Traffic assignment is the last step in the conventional four-step transportation planning model, following trip generation, trip distribution, and mode choice. It concerns selection of routes between origins and destinations on the traffic network. Traditional traffic assignment methods do not consider trip chaining behavior. Since commuters always make daily trips in the form of trip chains, meaning a traveler’s trips are sequentially made with spatial correlation, it makes sense to develop models to feature this trip chaining behavior. Network performance in congested areas depends not only on the total daily traffic volume but also on the trip distribution over the course of a day. Therefore, this research makes an effort to propose a network traffic assignment framework featuring commuters’ trip chaining behavior. Travelers make decisions on their departure time and route choices under a capacity-constrained network. The modeling framework sequentially consists of an activity origin-destination (OD) choice model and a dynamic user equilibrium (DUE) traffic assignment model. A heuristic algorithm in an iterative process is proposed. A solution tells commuters’ daily travel patterns and departure distributions. Finally, a numerical test on a simple transportation network with simulation data is provided. In the numerical test, sensitivity analysis is additionally conducted on modeling parameters.

O objetivo principal deste trabalho é identificar se e como as áreas urbanas interferem nos padrões de viagens encadeadas dos viajantes urbanos. Para atingir os objetivos, as diferenças e similaridades notadas entre os principais grupos socioeconômicos das áreas urbanas em relação aos padrões de viagens encadeadas serão discutidas. O método para comparação dos comportamentos relacionados às viagens encadeadas baseia-se na compatibilização das variáveis das três áreas e posterior aplicação do minerador de dados denominado Árvore de Decisão e Classificação, disponível no pacote estatístico S-Plus 6.1. As viagens encadeadas foram representadas através da codificação inicialmente proposta por Ichikawa (2002) e ampliada por Pitombo (2003). Foram codificados os motivos, modos e período do dia em que cada viagem foi realizada. A análise foi baseada nas pesquisas origem-destino realizadas na região metropolitana de São Paulo pelo Metrô-SP, em 1997, na região metropolitana de Belém pela JICA/Governo do Estado do Pará, em 2000, e na cidade de Bauru pela EMDURB, em 1997. Concluiu-se que, em geral, o comportamento de viajantes urbanos são influenciados pelas políticas urbanas regionais, características socioeconômicas e espaciais de cada região. / The main aim of this work is to identify whether and how the urban areas interfere in the urban trips makers\'trip chaining pattern. For attaining the aims, the differences and similarities observed among the behaviour of trip makers belonging to the main socioeconomic groups living in the three urban areas will be discussed. The method to compare the behavior related to trip chaining is based on the compatibilization of the variables of three areas and subsequent application of the data miner named Decision and Classification Tree, available in the S-Plus 6.1 statistical package. The chained trips were coded by using the process initially proposed by Ichikawa (2002) and amplified later by Pitombo (2003). The trip purpose, travel mode and period of the day in which each trip occurs were coded. The analysis was based on the origin-destination home-interview surveys carried out in São Paulo Metropolitan Area by Metrô-SP, in 1997, Belém Metropolitan Area by JICA/Pará State Government, in 2000, and Bauru city by EMDURB, in 1997. The main finding is that urban trip makers\'behaviour are affected by regional urban policy, socioeconomic features and geographical characteristics of each area.

O objetivo principal deste trabalho é analisar o comportamento de grupos homogêneos de indivíduos com relação às viagens encadeadas, usando um minerador de dados. Vários aspectos das viagens encadeadas foram representados através da extensão do processo de codificação inicialmente proposto por Ichikawa (2002). Foram codificados os aspectos como seqüência de atividades realizadas por cada indivíduo, modo de viagem, período do dia em que cada viagem foi realizada e tempo de viagem. O minerador de dados usado neste trabalho foi Árvore de Decisão e Classificação, uma ferramenta de análise disponível no software S-Plus 2000. A análise baseou-se na pesquisa origem-destino realizada pelo METRÔ-SP na região metropolitana de São Paulo, por meio de entrevistas domiciliares, em 1987. Concluiu-se que variáveis socioeconômicas podem explicar o comportamento relacionado a viagens encadeadas, indicando que minerador de dados pode ter um papel importante na análise do comportamento relacionado às viagens encadeadas. / The main aim of this work is to analyze the behavior of homogeneous groups of individuals regarding the chained trips by using a data miner. Several aspects of chained trips were represented through the extension of the coding process initially proposed by Ichikawa (2002). Aspects such as sequence of activities performed by each individual, travel mode, period of the day in which each trip occurs, and travel time were coded. The data miner used in this work was Decision and Classification Tree, an analysis tool available in S-Plus 2000 software package. The analysis was based on the origin-destination home-interview survey carried out by METRÔ-SP in São Paulo metropolitan area, in 1987. The main finding is that the socioeconomic variables can explain the behavior related to the chained trips, indicating that data miner can play an important role in the analysis of the behavior related to the chained trips.

O objetivo principal deste trabalho é analisar o comportamento de grupos homogêneos de indivíduos com relação às viagens encadeadas, usando um minerador de dados. Vários aspectos das viagens encadeadas foram representados através da extensão do processo de codificação inicialmente proposto por Ichikawa (2002). Foram codificados os aspectos como seqüência de atividades realizadas por cada indivíduo, modo de viagem, período do dia em que cada viagem foi realizada e tempo de viagem. O minerador de dados usado neste trabalho foi Árvore de Decisão e Classificação, uma ferramenta de análise disponível no software S-Plus 2000. A análise baseou-se na pesquisa origem-destino realizada pelo METRÔ-SP na região metropolitana de São Paulo, por meio de entrevistas domiciliares, em 1987. Concluiu-se que variáveis socioeconômicas podem explicar o comportamento relacionado a viagens encadeadas, indicando que minerador de dados pode ter um papel importante na análise do comportamento relacionado às viagens encadeadas. / The main aim of this work is to analyze the behavior of homogeneous groups of individuals regarding the chained trips by using a data miner. Several aspects of chained trips were represented through the extension of the coding process initially proposed by Ichikawa (2002). Aspects such as sequence of activities performed by each individual, travel mode, period of the day in which each trip occurs, and travel time were coded. The data miner used in this work was Decision and Classification Tree, an analysis tool available in S-Plus 2000 software package. The analysis was based on the origin-destination home-interview survey carried out by METRÔ-SP in São Paulo metropolitan area, in 1987. The main finding is that the socioeconomic variables can explain the behavior related to the chained trips, indicating that data miner can play an important role in the analysis of the behavior related to the chained trips.

O objetivo principal deste trabalho é identificar se e como as áreas urbanas interferem nos padrões de viagens encadeadas dos viajantes urbanos. Para atingir os objetivos, as diferenças e similaridades notadas entre os principais grupos socioeconômicos das áreas urbanas em relação aos padrões de viagens encadeadas serão discutidas. O método para comparação dos comportamentos relacionados às viagens encadeadas baseia-se na compatibilização das variáveis das três áreas e posterior aplicação do minerador de dados denominado Árvore de Decisão e Classificação, disponível no pacote estatístico S-Plus 6.1. As viagens encadeadas foram representadas através da codificação inicialmente proposta por Ichikawa (2002) e ampliada por Pitombo (2003). Foram codificados os motivos, modos e período do dia em que cada viagem foi realizada. A análise foi baseada nas pesquisas origem-destino realizadas na região metropolitana de São Paulo pelo Metrô-SP, em 1997, na região metropolitana de Belém pela JICA/Governo do Estado do Pará, em 2000, e na cidade de Bauru pela EMDURB, em 1997. Concluiu-se que, em geral, o comportamento de viajantes urbanos são influenciados pelas políticas urbanas regionais, características socioeconômicas e espaciais de cada região. / The main aim of this work is to identify whether and how the urban areas interfere in the urban trips makers\'trip chaining pattern. For attaining the aims, the differences and similarities observed among the behaviour of trip makers belonging to the main socioeconomic groups living in the three urban areas will be discussed. The method to compare the behavior related to trip chaining is based on the compatibilization of the variables of three areas and subsequent application of the data miner named Decision and Classification Tree, available in the S-Plus 6.1 statistical package. The chained trips were coded by using the process initially proposed by Ichikawa (2002) and amplified later by Pitombo (2003). The trip purpose, travel mode and period of the day in which each trip occurs were coded. The analysis was based on the origin-destination home-interview surveys carried out in São Paulo Metropolitan Area by Metrô-SP, in 1997, Belém Metropolitan Area by JICA/Pará State Government, in 2000, and Bauru city by EMDURB, in 1997. The main finding is that urban trip makers\'behaviour are affected by regional urban policy, socioeconomic features and geographical characteristics of each area.

Gothenburg introduced a time-of-day dependent cordon-based congestion charging scheme in January 2013. This paper explores how the introduction of the Gothenburg congestion charging scheme has affected trip tour and trip chaining behavior, using panel surveys conducted in 2012 and 2013, before and after the Gothenburg congestion charging began. This study proposes a typology of trip tour and trip chaining behavior based on organization of trips. Further, the study develops a series of indicators to characterize trip chains and trip tours patterns. Descriptive analysis is used to compare travel patterns before and after congestion pricing at the daylevel, tour-level and stage-level. The analysis results show that car travelers not only suppress activities to a small extent but also tend to have simpler tour patterns after the congestion charges implementation. The adaptation patterns reduce charges paid to some extent. In general, the reorganization of activities taken from on the way from work/school to home contributes greatly to reducing the congestion charges paid. A linear model is also developed to identify the effects of socio-demographic factors and contextual factors on the amount of charges paid based on panel data.

O principal objetivo deste trabalho é analisar a aplicabilidade de um minerador de dados para obter relações entre padrões de viagens encadeadas e características sócio-econômicas de viajantes urbanos. Para representar as viagens encadeadas, as viagens correspondentes a cada indivíduo do banco de dados foram codificadas em termos de seqüência de letras que indicam uma ordem cronológica em que atividades são desenvolvidas. O minerador de dados utilizado neste trabalho é árvore de decisão e classificação, uma ferramenta de análise disponível no software S-Plus. A análise foi baseada na pesquisa origem-destino realizada pelo Metrô-SP na região metropolitana de São Paulo, por meio de entrevistas domiciliares, em 1987. Um dos importantes resultados é que indivíduos que têm atributos sócio-econômicos e de viagens similares não se comportam de maneira similar; pelo contrário, eles fazem diferentes padrões de viagens encadeadas, as quais podem ser descritas em termos de probabilidade ou freqüência associada a cada padrão. Portanto, o minerador de dados deve possuir a habilidade para representar essa distribuição. A consistência do resultado foi analisada comparando-os com alguns resultados encontrados na literatura referente a análise de viagem baseada em atividades. A principal conclusão é que árvore de decisão e classificação aplicada a dados individuais, contendo encadeamento de viagem codificado e atributos socioeconômicos e de viagem, permite extrair conhecimento e informações ocultas que ajudam a compreender o comportamento de viagem de viajantes urbanos. / The main aim of this work is to analyze the applicability of a data miner for obtaining relationships between trip-chaining patterns and urban trip-makers socioeconomic characteristics. In order to represent the trip-chains, trips corresponding to each individual in the data set were coded in terms of letters indicating a chronological order in which activities are performed. Data miner applied in this work is decision and classification tree, an analysis tool available in S-Plus software package. The analysis was based on the origin-destination home-interview survey carried out by Metrô-SP in São Paulo metropolitan area. One of the important findings is that individuals having similar socieconomic and trip attributes do not behave in a similar way; on the contrary, they make different trip-chaining patterns, which may be described in term of probability or frequency associated to each pattern. Therefore, the data miner should have ability to represent that distribution. The consistency of results was analyzed by comparing them with some results found in literature related to activity-based travel analysis. The main conclusion is that decision and classification tree applied to individual data, containing coded trip-chaining and socioeconomic and trip attributes, allows extracting hidden knowledge and information that help to understand the travel behaviour of urban trip-makers.

O principal objetivo deste trabalho é analisar a aplicabilidade de um minerador de dados para obter relações entre padrões de viagens encadeadas e características sócio-econômicas de viajantes urbanos. Para representar as viagens encadeadas, as viagens correspondentes a cada indivíduo do banco de dados foram codificadas em termos de seqüência de letras que indicam uma ordem cronológica em que atividades são desenvolvidas. O minerador de dados utilizado neste trabalho é árvore de decisão e classificação, uma ferramenta de análise disponível no software S-Plus. A análise foi baseada na pesquisa origem-destino realizada pelo Metrô-SP na região metropolitana de São Paulo, por meio de entrevistas domiciliares, em 1987. Um dos importantes resultados é que indivíduos que têm atributos sócio-econômicos e de viagens similares não se comportam de maneira similar; pelo contrário, eles fazem diferentes padrões de viagens encadeadas, as quais podem ser descritas em termos de probabilidade ou freqüência associada a cada padrão. Portanto, o minerador de dados deve possuir a habilidade para representar essa distribuição. A consistência do resultado foi analisada comparando-os com alguns resultados encontrados na literatura referente a análise de viagem baseada em atividades. A principal conclusão é que árvore de decisão e classificação aplicada a dados individuais, contendo encadeamento de viagem codificado e atributos socioeconômicos e de viagem, permite extrair conhecimento e informações ocultas que ajudam a compreender o comportamento de viagem de viajantes urbanos. / The main aim of this work is to analyze the applicability of a data miner for obtaining relationships between trip-chaining patterns and urban trip-makers socioeconomic characteristics. In order to represent the trip-chains, trips corresponding to each individual in the data set were coded in terms of letters indicating a chronological order in which activities are performed. Data miner applied in this work is decision and classification tree, an analysis tool available in S-Plus software package. The analysis was based on the origin-destination home-interview survey carried out by Metrô-SP in São Paulo metropolitan area. One of the important findings is that individuals having similar socieconomic and trip attributes do not behave in a similar way; on the contrary, they make different trip-chaining patterns, which may be described in term of probability or frequency associated to each pattern. Therefore, the data miner should have ability to represent that distribution. The consistency of results was analyzed by comparing them with some results found in literature related to activity-based travel analysis. The main conclusion is that decision and classification tree applied to individual data, containing coded trip-chaining and socioeconomic and trip attributes, allows extracting hidden knowledge and information that help to understand the travel behaviour of urban trip-makers.

In dieser Arbeit werden außerberufliche Tätigkeiten von Erwerbstätigen in ihrem Arbeitsortumfeld untersucht. Es wird erforscht, welche Aktivitäten Erwerbstätige dort koppeln. Als Einflussfaktoren werden die funktional-räumliche Ausstattung des Arbeitsortumfeldes, deren Wahrnehmung und Bewertung durch die Erwerbstätigen und Merkmale der beruflichen Tätigkeit, Verkehrsmittelwahl und soziodemographische Merkmale betrachtet. Nahmobilität im Arbeitsortumfeld wurde bislang in Deutschland noch nicht explizit untersucht. Damit wurden bisher aus theoretischer Sicht ein bedeutsamer Pol des Aktionsraumes von Personen sowie ein wesentlicher Ansatzpunkt zur planerischen Stärkung der Nahmobilität bzw. der Umsetzung des Leitbildes der Stadt der kurzen Wege vernachlässigt. Eine quantitative Befragung von Angehörigen der Humboldt-Universität zu Berlin (N = 565) zeigte die Bedeutung des Arbeitsortumfeldes für die Alltagsorganisation in den Bereichen Freizeit, Dienstleistungen und Einzelhandel auf. Zur Beschreibung des Kopplungsverhaltens dienen die Begriffe „Nutzerakzeptanz“, „objektives Nutzungsspektrum“ und „subjektives Nutzungsspektrum“. Es üben 96 % der Personen Aktivitäten im Arbeitsortumfeld aus (Nutzerakzeptanz). Sie konzentrieren ihre Nutzung meist auf wenige Gelegenheiten aus dem Spektrum aller vorhandenen Gelegenheiten (objektives Nutzungsspektrum). Neu eingeführt wird in der vorliegenden Studie das subjektive Nutzungsspektrum als Anteil der genutzten an den subjektiv bekannten Angeboten im Arbeitsortumfeld. Im Vergleich zum objektiven ist das subjektive Nutzungsspektrum deutlich größer. Es konnte ein deutlicher Zusammenhang der Nutzung von Angeboten im Arbeitsortumfeld mit der Stadtstruktur, mit der Verkehrsmittelwahl und mit soziodemographischen Merkmalen der Befragten aufgezeigt werden. Der Zusammenhang des Nutzungsverhaltens mit Merkmalen der Erwerbstätigkeit ist hingegen nicht eindeutig interpretierbar. / The present work investigates what non-work activities are trip chained by employees nearby their places of work. As influencing factors the facility mix close to the places of work, its perception and evaluation, occupational characteristics, mode of transport, and sociodemographic factors are taken into account. So far, in (German) research there is a strong tendency to focus on the residential area end of the trip when exploring short-distance mobility patterns. Thus, research left an important part of action space unattended and disregarded an aspect of land use that might be susceptible to successful planning control in order to promote short-distance mobility patterns. A quantitative survey among members of Humboldt-Universität zu Berlin (N = 565) revealed the importance of the proximity of the place of work for non-work activities in the fields of recreation, services and shopping. The utilisation of facilities is described by the terms “acceptance of facilities by users” (1; “Nutzerakzeptanz”), “objectively used share of facilities” (2; “objektives Nutzungsspektrum”) and “subjectively used share of facilities” (3; “subjektives Nutzungsspektrum”). 96 % of the respondents carry out activities nearby their place of work (1). In doing so, most people concentrate only on a few facilities out of the whole range of facilities offered (2). A new aspect in the present work is the focus on the “subjectively used share of facilities” which describes the portion of used facilities of all facilities known to a person. In comparison to the “objectively used share of facilities” the “subjectively used share of facilities” is bigger. An interrelationship of the utilisation of facilities with facility mix, perception and evaluation of the facilities, choice of transport mode, and sociodemographic characteristics, respectively, was found. The interrelation between the utilization of facilities and occupational characteristics is less clear.

Indian cities have been witnessing rapid transformation due to the synergistic effect of industrialisation, flourishing-economy, motorisation, population explosion, and migration. The alarming increase in travel demand as an after effect of the transformation, and the scarcity in transport infrastructures have exacerbated urban transport issues such as congestion, pollution, and inequity. Due to the escalating cost of transport infrastructure and the scarcity of resources such as space, there has been an increasing interest in promoting sustainable transportation policy measures for the optimum use of existing resources. Such policy measures mostly target the activitytravel behaviour of individuals to bring about desired changes in the transport sector. However, the responses of individuals to most of the measures are complex or unknown. The current ‘commute trip-based’ aggregate travel demand analysis strategy followed in most of the Indian cities is inadequate for providing basic inputs to understand the activity-travel behaviour of individuals under such policy interventions. Furthermore, the current analysis strategy also ignores the activitytravel behaviour of non-workers – who include homemakers, unemployed, and retired individuals – whose inclusion to transportation planning is relevant when the proposed policies are mostly ‘citizen-centric’. Analysis of activity-travel behaviour of non-workers provide important inputs to transportation planning as their activity-travel behaviour, and responses to transportation policies are different from that of workers. However, case studies exploring the activity-travel behaviour of non-workers from Indian cities are very limited. Appraising the practical importance of this subject, the current research undertakes a comprehensive analysis of the activity-travel behaviour of non-workers from a developing country’s context. To fulfil the goal, a series of empirical analysis are conducted on a primary activity-travel weekday survey data collected from Bangalore city. The analysis provides insightful findings and interpretations consistent with a developing country’s perspective. The day-planner format of time use diary, which was observed to have satisfactory performances in developed countries, is apparently have inferior performances in a developing country’s context. Further, the face-to-face method of survey administration is observed to have higher operating and economic efficiencies compared to the drop-off and pick-up method. The comprehensive analysis of activity-travel behaviour of non-workers indicate that comparing with their counterparts in the developed world (e.g. the U.S.), non-workers in Bangalore city are observed to have lower activity participation level (in terms of time allocation and number of stops), higher dependency on walking, lower trip chaining tendency, and a distinct time-of-day preference for departing to activity locations. On the other hand, the analysis shows similarities (mode use and trip chaining) and differences (time allocation and departure time choice) with the findings of the case studies from the developing world (e.g. China). Activity-travel behaviour of non-workers belonging to low-income households is characterised by lower activity participation level, higher dependency on sustainable transport modes, and lower trip chaining propensity, compared to other two income groups (middle and high-income groups). The research also suggests that built environment measures have their highest impacts on non-workers’ travel decisions related to shopping. Finally, the joint analysis of activity participation and travel behaviour of non-workers indicate that in-home maintenance activity duration drives the time allocation and travel behaviour of non-workers, and non-workers trade in-home discretionary activity duration with travel time. The joint analysis also shows that the time spent on children’s and elders’ activity is an important time allocation of its own. Keywords: Activity-travel behaviour, Non-worker, Time Use, Income Groups, India