -.163** 074 031 269 051 046 244 ** 272 020 011 175 043 177** 004 ** 159** 175** 235** -.100 210** 272** 760 ** 020 011 ** 175 ** 178 ** 177 004 ** 245 245** -.188** -.155** -.230** -.242** -.217** -.151** -.117* 244 760 Correlations of buffer 200 - Access trip Senior Young _peopl _peopl e e Male Senior_people Young_people Male Low_income Mid_income High_income -.588 ** -.588 -.008 -.031 ** ** ** ** ** -.181 456 058 -.342** Motor cycle Car_dri _driver Low_i Mid_in High_i ver_lis _lisenc ncome come ncome ence e -.008 -.181** 058 207** 065 -.007 ** -.031 456 -.342** -.203** -.261** -.098 -.103 115 -.016 141* 279** -.103 -.816 ** -.338** -.186** -.149* ** 115 -.816 -.268** 063 162** ** ** ** Main_t Numbe ranspo Private Conflic Popula Numbe r_of_p Numbe rtation _vehicl t_with Step_u Walkin tion_D Job_D Entrop r_of_b Bus_fr ublic_f r_of_in _mode Total_ es_ava _other Cleanli Level_ Draina p_and g_ame ensity ensity y_Inde us_sto equenc acilitie tersecti _Moto buses ilable _mode ness road Across ge _down nities _200 _200 x_200 p_200 y_200 s_200 on_200 -.167** ** -.156 191** * -.146 210** -.016 -.100 062 -.172** -.097 -.011 -.046 -.053 Drainage Step_up_and_down Walking_amenities -.077 -.013 026 -.005 -.025 049 011 022 -.010 -.022 -.027 055 -.044 -.018 -.058 031 057 178** -.052 042 -.060 -.078 051 Population_Density _200 000 014 030 040 -.116* -.014 074 -.024 Job_Density_200 045 080 140* 064 114 -.039 069 090 Entropy_Index_200 -.022 050 -.019 069 -.012 -.127* -.097 089 -.013 -.022 -.156** 006 -.170** Number_of_bus_stop_200 -.002 022 060 052 -.086 054 057 011 Bus_frequency_200 -.013 -.014 086 024 -.004 -.035 096 110 * ** 017 -.034 068 -.054 086 072 148 -.152 111 -.100 012 -.028 039 ** -.016 156 059 -.012 -.089 -.070 145* -.192** 034 -.047 -.021 -.088 000 045 -.022 -.002 -.054 -.057 -.051 -.013 -.010 026 014 080 050 022 110 -.049 -.087 -.134 007 -.022 014 -.019 060 -.045 -.085 -.005 -.027 106 140* 030 064 -.067 -.116* -.106 026 ** 114 069 052 024 084 050 060 073 -.025 055 -.060 040 -.039 -.012 -.086 -.004 068 039 101 -.026 -.007 045 057 049 -.044 -.078 054 -.035 -.054 -.016 -.080 -.007 025 004 011 -.018 051 -.127* 069 -.097 083 -.116* -.014 089 057 096 ** -.043 -.058 * 035 -.103 -.152 137 021 120* 049 181** 089 315** 184** -.014 195** 161** 081 ** 401 ** 167** 195 313** 161** 401 ** 299** 106 Number_of_public_facilities _200 Number_of_intersection_20 022 174** 374** 044 095 277** -.004 137* 150* 014 036 -.077 313** 026 -.001 -.100 -.031 * 081 167** -.088 111 -.014 -.152** 086 017 017 -.060 -.215 -.009 158** -.016 -.338 -.268 208 113 207 -.203 Car_driver_lisence 065 -.261** 141* -.186** 063 208** 246** 263** -.027 Motorcycle _driver_lisence -.007 -.098 279** -.149* 162** -.016 246** 262** -.037 Main_transportation_mode_ -.167** -.156** 191** -.146* 210** -.100 263** 262** -.043 Motorbike Total_buses 062 -.097 -.053 -.060 -.009 113 -.027 -.037 -.043 Private_vehicles_available -.011 110 -.215** 158** 101 083 137* 181** 089 -.172** Conflict_with_other_mode -.046 -.054 -.049 -.067 084 -.026 -.080 035 021 315** Cleanliness 014 -.057 -.087 -.045 050 -.007 -.007 -.103 120* 184** * Level_road 017 -.134 007 -.085 060 045 025 -.152** 049 -.014 * Across -.031 -.051 -.116 -.106 073 057 004 -.043 -.053 210** 148* 014 ** -.002 269 046 062 261** 262** 081 016 074 090 -.013 011 110 042 -.024 -.022 006 036 145* 034 -.021 210** -.012 -.047 -.001 174** 095 137* -.002 -.070 -.192** 040 128* -.078 -.037 374** 277** 150* 062 035 -.055 005 -.036 -.005 -.043 299** 261** 262** 034 269** 081 016 -.094 -.045 -.008 -.011 -.085 -.026 121* 001 -.054 077 -.003 021 052 051 040 260** -.041 -.062 -.023 038 -.015 -.019 053 134* 290** 067 -.036 -.038 006 -.051 -.011 -.088 -.087 -.078 005 030 -.003 099 007 -.043 -.007 032 -.013 -.001 -.128* -.035 196** 269** ** 375** 196 ** ** 269 375 034 040 134* * ** ** 121 260 290 001 -.041 -.036 067 -.078 -.043 035 -.094 -.054 -.062 -.038 -.045 077 -.023 006 030 128* 040 005 -.008 -.003 038 -.051 -.003 -.036 -.011 021 -.015 -.011 099 -.078 -.005 -.085 052 -.019 -.088 -.128* 007 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 63 -.026 051 086 156** 072 059 -.052 -.055 -.043 012 -.028 057 -.006 -.037 -.034 031 178** 044 -.004 -.053 -.103 -.013 053 -.087 005 -.089 -.156** -.170** 046 -.103 -.006 022 229** 178** 101 103 240** -.090 ** ** ** -.007 229 405 230 225** 329** 289** ** ** ** 032 178 405 250 283** 290** 194** ** ** -.013 101 230 626 ** 057 204** 250 ** ** ** -.001 103 225 076 030 283 626 -.035 240** 329** 022 -.090 289** 290** 057 ** ** 194 204 352** 030 352 076 ** Senior_ Young_ people people Senior_people Young_people Male Low_income Mid_income High_income -.588 ** ** -.588 -.008 Motorcycle _driver_lisence 207** -.203** 065 -.261** -.007 -.098 Main_transportation_mode_ Motorbike Total_buses -.167** -.156** 062 -.097 Private_vehicles_available -.172** -.046 Cleanliness Level_road Car_driver_lisence Conflict_with_other_mode Male -.008 -.181** -.031 456 ** -.031 -.181** 456 ** 058 -.342** Motorc ycle Car_dri _driver Low_in Mid_in High_in ver_lise _lisenc come come come nce e -.103 058 207** 065 ** ** ** -.342 -.203 -.261 115 -.016 141* -.816 ** -.338** -.186** 115 -.816 ** -.268** 063 -.016 -.338** -.268** 208** 063 208** 141* -.186** -.103 ** * ** ** 062 -.172** -.097 014 -.046 104 -.057 -.049 -.087 -.134 007 009 084 050 060 073 -.025 055 -.060 060 005 004 030 045 027 057 -.026 -.007 045 057 049 -.044 -.078 -.065 -.086 -.058 -.035 -.007 025 004 011 -.018 051 -.129* 097 -.069 -.080 -.119* 007 065 081 110 077 -.103 -.152** 049 120* -.043 -.058 057 -.052 079 107 017 107 ** 100 151** 075 -.053 031 042 003 017 010 014 131* 004 -.034 -.012 -.149* -.304** 052 004 -.087 -.082 -.111 -.064 148 021 -.043 156** 069 069 156** 021 069 315** 199** 120* 049 184** -.014 137* 068 -.053 210** 044 148* -.054 104 -.198** -.049 -.067 125* 084 127* -.026 -.080 148* 035 014 -.057 -.087 -.045 050 -.007 -.007 -.103 017 * 007 -.085 060 045 -.106 073 057 025 -.152** 004 -.043 -.005 -.025 049 011 -.078 Population_Density _500 -.019 027 013 060 062 053 143* 107 073 005 -.035 008 210** -.100 -.043 -.044 -.115* -.023 -.090 -.208 063 142* 162** -.016 055 ** 177 009 262** -.037 -.060 -.040 012 037 263** -.027 106 083 073 246 -.027 053 * 143 013 -.100 014 027 014 106 210** -.009 -.022 026 -.022 -.027 162 026 -.010 026 192** ** -.005 -.146* -.060 -.010 -.013 * 232** -.116 -.106 -.149 022 -.051 048 -.085 191** -.053 -.088 064 -.045 035 Walking_amenities -.020 -.067 * Step_up_and_down 062 -.060 -.198** -.009 125* -.037 -.013 -.019 -.146* -.027 -.077 -.088 191 ** Drainage 022 -.149* 263** -.116* 026 -.077 279 246** 113 -.031 107 ** -.134 -.051 262 113 315** 184** -.014 210** 044 199** 137* 068 148* 117* 117* 051 167** 374** 277** 150* 005 -.009 076 -.029 -.023 -.057 299** 261** -.100 -.050 006 -.002 -.083 -.068 167 ** 313 ** ** 262** 034 015 ** 313** 269** 081 068 401 ** 401 ** * 121 019 -.048 024 -.033 051 015 -.025 374** 299** 196** 040 260** -.022 -.089 002 -.001 -.015 -.075 -.028 117* 277** 261** 134* 290** 067 -.046 021 013 -.003 -.072 262** 081 375** 040 -.045 150* 269** 034 -.070 -.119* -.029 * ** 196 269 375** 031 -.018 057 -.052 178** 042 -.004 051 -.012 117* 051 -.119* 007 079 003 -.101 032 269 068 097 107 -.078 005 -.015 -.009 -.050 024 002 021 * 052 076 006 -.033 -.001 013 ** 131 -.304 004 -.087 004 -.029 -.002 051 -.015 -.111 -.023 -.083 015 -.034 -.064 -.057 -.068 -.025 -.020 083 012 037 004 065 017 017 -.172** 010 -.230** Number_of_bus_stop_500 064 -.040 ** 009 030 -.065 081 107 014 Bus_frequency_500 048 -.090 * 045 -.086 110 ** -.208** 009 027 -.058 077 156 100 * 232** 142 063 008 192** -.115* -.023 -.035 057 -.035 151** 075 -.149 -.082 156 178** -.004 -.058 -.129* -.069 Number_of_public_facilities _500 Number_of_intersection_50 -.054 * -.053 279 177 017 ** -.031 Entropy_Index_500 014 127* 069 Across Job_Density_500 -.007 -.167** -.098 -.156** -.016 014 Correlations of buffer 500 - Access trip Main_tr Number ansport Private Conflict Populat Number _of_pu Number ation_m _vehicl _with_ Step_u Walkin ion_De Job_De Entropy _of_bu Bus_fre blic_fac _of_int ode_M Total_b es_avai other_ Cleanlin Level_r Drainag p_and_ g_amen nsity nsity_5 _Index_ s_stop quency ilities_5 ersectio otorbik uses lable mode ess oad Across e down ities _500 00 500 _500 _500 00 n_500 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 64 ** 134* -.101 -.172** -.230** 032 -.078 -.015 -.048 002 027 032 053 260 -.022 290** -.045 067 -.036 -.016 027 053 -.005 -.068 000 015 121 019 -.048 -.036 244** 265** 237** 301** -.074 -.100 -.048 -.089 -.046 002 -.016 296** 296** 394** 469 ** 398** 027 027 500 ** 500 ** 492 ** ** ** 491 ** ** 136* 032 053 492 ** ** 604 ** ** 479 ** -.003 053 -.005 237 394 491 ** ** -.075 -.072 -.070 -.068 469 ** 204** 454 ** -.028 -.119* -.029 000 301** -.074 398** 136* 479 ** 244 ** 265 ** ** 422 422 604 204 454 ** 208** 333** 208** 595 ** 595 ** 333 Correlations of buffer 1000 - Access trip Senior_ Young_ people people Senior_people Young_people Main_tr Number Motorc Private_ Conflict Populati Number Number Car_dri ansport cross Step_u Walkin Job_De Entropy Bus_fre _of_pu Low_in Mid_in High_in ycle Total_b vehicles _with_o Cleanlin Level_r Drainag on_Den _of_bu _of_int ver_lise ation_m the p_and_ g_amen nsity_5 _Index_ quency blic_fac come come come _driver uses _availa ther_mo ess oad e sity s_stop_ ersectio nce ode_M sstreet down ities 00 500 _500 ilities_5 _lisence ble de _500 500 n_500 otorbike 00 Male -.588 ** -.588 -.008 -.031 -.008 -.181** 058 207** 065 -.007 -.167** 062 014 017 -.031 -.077 022 -.088 -.031 047 -.051 003 011 208** ** ** ** ** -.098 ** -.097 -.172** -.011 -.046 -.031 -.054 -.057 * -.051 -.013 -.010 026 018 057 105 * ** 026 -.022 014 091 013 096 -.163 072 -.181** 058 -.005 -.027 106 154** 005 135 090 084 057 036 094 068 -.017 ** 456 -.103 144* -.061 -.342 115 -.203 -.016 -.261 141* 279** 191** -.053 110 -.049 -.087 -.134 007 -.103 -.816 ** ** 115 -.816 -.338** -.149* -.146* -.060 -.215** -.067 -.045 -.085 060 073 -.025 055 -.060 063 007 007 -.026 -.004 036 011 -.026 -.007 045 057 049 -.044 -.078 -.112 -.106 -.071 -.031 -.003 141* -.186** 263** -.027 083 -.080 -.007 025 004 011 -.018 051 043 102 137* 279** -.149* 162** 246** -.037 137* 035 -.103 -.058 057 -.052 099 020 066 092 -.156** -.097 191** -.053 -.146* -.060 210** -.009 263** -.027 262** -.037 -.043 021 120* -.053 031 059 047 025 -.031 020 ** ** -.014 ** 044 178** -.004 042 -.043 181** 089 135* -.005 162** 046 -.167** 062 -.152** 049 -.043 Main_transportation_mode_ Motorbike Total_buses 262** 122* 108 092 -.007 246** -.116* 075 -.107 -.261** -.098 -.268** 063 158** 101 050 -.338** 210** -.100 084 -.016 162** -.016 -.009 -.203** -.268** -.186** 063 -.116* -.106 -.012 Private_vehicles_available -.172** -.046 -.011 110 101 083 089 -.261** -.059 -.124* -.087 -.174** -.082 -.080 181** 021 -.190** -.047 -.026 137* 035 -.269** -.003 -.049 158** 084 -.193** -.054 -.054 -.215** -.067 -.142* 023 315** 195** Cleanliness 014 -.057 -.087 -.045 050 -.007 -.007 -.103 Level_road 017 * 007 -.085 060 045 025 ** 184** -.014 161** 081 -.106 073 057 004 -.152 -.043 120* 049 -.053 -.005 -.025 049 011 -.058 031 210** 044 174** 095 -.004 -.012 137* -.002 Male Low_income Mid_income High_income Car_driver_lisence Motorcycle _driver_lisence Conflict_with_other_mode 207** 065 456 ** -.342** 208** -.016 -.100 113 208** -.156 113 Across -.031 -.134 -.051 Drainage -.077 -.013 -.116* 026 Step_up_and_down 022 -.010 -.022 -.027 055 -.044 -.018 057 Walking_amenities -.088 026 014 106 -.060 -.078 051 -.052 178** 042 Population_Density _500 -.031 018 005 063 -.112 043 099 059 -.142* 023 315 195** 184 210 -.019 -.009 -.020 161** 081 174** 095 137* -.002 167** 374** 277** 150* 016 -.001 047 005 -.037 -.066 299** 261** -.090 -.068 -.014 -.072 -.078 -.101 167 ** 313 ** ** 262** 034 016 ** 313** 269** 081 058 401 ** 401 ** * 121 041 -.038 -.022 -.043 -.036 -.012 -.052 374** 299** 196** 040 260** -.022 -.092 -.042 -.058 -.087 -.070 -.060 277** 261** 290** 067 052 014 002 -.103 -.036 134* 134* -.041 262** 081 375** 040 -.046 150* 269** 034 -.013 016 061 053 012 -.093 -.044 * ** ** 067 -.023 -.001 -.019 050 005 -.059 025 288** 394** 435 ** 380** -.040 ** 269 058 196 269 375** 016 121 041 260 -.022 290 -.046 -.013 -.023 047 057 154** 091 057 007 -.106 108 047 -.193** -.054 016 -.090 -.038 -.092 -.041 016 -.001 406 ** 762 ** 664 ** 622 ** 105 013 036 007 -.071 020 025 ** -.003 -.001 -.068 -.022 -.042 052 061 -.019 ** 639 ** 639 ** 777 ** -.051 122* 092 406 ** ** 690 ** ** 318** Number_of_bus_stop_500 003 * 094 -.026 * 066 -.031 ** -.190 -.047 047 -.014 -.043 -.058 014 053 050 394 777 ** ** 880 ** ** 626 ** 011 096 068 -.004 -.116 -.107 075 Bus_frequency_500 135 084 090 102 092 020 -.261** -.059 005 -.072 -.036 -.087 002 012 005 435 ** 762 ** 690 ** 880 ** 583 ** ** ** * * -.005 * -.087 -.037 -.078 -.012 -.070 -.103 -.093 -.059 ** 664 ** ** 566 ** 611 ** 611 ** ** -.082 -.066 -.101 -.052 -.060 -.036 -.044 025 622 ** 626 ** 583 ** ** Job_Density_500 Entropy_Index_500 Number_of_public_facilities _500 Number_of_intersection_50 208 * 144 -.163 -.061 072 -.017 036 -.031 -.019 -.009 011 -.003 137 ** 162 135 046 -.020 -.269 -.124 -.174 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 65 288 ** 380 -.040 620 277 ** 318 620 277 566 761 761 ** Correlations of buffer 100 - Egress M ain_tras Number_o M otorcycl Other_veh Population Number_o Number_o Low_inco M id_inco High_inco Car_driver portation_ Total_bus Job_Densi Entropy_I Bus_frequ f_public_f e_driver_li icles_avail _Density f_bus_sto f_intersect me me me _license mode_M o es ty_100 ndex_100 ency_100 acilities_1 cense able _100 p_100 ion_100 torbike 00 Senior_pe Young_pe M ale ople ople Senior_people Young_people M ale ** -.499 081 -.499** 081 -.159** 081 -.040 447 ** -.378 -.116 -.040 -.116* 084 052 -.116* 084 -.806** 052 -.321 ** -.302 -.227 ** 213 Low_income -.159** M id_income 081 -.378** * 127 * -.116 047 -.282 High_income Car_driver_license M otorcycle_driver_lice nse M ain_trasportation_mo de_M otorbike Total_buses Other_vehicles_availabl e Population_Density _100 Job_Density_100 ** 447 ** * ** 174 ** ** ** -.806 * 127* 047 * -.282 -.023 099 ** 023 064 -.044 089 123* -.055 052 -.123 -.055 -.076 024 -.132 * -.181 174** 282** 070 048 062 081 010 -.026 161** 167** -.001 052 -.321** -.227** -.143* -.195** -.085 -.221** 028 -.074 030 002 048 -.022 -.107 -.302** 213** 169** 267** 004 144* -.030 044 -.048 009 001 -.029 032 -.113 * 129 * 126 002 049 028 -.017 -.079 082 121* ** 115 * 159 ** 059 -.006 028 127 * 076 005 064 * ** 024 ** 024 -.040 244 230** -.195** 267** -.113 -.068 026 048 -.085 004 129 * * 144 126 * -.040 ** 169 070 -.114 244 ** -.186** ** -.180** 026 -.141* ** -.068 -.186 -.114 -.143 -.141* * -.039 282 ** -.039 ** 230 ** * ** 307 061 148 -.040 051 022 069 078 040 095 307** -.067 274** -.047 029 027 043 046 028 019 * 061 -.067 112 -.109 -.046 -.041 -.064 -.039 -.064 018 ** * ** 274 112 005 009 045 -.003 010 -.043 077 115 -.055 062 -.221 -.023 052 081 028 -.030 002 059 -.040 -.047 -.109 005 013 111 -.038 020 117* 072 099 -.123* 010 -.074 044 049 -.006 051 029 -.046 009 013 178** 180** 125* 284** 160** Entropy_Index_100 023 -.055 -.026 030 -.048 028 028 022 027 -.041 045 111 178** 175** 180** 238** 056 Number_of_bus_stop_1 00 Bus_frequency_100 064 -.076 161 ** 002 009 -.017 127 * 069 043 -.064 -.003 -.038 180 831 055 024 012 -.015 254** Number_of_public_facil ities_100 Number_of_intersection _100 -.180 159 148 ** ** 167 048 001 -.079 076 078 046 -.039 010 020 125 * -.044 024 089 -.132* -.001 -.022 -.029 082 005 040 028 -.064 -.043 117* 284** ** 052 -.107 032 121 * 064 095 019 018 077 072 160 * 123 -.181 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 66 ** ** 175 ** 180 ** 831 ** 238** 055 012 056 024 -.015 254 ** Correlations buffer 200- Egress Senior_pe Young_pe ople ople Main_tras Number_o Motorcycl portation_ Private_ve Populatio Number_o f_public_f Number_o Low_inco Mid_inco High_inco Car_driver e_driver_li mode_Mo Total_bus hicles_ava n_Density Job_Densi Entropy_I f_bus_sto Bus_frequ acilities_2 f_intersect me me me _license cense torbike es ilable _200 ty_200 ndex_200 p_200 ency_200 00 ion_200 Male Senior_people -.499 ** 081 -.159** 081 127* 047 -.039 -.141* -.068 -.180** -.015 093 012 133* -.046 041 251** Young_people -.499 ** -.040 447 ** -.378** -.116* -.282** -.114* -.186** 026 -.055 049 -.131* -.032 -.111 037 -.095 -.228** 081 -.040 -.116* 084 052 174** 282** 070 048 062 083 007 -.048 093 069 067 053 Low_income -.159** 447 ** -.116* -.806 ** -.321** -.227** -.143* -.195** -.085 -.221** 015 -.072 019 -.029 -.033 -.034 -.111 Mid_income 081 -.378** 084 -.806 ** -.302** 213** 169** 267** 004 144* -.024 050 -.015 058 084 021 056 High_income 127* -.116* 052 -.321** -.302** 024 -.040 -.113 129* 126* 014 037 -.006 -.046 -.081 021 089 047 -.282** 174** -.227** 213** 024 244** 230** 115* 159** 064 009 -.005 131* 054 -.013 138* -.039 -.114* 282** -.143* 169** -.040 244** 307** 061 148* -.038 054 -.067 041 018 059 090 -.141* -.186** 070 -.195** 267** -.113 230** 307** -.067 274** -.044 031 012 074 099 066 048 -.068 026 048 -.085 004 129* 115* 061 -.067 112 -.111 -.048 -.068 -.110 -.062 -.078 010 -.180** -.055 062 -.221** 144* 126* 159** 148* 274** 112 006 011 -.009 032 052 -.038 018 -.015 049 083 015 -.024 014 064 -.038 -.044 -.111 006 045 075 061 092 066 -.034 093 * 007 -.072 050 037 009 054 031 -.048 011 045 ** ** * ** 269** Male Car_driver_license Motorcycle_driver_li cense Main_trasportation_ mode_Motorbike Total_buses Private_vehicles_ava ilable Population_Density _200 Job_Density_200 -.131 280 219 143 431 Entropy_Index_200 012 -.032 -.048 019 -.015 -.006 -.005 -.067 012 -.068 -.009 075 280** 297** 356** 229** -.130* Number_of_bus_sto p_200 Bus_frequency_200 133* -.111 093 -.029 058 -.046 131* 041 074 -.110 032 061 219** 297** 636 ** 111 137* -.046 037 069 -.033 084 -.081 054 018 099 -.062 052 092 143* 356** 636 ** 095 039 Number_of_public_f acilities_200 Number_of_intersect ion_200 041 -.095 067 -.034 021 021 -.013 059 066 -.078 -.038 066 431 ** 229** 111 095 366** 251** -.228** 053 -.111 056 089 138* 090 048 010 018 -.034 269** -.130* 137* 039 366** ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 67 Correlations of buffer 500 - Egress Senior_pe Young_pe ople ople Senior_people Young_people Male Low_income Mid_income High_income Main_tras Number_o Motorcycl portation_ Other_ve Populatio Number_o f_public_f Number_o Low_inco Mid_inco High_inco Car_driver e_driver_l mode_Mo Total_bus hicles_av n_Density Job_Dens Entropy_I f_bus_sto Bus_frequ acilities_5 f_intersec me me me _license icense torbike es ailable _500 ity_500 ndex_500 p_500 ency_500 00 tion_500 Male ** 081 -.159** 081 127* 047 -.039 -.141* -.068 -.180** -.033 025 -.083 094 032 133* 235** -.499 ** -.040 447 ** -.378** -.116* -.282** -.114* -.186** 026 -.055 074 -.118* 071 -.066 045 -.164** -.247** 081 -.040 -.116* 084 052 174** 282** 070 048 062 089 014 007 195** 128* 021 034 -.159** 447 ** -.116* -.806 ** -.321** -.227** -.143* -.195** -.085 -.221** 029 -.087 003 019 -.015 -.045 -.071 081 ** 084 ** ** ** ** ** 004 * -.028 062 012 019 016 026 045 ** ** 024 -.040 -.113 * 129 * 126 -.001 041 -.024 -.061 -.002 031 043 * -.499 -.378 -.806 -.302 213 169 267 144 * 052 047 -.282** 174** -.227** 213** 024 244** 230** 115* 159** 071 -.018 -.133* 059 003 -.005 123* -.039 -.114* 282** -.143* 169** -.040 244** 307** 061 148* -.046 044 -.038 047 034 047 133* -.141* -.186** 070 -.195** 267** -.113 230** 307** -.067 274** -.053 080 003 083 052 091 103 -.068 026 048 -.085 004 129* 115* 061 -.067 112 -.136* -.098 -.071 -.146* -.094 -.128* -.097 Other_vehicles_ available Population_Dens ity _500 Job_Density_500 -.180** -.055 062 -.221** 144* 126* 159** 148* 274** 112 -.013 027 010 -.080 -.069 -.058 -.033 -.033 074 089 029 -.028 -.001 071 -.046 -.053 -.136* -.013 185** 363** 241** 182** 181** -.011 025 * 014 -.087 062 041 -.018 044 080 -.098 027 ** 185 ** ** ** 342 594 ** 391** Entropy_Index_5 00 Number_of_bus _stop_500 Bus_frequency_ 500 Number_of_publ ic_facilities_500 Number_of_inter section_500 -.083 071 007 003 012 -.024 -.133* -.038 003 -.071 010 363** 404 ** 353** 441 ** 184** -.012 094 -.066 195** 019 019 -.061 059 047 083 -.146* -.080 241** 406 ** 353** 677 ** 416 ** 371** 032 045 128* -.015 016 -.002 003 034 052 -.094 -.069 182** 342** 441 ** 677 ** 338** 208** 133* -.164** 021 -.045 026 031 -.005 047 091 -.128* -.058 181** 594 ** 184** 416 ** 338** 732 ** 235** -.247** 034 -.071 045 043 123* 133* 103 -.097 -.033 -.011 391** -.012 371** 208** 732 ** Car_driver_licen se Motorcycle_driv er_license Main_trasportati on_mode_Motor Total_buses 127 -.116 -.118 -.321 -.302 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 68 404 406 Correlations buffer 1000 - Egress Senior_ Young_ people people Main_tr Number Motorcy asportat Private_ Populati Number _of_pub Number Car_dri cle_driv ion_mo vehicles on_Den Job_De Entropy _of_bus Bus_fre lic_facili _of_inte Low_in Mid_inc High_in ver_lice er_licen de_Mot Total_b _availa sity nsity_1 _Index_ _stop_1 quency ties_10 rsection come ome come nse se orbike uses ble _1000 000 1000 000 _1000 00 _1000 Male Senior_people -.499 ** 081 -.159 ** 081 127 * 047 -.039 -.141 * -.068 -.180 ** -.023 007 -.133 * -.001 -.037 140 * 144 * Young_people -.499 ** -.040 447 ** -.378 ** -.116 * -.282 ** -.114 * -.186 ** 026 -.055 098 -.105 123 * -.022 031 -.146 * -.183 ** 081 -.040 * 084 052 ** 070 048 062 128 * 033 -.032 022 025 046 -.009 ** 447 ** * ** -.321 ** * -.195 ** -.085 ** 016 -.031 044 045 025 -.033 -.019 -.378 ** 084 -.806 ** -.302 ** 267 ** 004 144 * 005 032 -.012 -.021 004 040 011 -.321 ** ** 024 -.040 -.113 129 * 126 * -.034 -.002 -.051 -.039 -.046 -.010 012 Male Low_income Mid_income High_income -.159 081 * -.116 -.116 -.806 174 ** -.227 ** 213 ** 282 -.143 169 ** -.221 * 052 047 -.282 ** 174 ** -.227 ** 213 ** 024 244 ** 230 ** 115 * 159 ** 035 -.035 -.096 -.058 -.059 -.020 018 -.039 -.114 * 282 ** -.143 * 169 ** -.040 244 ** 307 ** 061 148 * -.042 037 -.033 -.008 025 060 082 * ** 070 ** ** -.113 230 ** ** -.067 ** -.062 067 001 053 028 084 129 -.068 026 048 -.085 004 129 * 115 * 061 -.067 112 -.131 * -.116 * -.105 -.111 -.123 * -.167 ** -.144 * Private_vehicles_av ailable Population_Density _1000 Job_Density_1000 -.180 ** -.055 062 -.221 ** 144 * 126 * 159 ** 148 * 274 ** 112 -.078 -.031 004 -.065 -.054 -.071 -.003 -.023 098 128 * 016 005 -.034 035 -.042 -.062 -.131 * -.078 ** 402 ** ** ** ** -.016 007 -.105 033 -.031 032 -.002 -.035 037 067 -.116 * -.031 372 ** 570 ** 793 ** 804 ** 713 ** 557 ** Entropy_Index_1000 -.133 * 123 * -.032 044 -.012 -.051 -.096 -.033 001 -.105 004 402 ** 570 ** 633 ** 710 ** 219 ** 088 ** ** ** ** 498 ** Car_driver_license Motorcycle_driver_lic ense Main_trasportation_ mode_Motorbike Total_buses Number_of_bus_st op_1000 Bus_frequency_100 Number_of_public_f acilities_1000 Number_of_intersec tion_1000 127 -.141 -.116 -.186 -.195 -.302 267 307 274 372 443 499 278 * ** -.001 -.022 022 045 -.021 -.039 -.058 -.008 053 -.111 -.065 443 -.037 031 025 025 004 -.046 -.059 025 028 -.123 * -.054 499 ** 804 ** 710 ** 875 ** 624 ** 473 ** 140 * -.146 * 046 -.033 040 -.010 -.020 060 084 -.167 ** -.071 278 ** 713 ** 219 ** 498 ** 624 ** 844 ** 144 * -.183 ** -.009 -.019 011 012 018 082 129 * -.144 * -.003 -.016 557 ** 088 440 ** 473 ** 844 ** ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-ta 69 793 633 875 440 70 ... correlation with walking distance to stops within downtown areas, (3) the number of transit stops positively associated with walking distance to stops within downtown whereas is negatively correlated with. .. transport in Hanoi and (2) determining how built environment characteristics influence walking distance to transit stops of both access segment from origins to transit stops and egress segment from transit. .. models to compare the effects of the built environment around transit stops upon walking distance of transit egress trip Focusing on walking distance of 10 egress trip (between transit stops and