Impact assessment of traffic congestion mitigation policies on transportation network in hanoi city

This thesis study aims to analyze the impact of traffic congestion mitigation policies of Hanoi city on it's transportation network.. Traffic volume and traffic congestion in the road ne

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

NGO THI MAI LOAN

IMPACT ASSESSMENT OF TRAFFIC CONGESTION MITIGATION POLICIES

ON TRANSPORTATION NETWORK IN

HANOI CITY

MASTER'S THESIS

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM JAPAN UNIVERSITY

NGO THI MAI LOAN

IMPACT ASSESSMENT OF TRAFFIC CONGESTION MITIGATION POLICIES

ABSTRACT

Recently, with the rapid growing economics and urbanization in Hanoi city, there is

an increasing of auto – mobilization, This has effected on the level of transport demand, transport patterns and led to the overload of the urban transport infrastructure, causing traffic congestion and environment pollution Therefore, the city government has approved a number of mechanisms, policies and measures to manage and reduce the role of the private automobile to reduce traffic congestion and protect the environment

This thesis study aims to analyze the impact of traffic congestion mitigation policies

of Hanoi city on it's transportation network The policy will ban the activities of motorcycle in the central districts of Hanoi city by 2030 To do so, this study used a dataset from a stated preference Survey that was designed and conducted from a project of World Bank since 2014 This Survey interviewed total 6047 respondents

in the whole 30 districts of Hanoi city Urban transport modeling was estimated using the internationally common 4-step model (Trip generation, trip distribution, mode choice analysis and trip assignment) This 4-step model helps to pridict transport demand in 2030 Then, a traffic demand forecast system was made based

on a demand analysis software called “VISUM” This traffic demand forecast system will helps to evaluate the impact of ban policy by analysing and then comparing on three different scenarios of Motorcycle ban policies

The results of this study reveal that the ban policy contributes toward reducing traffic congestion These finding of this study would assess the feasibility and efficiency of the policy and provide useful information on recommendations for the motorcycle ban policy in hanoi city Furthermore, this would contribute to the planner who doing with urban transport planning of Hanoi and the policy making in making public transport development plan

ACKNOWLEDGEMENT

To begin with, I would like to thank Vietnam Japan University for giving me opportunity to meet and learn from leading professors of Vietnam and Japan when doing my master study here The knowledge and experience that I gained from here during my study period of almost 2 years have been very useful for me

Firstly, I would like to thank to Dr Tran Minh Tu, my supervisor Dr Tu gave me very in-time valuable teaching and guiding in preparing and doing my master study

I also would like to express my gratitude to Prof Hironori KATO and Dr Phan Le Binh, my academic supervisors for their permission to be my academic supervisors and more importantly for their enthusiastic encouragements and precious instructions during my master study and my thesis study

My special thank goes to the program Director of MIE program, Prof Nguyen Dinh Duc for his kindness advice, help and support during my master study, this is a source of encouragement for me in studying

I would like to thank to two program assisstants of MIE program, Mr Nguyen Ngoc Dung and Mr Bui Hoang Tan for their usful assisstance during my master study I’m very grateful for their contributions

I would like to thank Assoct.Prof Vu Hoai Nam for his kindness surport when lending me the lisence key of VISUM software to do my thesis study This surport was very usful and valuable

Finally, I am grateful to all JICA long-term experts at VJU, VJU office of academic affairs and the VJU Career Survice Team for their help, support and provide students like me information and precious opportunity in finding a suitable job after graduated I would like to express my grateful for their contributions

TABLE OF CONTENTS

LIST OF TABLES V LIST OF FIGURES VI

INTRODUCTION 1

BACKGROUND OF THE STUDY 1

RESEARCH QUESTION 3

SCOPE OF THE STUDY 4

THESIS STRUCTURE 5

CHAPTER 1: LITERATURE REVIEW 7

CHAPTER 2: DATA 9

2.1.STATED PREFERENCE DATA 9

2.1.1 Introduction 9

2.1.2 Designing of the questionnaire 9

2.1.3 Characteristics of collected data .12

2.1.4 Conclusion .19

2.2.NETWORK AND ZONE DATABASE .20

2.2.1 Zone system .20

2.2.2 Road Network and Bus Network .20

CHAPTER 3: METHODOLOGY 23

3.1.OVERALL APPROACH TO ASSESSMENT OF MOTORCYCLE BAN 23

3.2.TRAVEL DEMAND FORECAST FOR NETWORK DEVELOPMENT TO 2030 25

3.3.ESTIMATION OF STATED PREFERENCE DATA 26

CHAPTER 4: RESULTS AND DISCUSSIONS 28

4.1.RESULTS OF MODEL ESTIMATION 28

4.2.SCENARIOS ANALYSIS 29

CONCLUSIONS 34

REFERENCES 35

APPENDIX 37

APPENDIX 1: TYPICAL SP QUESTIONNAIRE FORM OF WORLDBANK SURVEY 2014 .37

APPENDIX 2: ZONE SYSTEM OF THE TRAVEL DEMAND MODEL ANALYSIS 46

APPENDIX 3: LIST OF PLANED ROAD NETWORK 2030 IN THE URBAN CENTRAL OF HANOI CITY .60

LIST OF TABLES

Table 1 Total automobiles and motorcycles in the stage of 2005-2016 1

Table 2.1.1 Population density of Hanoi city in 2014 and number of

Table 2.1.3 Descriptive of household vehicle ownership by Income 17

Table 2.1.4 Descriptive of Modal share by household monthly income

LIST OF FIGURES

Figure 1 Growth chart of Motocycle in Hanoi, stage of 2005-2016 2

Figure 2 Growth chart of automobiles in Hanoi, stage of 2005-2016 2

Figure 2.1 Sample of a choice options in Question D2 of SP 12

Figure 2.2 Comparison of Age distribution: Field survey versus

Statistical Yearbook 2014

14

Figure 2.6 Zone system in transport modeling by VISUM software 19

Figure 2.7 Simulating of Hanoi road network in Visum network model 20

Figure 3.1 Overall approach to assess motorcycle ban policy 21

Figure 4.1 Traffic volume and traffic congestion in the road network

without the motorcycle ban policy

28

Figure 4.2 Traffic volume and traffic congestion in the road network

with the motorcycle ban policy in the urban core (4 districts)

29

Figure 4.3 Traffic volume and traffic congestion in the road network

with the motorcycle ban policy in the urban fringe (9 districts)

30

INTRODUCTION

Background of the study

Like many other Asian cities, Hanoi recently experience a special situation that called motorcycle dependence city Motorization in Hanoi also accelerated dramatically, with the number of motor vehicles (including motorcycles) reaching 5.7 million by 2016 compared to two million in 2005 (Note that the number of cars

in the city grew from just 56,000 in 2005 to over 328,000 in 2016, but motorcycles continued to dominate the streets in huge numbers (80%), while bus ridership declined, accounting for less than 10 percent of all trips

According to statistics of Vietnam Register Department and The Police of Hanoi, the number of road traffic in the city as of December 2016 as follows:

Table 1 Total automobiles and motorcycles in the stage of 2005-2016

Figure 1 and Figure 2 show the growth chart of motorcycle and automobiles in Hanoi at the stage of 2005 to 2016

Figure 1: Growth chart of Motocycle in Hanoi, stage of 2005-2016

Figure 2: Growth chart of automobiles in Hanoi, stage of 2005-2016

Source: Plan “Strengthen the management of road traffic to reduce traffic congestion and environmental pollution in Hanoi city, period 2017-2020, vision to 2030”

With over 5.2 million motorcycles, 485,955 automobiles, more than 1.2 million

0 1000000

15% of vehivles from other cities); The average growth rate for the period of

2011-2016 is 10.2% for automobiles and 6.7% for motorcycles, while the average growth rate for road length is only 3.85% The rapid development of road traffics has created a great pressure on the transport infrastructure of Hanoi city, which increases traffic congestion and environmental pollution This situation require

proper policies to reduce road congestion of Hanoi city

On 4th July 2017, Hanoi People’s Committee has approved the plan “Increasing management of road vehicles in order to reduce traffic congestion and environmental pollution in Hanoi in the 2017-2020 period, and vision to 2030”, at the Decision No.5953/QD-UBDN Six groups of solutions were proposed to reduce traffic congestion The third solution was to stop the activities of motorbikes in the

urban districts in 2030 Itinerary to stop motorbike activities as follows:

+ Stop the activities of motorcycles by hour, by day, on some main street, in some center districts of the city in the period of 2025-2029

+ Stop the activities of motorbikes in the center urban districts in 2030

These solutions were proposed but there is no specific impact assessment yet to assess the Feasibility and efficiency of the ban policy

With the context as mentioned above, It is necessary to assess the impact of those solutions of the plan on mode choice behaviors of Hanoi’s people, and further is the impacts on transport network of the city

to design detail plan to implement the solutions effectively

Scope of the study

According to the motorcycle ban policy, motorcycle's activities will be stopped in the urban districts in 2030 Hence, this study will focus on assess the impact of traffic congestion mitigation policies on transportation net work in 4 districts in the core of Hanoi city: Hoan Kiem, Ba Dinh, Dong Da, Hai Ba Trung and 5 districts in urban fringe: Cau Giay, Tay Ho, Thanh Xuan, Hoang Mai and Long Bien

Figure 1.3 illustrates the study area, that includes 9 central district of Hanoi city As

of 2016, Hanoi city is consists of 30 districts, the total area of the city is approximately 3,358.92 km2, the total population is approximately 7.58 million and the average population density is approximately 2.3 thousands people per 1 km2 The study area has a total population of 2.5 million, with an area of 180.63 km2 and the average population density is approximately 14 thousands people per 1 km2 The area of the study area accounts for only 5.4% of the total area of Hanoi but the population accounts for 33.3%, the population density of the study area is 6,2 times compare to the whole city

The urbanization process in Hanoi is currently unbalanced, the urbanization progresses so fast in the central districts, while the suburban are developing very poorly, the The construction of a number of bridges across the Red River such as Nhat Tan, Vinh Tuy, Thanh Tri and Tu Lien creating conditions for urban development in the north eastern districts of Hanoi The study area is located inside the Ring Road no.3 The urban core of the city is the center of socio-cultural and political activities While, The urban fringe is the center of business activities with business offices and new urban areas and high population density This led to the increasing of high travel demand, along with traffic jams and traffic congestion during peak hours The study area is connected to the suburban area by the radial axis link road system Currently, along these link roads, new urban areas are under construction at high densities, which present a potential for serious traffic congestion in the near future In order to deal with this situation, Hanoi needs to invest in a modern public transport system that supply high capacity and high speed

to connect between the central urban area and the suburban Further more, the city need to have proper policies to encourage people to use public transport and minimize the use of personal vehicles

Figure 3 Study area in Hanoi

Thesis structure

This study comprises of 6 Parts as follows:

Introduction

This includes the general introduction, background, research questions, scope of the study and research design

Chapter 1: Literature Review

It reviews the extant literature

Chapter 4: Results and Discussion

Presents the estimation results of the model and presents the simulation results of the impact analysis

Conclusion

It includes the summary of the findings and followed by the recommendations and suggestion for future research

CHAPTER 1: LITERATURE REVIEW

In the field of urban transportation research, there are some studies that have estimated the impact of motorcycles ban policies in developing cities Xingdong et

al (2009) summarizes the major characteristics of the traffic mode transferring period after “Motorcycle Forbidden Ban” Effect across main urban areas in Guangzhou City since 2007 The study estimated the travel volumes transferring from motorcycles to other modes and analyzed the changes of residents’ travel mode choice and showed that the ban decreased the use of motorcycles and increased the use of public transportation, bicycles, and cars The study has assessed the impact of a motorcycle ban primarily on an individual’s modal choice, that is the shifting from the use of motorcycles to other transportation modes Inaba and Kato (2016) analyzed the potential impacts of a motorcycle ban with an integrated travel demand model that combine with trip generation, vehicle ownership, and modal choice in Yangon City where motorcycles have been ban since 2003 To do the study, Inaba and Kato have estimated a vehicle ownership model with travel demand models of modal choice, destination choice, and trip frequency, then developed a traffic demand forecasts system in which, a traffic assignment modal is integrated with a vehicle ownership model and travel demand models to evaluate the impacts of motorcycle ban Result of the study showed that the ban policy have contributed to the mitigation of the urban transportation problems of Yangon; however it would promote car ownership Two studies above have assessed the impact of motorcycle ban policies in the context of a ban policy that will be implemented in 2030 These studies estimated the contribution of the ban policies to the mitigation of the urban transportation problems by comparing the congestion situation before and after the implemented of the policies and estimated the shifting from the use of motorcycles to other transportation modes This study will assess the impact to the traffic congestion mitigation of a motorcycle ban policy that has not implemented yet by comparing the congestion situation of Hanoi city with 2 scenarios with or without ban policy at the year of implementation To do so, this

study will estimate a commuting mode choice model behavior of Hanoi’s people and then building a travel demand forecast model in 2030 The results of this study would assess the feasibility and efficiency of the policy the give recommendation for the ban policy in hanoi Furthermore, this would be contribute to the planner who doing with urban transport planning of Hanoi and the policy making in making public transport development plan

Like other developing cities, numbers of motor vehicles in Hanoi are rising rapidly Between 2011 and 2016, the average growth rate for number of automobile is 10.2% and 6.7% for motorcycles Along with it, there were a number of studies that estimated mode choice behavior of Hanoi's people VA Tuan (2015) estimated mode choice behavior and modal shift to public transport to explore patterns of people's travel behavior and anticipate mode choice changes under intervention scenarios The study has conducted a stated preference survey of person trips and estimated a SP/RP mode choice models for different population segments the study examined people's responses to different policy scenarios Tran el at (2015) assessed effects of perceived neighborhood walkability on mode choice of short- distance trips in Hanoi city While, Tran el at (2016) evaluated effects of land use diversity and population density on the commuting mode choice by developing a joint analysis of residential location, work location and commuting mode choices in Hanoi Not like these above studies, this study estimate a mode choice model using

a dataset consists of 6047 respondents that was conducted by World Bank since

2014 The survey built 9 scenarios of stated preferences survey The survey develop BNL model for each choice set then, combining difference data sources by using scale parameter and finally a multiple-BNL model is developed Parameters that received from the model would be used to develop the 2030 OD matrix by transport mode Up to the time of this study, for all of our research, no study has estimated mode choice model and building demand forecast model to assess the impact of motorcycle ban policy in Hanoi city

2.1.2 Designing of the questionnaire

A typical questionnaire of the survey is divided into 7 parts:

- Part 0: Filter conditions;

- Part A: personal's information;

- Part B: Household's information;

- Part C: Household's vehicle ownership;

- Part F: Contact info of respondents

Part 0 consists of 2 condition questions to filter in suitable respondents who are over

18 years old and have a driver's license

Part A consists of 3 questions from A1 to A3 to collect information about personal information

Part B consists of 5 questions, which are used to investigate basic household information as: number of family members, household's type, household's income, type and area of the house

Part C consists of 2 questions about household's vehicle ownership

Part D1 consists of 9 questions namely from D1 to D9 respectively This part investigates details information about a most recent trip that has using vehicle These information are include of information about purpose of the trip, time and distance, self-ride, number of passengers, type of vehicle, number of stop, parking available The respondent also request to provide information parking fee and cost

of parking fee for the whole trip

Part D2 is a stated preference (SP) experiment on transport mode choice for the trip that they described at part D1 above The SP experiment consists of nine cases Respondents are requested to assume to review and select the mode of the trip under each scenario case Each scenario offers two types of vehicles to choose from among five categories: bus, mass rapid transit (MRT), car, motorcycle and motorcycle taxi In a base scenario case, one alternative comprises from 3 to 5 attributes belong to type of mode, these attributes are: fare price, fuel price, parking fee, walking time to station and time from door to door The attributes are supposed

to have four levels for each case: The current value, the current value +50%, the current - 50% and double of the current value

The questionnaire set of the survey were designed into 24 versions, namely, version 1.1, version 1.2, version 2.1 to version 12.1, version 12.2 respectively These 24 versions are divided into 2 groups to investigate about mode choice of a work trip

(school trip) or non-work trip Group 1 consists of 12 versions from version 1.1 to version 6.2, Group 2 consists of 12 versions from version 7.1 to version 12.2

Contents of 24 versions only different at part D 3140 respondents were asked to describe about a work (school) trip, while 2907 other respondents described about a non-work trip (shopping or entertainment) To design content of Question D2, 5 transport mode were paired together into 10 pairs as follows: Car - Bus, Car - MRT, Car - Motorcycle taxi, Bus - MRT, Motorcycle - Car, Motorcycle - MRT, Motorcycle - Motorcycle taxi, Motorcycle - Bus, Motorcycle taxi - MRT and Motorcycle taxi - Bus From these 10 pairs of transport mode, project survey team has designed 24 hypothetical scenario cases by changing level of attributes of alternatives in each case, these 24 hypothetical scenario cases, namely, 1C, 2C to 24C, respectively

Nine cases in Question D2 of version 1.1 are used in version 1.2 also but were arranged in reversed order, Similarly for the case from version 2.1 and version 2.2

to version 12.1 and version 12.2, respectively Nine cases in Question D2 of version 1.1 and version 7.1 are the same, Similarly for the case from version 1.2 and version 7.2, version 2.1 and version 8.1 to version 6.1 and version 12.1, version 6.2 and version 12.2 respectively Nine scenario cases of Question D2 in each version are selected randomly in 24 designed scenario cases

Figure 2.1 shows a sample of a choice set option in Question D2 of SP survey that presented to the Respondents

Car MRT

Fuel cost 2,500đ/km 5,000đ/km current scenario - Parking cost free - Walking time to the station - 5 minutes

Time from door to door 2 times increase current - 50%

Figure 2.1 Sample of a choice option in Question D2 of SP

Note: Questionnaire form is attached at the appendix 1

2.1.3 Characteristics of collected data

The survey was conducted from April 17th to June 27th 2014 with 6047 respondents successfully collected in the 30 districts of Hanoi city

The table 2.1.1 shows the population density and the number of households surveyed in each district as of year 2014

100

%

Table 2.1.1 Population density of Hanoi city in 2014 and number of respondents

No

Name of

District

Population (thousand people)

Population density (People/km2)

Number of Respondents

Gender distribution of the respondents in the survey has the same high with data from Hanoi Statistical Yearbook 2014 Ratio of female is 50.5% and ratio of male is 49.5% Figure 2.2 shows the comparison between the age distribution (by gender)

of the respondents in the Field Survey with the corresponding data of Hanoi Statistical Yearbook as of 2014 According to the figure 2.2, the age distribution in the survey follows that of the population of Hanoi city, this implies that the sample dataset of the field survey represents the population to a reasonable extent

Figure 2.2 Comparison of Age distribution: Field survey versus Statistical

Yearbook 2014

Figure 2.3 shows the data collected in the occupation field According to the The figure 2.3, the highest share of the respondents work in the survice field with 1239 observations (20.5%), follows by students (20%) and officers (19.15%)

0.00 5.00 10.00 15.00 18-19

0.00 2.00 4.00 6.00 8.00 15-19

Figure 2.3 Occupation of respondents The survey also investigated about household's income of the respondents, table 2.1.2 show the data collected about household's income per month of respondents 38.2% of the respondents have total household's income from 10 million VNĐ to 20 million VNĐ, while only 3.2% of respondents made more than 30 million VNĐ per month

Table 2.1.2 Household's income per month

No Income/ month (VND) Observations %

0 200 400 600 800 1000 1200 1400 Survice

Officer Education

Production

Farm Student Retire Homemaker

Other

Occupation of respondents

Figure 3.4 Description of trip's distance Figure 2.5 describes the moving time of respondent's trips, the most popular moving time is 10 - 20 min (38,4%) followed by 0-10 min (33,8%) and 20-30min (16,2%)

It reveals that approximately 88,4% of respondents are moving at less than 30 minutes, while travel time longer than 60min accounts for only 2% This result reflects the short distance between residences and trip destination with relatively on motorcycle using because of it's door - to - door convenience

Figure 2.5 Description of travel time Table 2.1.3 presents the descriptive statistics of household vehicle ownership by

0 500 1000 1500 2000 2500 0-2km

household monthly income First, this shows that vehicle ownership can be seen across income levels, although the car ownership rate marginally increases with income level, the motorcycle ownership is almost unchanged This implies that motorcycles are popular as an inexpensive transportation mode in Hanoi, and demand of motorcycle use is balanced among the income groups Second, the car ownership rate increases with income level

Table 2.1.3 Descriptive of household vehicle ownership by Income

Household monthly

income VND Car Motorcycle Bicycle

Total Income Obs Obs % Obs % Obs %

< 5 mil 741 13 1.3 600 60.7 376 38.0 989 5mil - 10mil 2207 89 2.7 2054.0 61.9 1173 35.4 3316 10mil - 20mil 2310 171 4.7 2250.0 62.4 1185 32.9 3606 20mil-30mil 595 118 11.5 591.0 57.4 320 31.1 1029

>30mil 194 79 21.3 191.0 51.5 101 27.2 371

Sum 470 5.0 5686 61.1 3155 33.9 9311

Table 2.1.4 presents the descriptive statistics of respondents’ modal share by household monthly income and trip origin, that is, in the urban core, in the urban fringe and in the suburban of the city The survey investigates total 6028 trips and shows 1389 trips were made in the urban core, 2105 trips were made in the urban fringe and the rest 2534 trips were made in the suburban area of the city First, table 2.1.4 shows that car use is promoted by income, while bus use is decrease when income increase Car using inside the urban core increases compare to those outside

it Second, motorcycle using is almost unchanged by income and trip origin It is simply because motorcycles are popular transportation mode in Hanoi, and demand

of motorcycle using is balanced among the groups

Table 2.1.4 Descriptive of Modal share by household monthly income and trip origin

Household monthly

Motorcycle

5mil - 10mil 2207 47 2.1 10.0 0.5 1735 78.7 6 0.3 239 10.8 167 7.6 2204 10mil - 20mil 2310 49 2.1 21.0 0.9 1925 83.7 2 0.1 207 9.0 95 4.1 2299

2.2 Network and Zone database

This study uses a dataset that was compiled from the Metros project of JICA since 2015 The Process of Modeling transport network including public transport system will be done by VISUM software

2.2.1 Zone system

This study using the Visum software version that only suply for 320 zones Hence based on the 560 zone database, these 560 zone were changed in to 320 zone to suit to the zone system of the VISUM version Zone system of the Travel demand model Analysis was shown at the Appendix 2 of this report

Figure 2.6 shows the Zone system in transport modeling by VISUM software

Figure 2.6 Zone system in transport modeling by VISUM software

2.2.2 Road Network and Bus Network

Base on the road network from the Metros project (Metro line no.2 in 2015), Hanoi Road network 2018 (included road network and bridge constructions) will

be complemented by adding and updating new road directly on Visum Attribution of each road includes of: number of lanes, capacity and velocity A total of 2400 links and 760 nodes were added to the base network

Road network in 2030 will be added and updated base on the Hanoi road network

2030 that were published at Decision no 519/QĐ-TTG approved of Hanoi transport master planning to 2030 and vision to 2050 dated March 31 2016 List

of Hanoi planning transport network 2030 was attached at the Appendix no.3 of this report The network includes of: road network and bridge constructions A total of 450 links and 130 nodes were added to the road network 2018 and about

1000 links from the road network 2018 were updated

Figure 2.7 shows Road network of Hanoi that was developed in Visum network model

Figure 2.7 Road network was developed by using VISUM

Public transport network consits of Bus network and Mass Rapit Transit network: + Bus network Hanoi 2018 will be added and updated based on the bus network

that were published on TRANSERCO (Hanoi transportation company) website

A total of 111 routes were inputed

+ Bus network 2030 will be updated base on Bus network development plan to

2025 of TRANSERCO

+ Mass Rapid Trasit network 2030 consists of 4 lines: line 1, line 2A, line 2 and line 3

Figure 2.8 shows the Public transport network of Hanoi that was developed in Visum network model

Figure 2.8 Public transport network was developed by using VISUM

CHAPTER 3: METHODOLOGY

3.1 Overall Approach to Assessment of Motorcycle Ban

Impact Assessment of Motorcycle ban to Hanoi transport network was made based on a demand analysis software called “VISUM”, Visum software has been used widenly in urban transport planning in Vietnam recently Figure 4.1 presents a process of the analysis In the network analysis, input data includes of future travel demand and transport network of existing and planned road and bus routes

Figure 3.1 Overall approach to assess motorcycle ban policy

- 4 districts in urban core: Hoan Kiem, Ba Dinh, Dong Da & Hai Ba Trung)

Socio-economic data (Population & Trip Making)

Current transport

network (Road & Bus)

Transport Development Plan/Projects (Road & UMRT)

Motorcycle Ban Scenarios for Analysis Without

Ban Policy in

2030

Ban Area in 2030: 4 districts

in urban core

Ban Area in 2030: up to 9 districts

Network Performance Analysis by VISUM

(4-step model)

Assessment

Recommendations for Motorcycle Ban Policy in Hanoi

- 5 districts in urban fringe: Tay Ho, Cau Giay, Thanh Xuan, Hoang Mai & Long Bien)

(i) Current and planned transport network: the existing roads and bus network data was collected based on available road and bus route inventory, with reviewed and revised in accordance with the format require of Visum Planned transport network was collected based on Hanoi transport master plan to 2030 and vision to 2050, bus route was collected based on the Bus network development plan of TRANSERCO

(ii) Socio- economic data (population and trip making): Future economic data are required for travel demand forcast are estimated on population based on the use of Hanoi statistics Trip making data is collected based on the household interview Survey that conducted in the study of JICA (namely, METROS)

socio-(iii) Analysis on three different Scenarios of Motorcycle ban policies as follows:

(1) “Without Ban policy in 2030” Scenario: In this scenario, planned transport network are planned but assumed that there will be no motorcycle ban in the city in 2030

(2) “Ban area in the urban core in 2030” Scenario: In this scenario, it is assumed that motorcycle activity will be ban inside 4 district: Hoan Kiem, Dong Da, Ba Dinh and Hai Ba Trung The result of analysis will show how the mode choice behavior is changed when the ban policy is implemented

(3) “Ban area in the urban fringe in 2030” Scenario: In this scenario, it is assumed that motorcycle activity will be ban inside 9 district: Hoan Kiem, Dong Da, Ba Dinh and Hai Ba Trung, Cau Giay, Tay Ho, Thanh Xuan, Hoang Mai, Long Bien The result of analysis will show how the mode choice behavior is changed when the ban policy is implemented

(iv) Analysis on Network performance: Each scenario is evaluated based

on a set of performance indicators for total network

Other assumptions used in the analysis are as follows:

- When the ban policy is implemented, only mode choice behavior is changed, vehicle ownership is unchanged

- No constraints and penalties on the use of private vehicles such as higher parking fee at destinations, road pricing, strict traffic control and enforcement amongst other measures are not considered in the analysis

The result of network analysis will provide useful information on recommendations for Motorcycle ban policy in Hanoi city

3.2 Travel Demand Forecast for Network development to 2030

One of the main purposes of this study is to provide the estimate on urban transport demand in the study area Therefore, the internationally common 4-step model is used in the analysis, Figure 4.2 shows the methodology of demand forecast

Figure 3.2 Methodology of demand forecast This 4-step model will predict transport demand in 2030 The components of 4-step model are as follows:

- The first one is trip generation and attraction model In this model, the number of trip generated from traffic zones and attracted by traffic zones are estimated This process depends on land use and socio-demographic factors

- The second one is trip distribution model The output of this model is number of trips between traffic zones The gravity function model is applied to the estimation of trip distribution in this study (OD table) The number of this between OD pairs depends on travel impedance between those pairs

- The third one is modal split model, the output of this model is the share of trips made between pair of traffic zones by available transport modes Logit model is applied to the estimation of OD table by travel mode The share of each travel mode will highly be affected by travel time and travel cost

- The final one is traffic assignment, the output of this model is the number of vehicles on links of road network

3.3 Estimation of stated preference data

The mode choice model is formulated as the discrete choice model In the model,

in an individual is assumed to choose an option that would maximizing his/her utility function from a modal choice set Using the results of the SP survey, 10 binary choice data set were created The individual's choice set were designed as follows: Motorcycle - Car; Car - UMRT; Motorcycle - UMRT; Car - Bus; Motorcycle - Motorcycle taxi; Motorcycle taxi - UMRT; Bus - UMRT; Motorcycle - Bus; Car - Motorcycle taxi and Motorcycle taxi - Bus Figure 4.3 shows the process of the estimation of SP data

- The probability of choosing a transportation mode m for individual n who from origin i to destination j is:

- Uijm: The ultilize function of individual n chooses a transportation mode m from origin i to destination j

Figure 3.3 process of the estimation of SP data

CHAPTER 4: RESULTS AND DISCUSSIONS

4.1 Results of model estimation

To do the model estimation, the study area of 30 districts was divided into 314 traffic analysis zones and a representative centroid is assumed in each traffic analysis zones Next, a transportation network in Hanoi is update, including: Expressway, national highway, major roads, secondary roads, selected local roads, bridges, bus network and urban rail networks (UMRT) Then, socio-demographic and socioeconomic data are prepared for each traffic analysis zones and travel time and travel cost data are prepared on the basis of the transportation network The unknown coefficients in the modal choice model are estimated using the dataset

Table 4.1 shows the estimation results of the mode choice model Generalized cost is defined as monetary cost plus time cost estimated using the value of time and travel time The value of time is referenced from the Metros line 2 projects (2014) The table shows that Car ownership is significantly positive for car use and similaly, Motorcycle ownership is positive for motorcycle use This results implies that car and motorcycle owners prefer using their vehicles to travel The ceofficient of Household income is signficantly positive for car use and UMRT use and the highest for car, followed by UMRT, It means that people in the family with higher in come would prefer to use car than other public vehicle While, the significantly is negative for bus, it means that people with lower monthly income are more motivated to use bus In the other hand, the ceofficient

of female is signficantly positive for bus use and is significantly negative for car use and UMRT use, It implies that woman are more willing to use bus than car and UMRT The Generalized cost is significantly negative, this is reasonable.


Table 4.1 Estimation results of modal choice model

Figure 4.1 shows the Traffic volume and traffic congestion in the road network without the motorcycle ban policy, Figure 4.2 shows the Traffic volume and traffic congestion in the road network with the motorcycle ban policy in the

urban core (4 districts) and figure 4.3 shows the Traffic volume and traffic congestion in the road network with the motorcycle ban in the urban fringe (9 districts).

Figure 4.1 Traffic volume and traffic congestion in the road network without the

motorcycle ban policy

Figure 4.2 Traffic volume and traffic congestion in the road network with the

motorcycle ban policy in the urban core (4 districts)