Gender differentials in travel pattern – The case of a mid-sized city,Rajkot, India

This paper is at the conjunction of arguments for gender equity in transport services on one hand and need to move towards low carbon transport on the other in a developing country city. The case study city, Rajkot, a mid-sized Indian city with mixed land use and limited public transport at the time of this study, has short trip lengths and low trip rates. But, even in this city there is gender disparity in travel pattern. Thus, trip rates and trip lengths of women in the city in each of the income group are lower than that of their male counter parts. With the increase in income, both, the trip rates and lengths increase, but, the increase is higher for men than for women. While the large proportions of women in each income group walk, that among the lowest income group walking is the predominant mode, as they are ‘no-choice’ or ‘forced’ walkers. With the increase in household income, women tend to shift to para-transit and men to personal motorized transport. If sustainability arguments or climate policies are to target retaining the current low ecological footprint of the women as one of the strategies, it needs to cater to expansion of their mobility while improving infrastructure to support the same.     

Trip chaining as a barrier to the propensity to use public transport

Trip chaining is a growing phenomenon in travel and activity behaviour. Individuals increasingly seek out opportunities to minimise the amount of travel required as part of activity fulfilment, given the competing demands on time budgets and their valuation of travel time savings. This search for ways of fulfilling (more) activities with less travel input has produced a number of responses, one of which is trip chaining. A particularly important policy implication of trip chaining is the potential barrier it creates in attracting car users to switch to public transport. This paper seeks to improve our understanding of trip chaining as a barrier to public transport use. A series of discrete choice models are estimated to identify the role that socio-economic and demographic characteristics of households have on the propensity to undertake trip chains of varying degrees of simplicity/complexity that involve use of the car or public transport with an embedded commuting or non-commuting primary purpose. Multinomial logit, nested logit and random parameter logit models are developed and contrasted to establish the gains in relaxing the strict conditions of the multinomial logit model.     

Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Activity–travel behaviour of non-workers from Bangalore City in India

This paper presents exploratory and statistical analyses of the activity–travel behaviour of non-workers in Bangalore city in India. The study summarises the socio-demographic characteristics as well as the activity–travel behaviour of non-workers using a primary activity–travel survey data collected by the authors. Where possible, the research also compares the analysis findings with the case studies on activity–travel behaviour of non-workers, carried out in developed and developing countries. This gives an opportunity to understand the differences/similarities in the activity–travel behaviour of non-workers across diverse socio-cultural settings. The preliminary exploratory analysis shed light on the differences in activity participation, trip chaining, time-of-day preference for trip departure, and mode use behaviour of non-workers in Bangalore city. Statistical models were developed for investigating the effects of individual and household socio-demographics, land use parameters, and travel context attributes on activity participation, trip chaining, time-of-day choice, and mode choice decisions of non-workers. A few important results of the analysis are the influence of viewing television at home on out-of-home activity participation and trip-chaining behaviour, and the impact of in-home maintenance activity duration on time-of-day choice. Further, based on the findings of the initial analyses, an attempt has been made in this study to develop an integrated model that links time allocation, time-of-day choice, and trip chaining behaviour of non-workers. The study also discusses the implications of the research findings for transportation planning and policy for Bangalore city.     

Trip assignment to radial major roads

The problem of flow-dependent trip assignment is considered for a city with a small number of radial major roads. CBD-based work trips are assigned to these radial major roads on the basis that each commuter seeks to minimise his individual travel time. A system of differential equations is derived for the spatial pattern of trip assignment in a model city with a continuous distribution of home locations and a ring-radial road network. This system is then solved for the special case of a uniform distribution of home locations.     

Alternative systems for urban transport in India

This paper is in the context of studying alternative systems of urban transport in India to determine the costs and performance not only for public transport systems but also for the total transport scenario (i.e. for all vehicles) such that the economic costs are inclusive of costs of time (conservatively), accidents and pollution. In view of inherent deficiencies and delays associated with a traditional transport planning process and its implementation, the paper develops quick response land-use transport planning models for Indian cities to enable integrated, cost-efficient strategies to be evolved, recognizing that urban transport is a function of urban size, form, structure, socio-economic base, etc. A simple statistically significant demand model identified from a basis of appropriate data represents the recommended demand model for Indian cities. This model can be then conveniently used to project trip volume for any Indian city in a future year. A simple gravity model is used to generate the trip assignment for hypothesized city sizes, forms and structures. The results provide a fairly reasonable approximation for the major corridor trip volumes and lengths in the context of the transport requirement for the metropolitan cities in India in 2001 and 2011 A.D. The GOI Study Group arising from the investigations reported in this paper and the discounted cash-flow method of analysis made clear overall recommendations in February 1987 for cities of various populations.     

Travel demand (modal split) estimation by hierarchical measurement

This paper develops a procedure for travel demand estimation via the Saaty method of Analytic Hierarchy. A stratification of the travel demand by trip-making and trip attributes has been represented more inclusively in a hierarchy system. Various elements and dimensions of the hierarchy have been hypothesized as different levels of decisions made by trip-makers. The elements contained in a set of specified matrices of travel attributes have been weighed utilizing a ratio scale, in a process of mapping transportation systems (modal) attributes with the characteristic trip-making behavior in a hierarchical demand structure. The principal output of this procedure is an estimate of the trip distribution by mode, or modal split. The estimate closely approximates the observed modal split pattern for the inter city travel problem simulated. This procedure is proposed for travel demand forecasting and planning.     

Optimal cordon pricing in a non-monocentric city

This paper examines the effect of cordon pricing based on an urban spatial model of a non-monocentric city where trips may occur between any pair of locations in the city. The model describes the spatial distribution of trip demand and traffic congestion under alternative pricing schemes. We evaluate the efficiency of resource allocation by comparing three schemes: no-toll equilibrium, first-best optimum, and optimal cordon pricing. Optimal cordon pricing is defined as a combination of cordon location and toll level that maximizes the social surplus in a city. Simulations show that cordon pricing is not always effective for congestion management: cordon pricing tends to be effective as the urban structure is more monocentric.     

Trip distribution for limited destinations: a case study for grocery shopping trips in the Netherlands

In this paper, we introduce a new trip distribution model for destinations that are not homogeneously distributed. The model is a gravity model in which the spatial configuration of destinations is incorporated in the modeling process. The performance was tested on a survey with reported grocery shopping trips in the Dutch city of Almelo. The results show that the new model outperforms the traditional gravity model. It is also superior to the intervening opportunities model, because the distribution can be described as a function of travel costs, without increasing the computational time. In this study, the distribution was described by a simple function of Euclidean distance, which provides a good fit to the survey data. The slope of the distribution is quite steep. This shows that most trips are made to nearby supermarkets. However, a significant fraction of trips, mainly made by car, still goes to supermarkets further away. We argue that modeling of these trips by the new method will improve traffic flow predictions.     

Could you also have made this trip by another mode? An investigation of perceived travel possibilities of car and train travellers on the main travel corridors to the city of Amsterdam,The Netherlands

We investigated perceived travel possibilities (or subjective choice-sets, consideration-sets) of car and train travellers on the main corridors to the city of Amsterdam, The Netherlands, and associations with traveller and trip characteristics. We conducted secondary analysis on a survey sample consisting of 7950 train and 19,232 car travellers. Forty-five percent of train travellers had a car in their objective choice-set, 27% of them would however never use it for this trip. Trip destination city centre, trip purpose, paying for the trip, public transport commitment, traffic congestion and parking problems were associated with consideration of car as alternative. Forty-two percent of car travellers had public transport in their subjective choice-set. The ratio between perceived public transport and objective car travel time stood out as determinant of consideration-sets, next to destination city centre, trip purpose, travel time and private versus company car ownership. On average, car travellers’ perceptions of public transport travel time exceeded objective values by 46%. We estimated that if perceptions would be more accurate, two out of three car travellers that currently do not see public transport as an alternative would include it in their choice-set, and use it from time to time. This effect has strong theoretical and policy implications.     

Analysis of the optimal length of road expansion – A case study of the Taipei metropolitan area

This study explores the optimal investment in the length of an expanded section of road to mitigate the congestion on a transportation corridor. It is assumed that one end of the road is in the central business district (CBD) and that the households are uniformly distributed along the road. Each individual makes trips from his/her residence to the CBD. Trip demand is elastic and depends on the cost of the trip (including congestion costs). During the first stage, the government determines the length of the expanded section given the width of that section. In the second stage, road users determine their trip demands by taking into consideration the trip cost function. In the process of solving this problem, the equilibrium traffic volume is first solved using differential equations. The optimal length of the expanded section is then solved by maximizing the social welfare. The analysis is then applied to the case of the Tucheng city – Banciao city – Taipei CBD corridor in the Taipei metropolitan area. The scheme of road expansion without tolling performs closely to the first-best scheme for the case of a high potential demand. This study’s approach can serve as valuable reference for city planners engaged in road planning in a transportation corridor between the CBD and satellite cities in a metropolitan area.     

A probabilistic model for the behaviour of traffic at a roundabout

A discrete-time, Markov chain model is proposed to describe the behaviour of traffic travelling on a single-lane roundabout and queueing on approach roads to enter the roundabout. A general origin-destination matrix is allowed for trip ends, there is an arbitrary number of approach roads and there is room for a general number of vehicles on each weaving section. Attention is given to the equilibrium régime at an approach subject to heavy traffic conditions. It is shown that for such an approach the moments of the distribution of the length of the queue of waiting vehicles may be found by a heavy traffic approximation.     

Accommodating user preferences in ad hoc shared ride trip planning using GIS

Ad hoc shared ride trip planning (SRTP) utilizes mobile devices, geo-sensors and wireless networks to match on-the-fly individual travel demand with transport supply. It represents one of many alternatives to single occupancy vehicle use. This paper outlines a SRTP approach via a two-phase algorithm based on user preferences in a time-dependent routing. Whereas current algorithms use minimization of travel time as the only optimization criterion in trip planning, in the framework presented here, the user can specify multiple trip preferences including travel time, walking time, number of transfers between cars and trip length. Various scenarios are simulated in the city of Tehran (Iran) to demonstrate how preference settings affect the routes of ad hoc shared journeys.     

Trip characteristics of selected israeli cities

Over the last 15 years travel patterns were investigated in 15 urban settlements in Israel. The results indicate an unusual combination of high trip generation by dwelling unit and low motorization rates.The diversity of socio-economic characteristics of population groups, as well as that of city size distribution, are reflected both in motorization rates and in trip generation.     

A zonal inference model based on observed smart-card transactions for Santiago de Chile

The collection of origin–destination data for a city is an important but often costly task. This way, there is a need to develop more efficient and inexpensive methods of collecting information about citizens’ travel patterns. In this line, this paper presents a generic methodology that allows to infer the origin and destination zones for an observed trip between two public transport stops (i.e., bus stops or metro stations) using socio-economic, land use, and network information. The proposed zonal inference model follows a disaggregated Logit approach including size variables. The model enables the estimation of a zonal origin–destination matrix for a city, if trip information passively collected by a smart-card payment system is available (in form of a stop-to-stop matrix). The methodology is applied to the Santiago de Chile’s morning peak period, with the purpose of serving as input for a public transport planning computational tool. To estimate the model, information was gathered from different sources and processed into a unified framework; data included a survey conducted at public transport stops, land use information, and a stop-to-stop trip matrix. Additionally, a zonal system with 1176 zones was constructed for the city, including the definition of its access links and associated distances. Our results shows that, ceteris paribus, zones with high numbers of housing units have higher probabilities of being the origin of a morning peak trip. Likewise, health facilities, educational, residential, commercial, and offices centres have significant attraction powers during this period. In this sense, our model manages to capture the expected effects of land use on trip generation and attraction. This study has numerous policy implications, as the information obtained can be used to predict the impacts of changes in the public transport network (such as extending routes, relocating their stops, designing new routes or changing the fare structure). Further research is needed to improve the zonal inference formulation and origin–destination matrix estimation, mainly by including better cost measures, and dealing with survey and data limitations.     

Zonal centrality measures and the neighborhood effect

The goal of this study is to develop a robust methodology for computing zone centrality measures in an urban area. Centrality refers to the relative importance of a zone in terms of network efficiency and utility for both transportation and urban study. Centrality indices that were developed to describe human relationships in the field of structural sociology were adopted. It is important to accommodate the neighborhood effect in dealing with centrality. The neighborhood effect describes the phenomenon whereby the attractiveness of a specific zone is affected by its neighbor zones. Kernel functions were employed to accommodate the neighborhood effect. The optimal bandwidth parameters were derived indirectly within the framework of trip attraction estimation under the assumption that the trip attraction of a zone is influenced by the integrated centrality, which includes the neighborhood effect. The well-known estimation tool of maximum likelihood estimation (MLE) was adopted to find the optimal bandwidth. As a byproduct of accommodating the neighborhood effect in centralities, a considerable advantage of the present study is an enhancement of the performance of trip attraction model. Another meaningful contribution of this study is a solution to the question of an acceptable delineation of the two city centers in Seoul. The boundaries of the two city centers were derived based on both the kernel function and its bandwidth.     

Comparing decision tree algorithms to estimate intercity trip distribution

Traditional trip distribution models usually ignore the fact that destination choices are made individually in addition to aggregated factors, such as employment and average travel costs. This paper proposes a disaggregated analysis of destination choices for intercity trips, taking into account aggregated characteristics of the origin city, an impedance measurement and disaggregated variables related to the individual, by applying nonparametric Decision Tree (DT) algorithms. Furthermore, each algorithm’s performance is compared with traditional gravity models estimated from a stepwise procedure (1) and a doubly constrained procedure (2). The analysis was based on a dataset from the 2012 Origin-Destination Survey carried out in Bahia, Brazil. The final selected variables to describe the destination choices were population of the origin city, GDP of the origin city and travel distances at an aggregated level, as well as the variables: age, occupation, level of education, income (monthly), number of cars per household and gender at a disaggregated one. The comparison of the DT models with gravity models demonstrated that the former models provided better accuracy when predicting the destination choices (trip length distribution, goodness-of-fit measures and qualitative perspective). The main conclusion is that Decision Tree algorithms can be applied to distribution modeling to improve traditional trip distribution approaches by assimilating the effect of disaggregated variables.     

The rider's impression of a simulated trip by PRT

The potential user interest in PRT's and the conditions for their use were studied. As users are unable to express certain opinions about technology they don't know, assessment studies must be close to real life. One way to getting close to reality is through studies in Virtual Reality (VR). Passenger encounters with PRT was studied by in-depth interviews directly after a VR-simulated trip in a real vehicle. The aims of using VR-technology seems to have been achieved. Many of the subjects had the impression of a real trip, some of them also of having travelled high above ground. All subjects were in favour of PRT and thought they would utilize it. They had confidence in the automatic control devices, although they wanted more information and better design of the safety system. The greatest conflict was the encroachment on the cityscape. Many of the subjects did not accept the impact of the guideways on the old city environment. However these views contrast with the desired accessibility.     

Structural equation approach to investigate trip-chaining and mode choice relationships in the context of developing countries

This paper investigates empirical relationships between trip chain type and mode class choice for developing countries. To formulate these two sets of decisions, four empirical models are developed using structural equation modeling (SEM). Those models are calibrated using one-month travel diary data collected in Dhaka city. SEM correlates the observed variables and identifies their relationship with trip-chaining type utility and mode class choice utility. The fitted models are selected based on statistical results and similarity with the real-life situation. Direct relationships between trip-chaining and mode choice utilities are found insignificant. However, several socio-demographic factors influence both simultaneously. Consequently, it is essential to consider mode class choice concurrently for modeling trip chains. This study also investigates the influencing factors for work-based and non-work-based trip chains separately and effects of road users’ heterogeneity. The research results can be utilized to perceive trip chain-mode choice patterns for developing countries.     

The geographical stability of a typical trip production model: Applications of national and local data in four urban areas

Estimates of the numbers of trips likely to be made by individuals and of the modes of transport that will be available to them for those trips are provided by the trip production model. The objective of the work described in this paper was to investigate the geographical stability of the trip production model by comparing the numbers of trips estimated by the model when using national rather than local data. The 1972/3 National Travel Survey was used as the national data. Household interview survey data from the transportation studies of Lincoln, Sheffield/Rotherham, South East Dorset and Bristol were the local data sources. Three home based trip purposes are modelled; 24 hour work, 24 hour shop, 24 hour other.The models calibrated from national and local data perform similarly provided both operate with local trip rates. The car ownership sub-model with national parameters produces similar forecasts to the models with local parameters. There are probably real differences in household trip rates for some trip purposes between urban areas.