Built environment,peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data

Commuting efficiency measures the impact of commuting on urban spatial and social environments. Urban policies aim to reduce commuting distances and improve commuting efficiency by supporting mixed land-use and job-housing balance. Many studies have addressed these issues by examining excess commuting at the aggregate level, and most aggregated measurements of excess commuting are based on home-to-work commuting flows between zones. However, residents' travel behaviour does not consist solely of rational attempts at minimizing commuting distances but is instead affected by commuting hours, the complexity of the commuting chain and the built environment. Thus, commuting efficiency must be studied at the individual or disaggregated levels. This paper examined individual commuting efficiency in suburban Beijing using a GPS-facilitated activity-travel survey and investigated the differences in commuting distance and route choice efficiency between morning and evening peaks. Notably, in so doing, we considered non-work stops, and also explored the impact of urban spatial factors – in both residential and working areas – on commuting efficiency using multilevel mixed effects generalized linear models. The findings suggest that there are significant differences in commuting distance and commuting efficiency between morning and evening peaks based on the nature of commutes. Residents working in city centres or with jobs near railway stations, with higher road network densities or with lower facility densities seem to be more adept at selecting optimal routes.     

Long-distance trips in a sparsely populated region: The impact of high-speed infrastructures

This paper aims to analyze the different territorial performance of two new high-speed transport infrastructures, a national motorway and a high-speed rail (HSR) line, with an emphasis on their different roles on long-distance trip making, in a peripheral and sparsely populated province of Spain, contributing to the existing limited research on the influence of high-speed transport infrastructures on urban structure and mobility of sparsely populated regions.The paper provides empirical evidence by means of a mobility survey. The analysis of modal split, travel frequencies, and travel purposes allows a better understanding of long-distance mobility patterns and establishes different travel profiles. The study of commuting and discretionary flows shows different levels and types of metropolitan integration depending on the type of connection and on local characteristics.     

Spatial and socio-demographic determinants of South East Queensland students’ school cycling

The low prevalence of Australian students’ utilitarian school cycling could be attributed to the varied and context specific demographic, socio-economic and spatial school travel mode choice determinants. Travel distance is universally important for school cycling and is reliant amongst related home and school spatial proximity factors on a student’s choice of schools. This paper, primarily based on school students’ travel data extracted from the 2009 South East Queensland Household Travel Survey (SEQHTS), examines comparative school cycling travel patterns, school catchment choices and the significant analytical determinants of cycling mode choices from within an urban regional Australian context. Students’ choice of a school external to that located within their designated State school catchment zone was associated with household attributes of parent/guardian employment location, number of income earners and ownership of private vehicles coupled with State school and catchment attributes. Noteworthy variations in school travel distances and modal splits were allied with school catchment choices. Adolescent male students from two parent households owning fewer than two cars and more than two bicycles, with parents/guardians commuting using non-motorised travel modes and resident in Census Collection Districts with conducive cycling environments, contributed largely to the one-way bi-directional primary and secondary school cycling mode shares. This prevalent student cyclist profile indicates the need for enhancements in student school cycling participation, through policies addressing both the spatial (built) and social environment which impact students’ personal and traffic safety coupled with utilitarian cycling image enhancements. Concerted efforts to bolster cycling amongst student segments with current low cycling participation inclusive of females, students from single parent households and those with adequate access to private motorised travel modes may be necessary to further enhance school cycling mode shares. The paper makes a case for individualised targeted travel interventions informed by segregated mode choice determinant analysis for respective primary and secondary school types and directions of school travel.     

Revealing intra-urban travel patterns and service ranges from taxi trajectories

As an important transport tool, taxi plays a significant role to meet travel demand in urban city. Understanding the travel patterns of taxis is important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of taxi trips to characterize travel patterns, while it may be more appropriate to explore taxi service strategies on seasonal, weekly or daily time scale. Therefore, intra-urban taxi mobility is investigated by examining taxi trajectory data that were collected in Harbin, China, while 12-week corresponding to 12-month is chosen as the sampling period in our study. The multivariate spatial point pattern analysis is firstly adopted to characterize and model the spatial dependence, and infer significant positive spatial relationships between the picked up points (PUPs) and the dropped off points (DOPs). Secondly, the points of interest (POIs) are identified from DOPs using the emerging hot spot detection technique, then the taxi services and movement patterns surrounding POIs are further examined in details. Moreover, our study builds on and extends the existing work to examine the statistical regularities of trip distances, and we also validate and quantify the impacts posed by airport trips on the distance distributions. Finally, the movement-based kernel density estimation (MKDE) method is proposed to estimate taxis' service ranges within three isopleth levels (50, 75 and 95%) between summer/weekday and winter/weekend from taxi driver's perspective, and season as well as temperature factors are identified as the significant effect within certain service range levels. These results are expected to enhance current urban mobility research and suggest some interesting avenues for future research.     

Impacts of urban sprawl and commuting: a modelling study for Italy

This paper aims to analyse empirically the intricate relationship between urban sprawl and commuting, a process that started a few decades ago in Italy. Using a mobility impact index based on commuting data for 1981 and 1991, we quantify the impact of commuting for seven major Italian urban areas, comprising in total 739 municipalities (communes). Our modelling experiment highlights the effect of sprawl at the commune level, while taking into account the variability of communes across geographical location and level of polycentrism. Causal relationships between spatial developments and explanatory factors related to changes in urban density are analysed using multivariate cross-section regression analysis and Causal Path Analysis (CPA). Our empirical results confirm the expectation that sprawl is accompanied by intensive travel movements and associated environmental effects.     

Key research themes on ICT and sustainable urban mobility

Abstract

Information and communication technologies (ICTs) are hypothesized to replace or change the use of the transport system by facilitating new or different activities. This article offers a review of more than 40 years of research regarding the relationship between ICTs and urban mobility. We discuss the expectations for the changes in travel demand, travel patterns, and the urban form as a result of the development and introduction of ICTs. Much of the interest in the relationships between ICTs and mobility is premised on the expectation of substitution effects, but empirical findings often suggest more complex effects than direct substitution. Although research on single types of travel activity may sometimes indicate simple substitution effects, examination of the broader impacts may also reveal travel generation effects as well. As such, ICTs do not simply substitute mobility patterns but change them. A growing body of research focuses on changing mobility patterns (in terms of time and space), changes in the experience of travel and changes in the perceptions of travel costs due to the interaction between old and new technologies for overcoming distance. ICTs are gradually becoming embedded within the transport system, enabling flexibility, multitasking, and an increase in human activities.     

The trilogy of distance, speed and time

Over the recent past there has been a dramatic increase in travel, mainly driven by the desire to move faster and over ever greater distances. This growth is unsustainable, and the continued growth in levels of mobility needs to be reassessed through substantially reducing the levels of consumption (energy and carbon) in transport. This means that travel activities should be based on shorter distances and slower speeds, with a more flexible interpretation of time constraints. Transport geographers should have a strong and instrumental role to play in this debate. This paper outlines the changing patterns of movement, before concentrating on urban areas where most daily travel takes place, and it examines the trilogy of distance, speed and time. The focus of the paper is on distance, and the role that land use planning and development, and technology can play in encouraging new forms of travel in cities, but there are strong implications on the ways in which speed and time are conceptualised. The conventional transport paradigm is heavily embedded in the belief that travel time needs to be minimised and consequently speeds need to be increased. The resulting impacts on travel distances have not been part of that debate, but reducing travel distances is central to sustainable transport.     

Urban structure,commuting burden,and employment status of labour forces in an Australian city

Understanding the productivity effects of worker commuting burdens is essential for appraisals of urban planning and investment strategies designed to improve urban productivity. However, the extant urban planning literature lacks systematic analysis of the influence of commuting costs on labour mobility, employment engagement, and productivity. This paper provides the first ever detailed analysis of mobility and commuting burdens for workers in a range of industries and occupational groups in Melbourne, Australia. Linking commuting burdens and measures of employment status in urban areas, this paper finds that the labour force in areas experiencing high commuting burdens exhibit lower levels of engagement with job markets. This research further reveals important variations in such relationships across diverse industry and occupation groups. The results provide urban policy makers with better information about urban transport and employment patterns, thus enabling them to investigate alternative approaches to investing in housing and transport infrastructure to reduce worker commuting burdens and improve economic performance.     

Unveiling large-scale commuting patterns based on mobile phone cellular network data

In this study, with Estonia as an example,we established an approach based on Hidden Markov Model to extract large-scale commuting patterns at different geographical levels using a massive amount of mobile phone cellular network data, which is referred to as Call detail record (CDR). The proposed model is designed for reconstructing and transforming the trajectories extracted from the CDR data. This step allowed us to perform origin-destination matrix extraction among different geographical levels, which helped in depicting the commuting patterns. Besides, we introduced different techniques for analyzing the commuting at the urban level. Our results unveiled that there is great potential behind mobile data of the cellular networks after transforming it into meaningful mobility patterns. That can easily be used for understanding urban dynamics, large-scale daily commuting and mobility. The aggressive development and growth of ubiquitous mobile sensing have generated valuable data that can be used with our approach for providing answers and solutions to the growing problems of transportation, urbanization and sustainability.     

Assessing the role of the built environment and sociodemographic characteristics on walking travel distances in Bogotá

Planning for more sustainable mobility is an important goal for public authorities worldwide. Setting better conditions for pedestrians and cyclists has been related to many social benefits, such as less pollution and congestion. Local authorities, aware of the relationship between transport and land-use, are adopting planning tools to analyze growth in cities and their impacts using multiple indicators. This paper develops an econometric trip length model that correlates socioeconomic characteristics and built environment conditions with walking travel distances in the city of Bogotá, Colombia. A log-linear regression model was estimated using information for 2015 of Bogotá's household travel survey, along with data of employment and population by block obtained from official sources. The built environment component of the model serves to evaluate the effect of land-use patterns. A proof of concept was developed using land-use information extracted from a Cellular Automata Land-Use model calibrated for the city. From its results, some factors of the built environment were estimated and two scenarios were tested in this study. One depicts the average walking distance for households surveyed in 2015, and the other takes a simulation of land-use policy in developing a new urban area as an input. The results indicate that people living in areas were the land-use mix and job/population ratio are low, tend to have longer walking distances, suggesting the need to implement special policies that reallocate some activities and encourage higher land-use mix in the urban periphery where low-income households tend to be located. The proposed method can identify the impact of land-use policies in the distances traveled by walking, facilitating the impact assessment of land-use regulations.     

Analysis of active school transportation in hilly urban environments: A case study of Dresden

This paper analyses the way students travel to school and examines the influence of environmental conditions on travel patterns. More specifically, it studies how topographic changes affect the likelihood of choosing cycling as a transport mode. We use mode choice data on students' home-to-school commuting trips from a previous study by Müller et al. (2008). The results show that models perform better when they account for the topographic conditions of the urban environment. We included this information in the model by introducing the “energy exerted” variable, which significantly improves the model and the results. The implications of this study are manifold; it guides the consolidation or expansion of school-based transportation network planning in Germany and prompts further analysis of active transportation systems, such as bike, pedelec and e-bike sharing systems. Overall, transportation policy should seek to foster active transportation, as it provides the greatest benefits for society and has a direct impact on people's well-being, while notably reducing the negative environmental and socioeconomic impacts of motorized transport.     

Commuting patterns of employees in the Information Technology and traditional manufacturing sectors of Bangalore, India

Rapid growth of the Information Technology (IT) sector in Bangalore, India, has transformed the city’s urban-industrial landscape since the liberalization of India's economy in 1991. The city's IT sector is closely integrated with a global system of production and caters largely to a global clientele. Apart from the impact of these developments on urban form, there are indications that they are causing uneven growth patterns and socio-economic polarization, which has resulted in different travel patterns in the work force. This paper compares the commuting patterns of employees in two types of firms, an IT multinational corporation and a traditional public-sector-unit (PSU), using data from a survey. Regression models show that there is a significant increase in travel cost as income rises for a sample of employees of the IT sector, even though travel distance is not influenced by income. The reverse holds true for a sample of employees of the PSU—rising income significantly increases distance though income does not affect travel cost. Behavioral choice models also show that with increasing income IT employees are more likely to choose two-wheelers and cars for commuting while PSU employees are more likely to choose public buses or walk to work. The paper suggests that Bangalore's services-oriented IT economy is magnifying differences in work commuting patterns relative to those in the traditional manufacturing economy. The IT economy is also transforming travel behavior in terms of work travel mode choices among socio-economic groups.     

Trends in regional jobs-housing proximity based on the minimum commute: The case of Belgium

This paper investigates recent trends in the efficiency of the Belgian territorial structure in terms of commuting, at both the urban and regional scales. The minimum commute distance (MCD) and excess rate (ER) are used to compare observed home-to-work trip lengths with an “optimal” alternative commuter pattern in which the sum of the distance traveled by the working population is minimized. The MCD is a proximity indicator that measures the spatial match between the labor market and the housing stock, which can also be regarded as an interesting indicator of potential border effects on travel behavior, especially in the inter-regional context of Belgium. An MCD calculation requires an origin–destination (OD) matrix and a distance matrix. In our Belgian case study, we employ a recent OD matrix (2010) originating from Social Security (ONSS) data. We compare this matrix with data from the 2001 and 1991 census surveys. In addition to identifying trends in jobs-housing proximity, the article assesses methodological implications regarding geographical scale arising from the use of the two data sources mentioned. Based on the available data, it was found that average actual commuting distance increased over both periods studied, while in general, growth rates of MCD are considerably lower than growth rates of the actual commuting distance. This indicates that the spatial proximity between the labor market and the housing stock in Belgium has declined over all periods studied, although this loss of spatial proximity only explains a small part of the increase of the actual commuting distance. Furthermore, we found that the comparison of excess commuting metrics between regions and time periods sets high standards on data requirements, in which uniformity in data collection and spatial level of aggregation is of great importance. Finally, as the main contribution of this study, the results demonstrate, through a statistical approach, that municipalities that are experiencing a higher-than-average increase in MCD and ER in one of the considered time frames are more likely to continue to exhibit a higher-than-average increase in the subsequent period. Therefore, the observed trends appear to be consistent over time.     

Comparison of efficiency between public and private transport modes using excess commuting: An experience in Dar es Salaam

The excess commuting concept is well-known in developed countries. Since the introduction of the concept in the developed countries, the excess commuting framework has been used to derive a set of benchmarks and indices for the analyses of spatial mismatch, jobs-housing balance, and commuting efficiency in urban regions. However, there are very few studies which have examined excess commuting parameters in relation to mode of transport in the current excess commuting literature. Additionally, very few studies on excess commuting have been undertaken in developing countries with no evidence on any study in African cities. This paper attempts to add to the excess commuting literature by examining and comparing excess commuting parameters between public and private transport modes in Dar es Salaam city. The study investigated the effects of land use patterns in the year 2007 (the base year) and the projected land uses in the year 2030 on excess commuting parameters. The results suggest that public transport in Dar es Salaam is very good in terms of providing excellent options to get everywhere in the city as it connects homes and jobs as well as private transport. This is very different from cities in the more developed world, especially in the USA, where public transport is less effective at connecting origins and destinations. It was also found that the land use scenario in the year 2030 encourages a travel pattern that increases the actual average travel distance.     

Changing student mobility behaviour under financial crisis: Lessons from a case study in the Oporto University

This paper explores how the commuting patterns of university students have changed in the face of the financial crisis that has affected Portugal in 2008. In this research, we focus on the mobility behaviour of students from the Faculty of Engineering of Oporto University (FEUP). Based on two similar surveys carried out in 2006 and 2012, i.e. before and during times of financial crisis, and macrosocial data from the Portuguese Census and from the metropolitan public transport system, we provide detailed accounts of commuting patterns, including main motivations, barriers, and discuss the influence of considering different scales of analysis of the built-environment. The results show a general trend to reduce the students' costs of commuting by living with their families and using more often public transports. Our results also suggest an increasing level of inequality towards mobility, reinforced by austerity policies, which may lead to undesirable travel behaviours in the future. Although the overall evolution of students' travel behaviour points towards greater sustainability, the identified changes also suggest social-spatial injustices.     

The impact of Covid-19 on children's active travel to school in Vietnam

This is among the first studies to provide empirical evidence on active school travel rates and determinants before and after the first Covid-19 lockdown in spring 2020. We have collected and analyzed primary survey data on the school travel patterns of 472 school-age children in Hanoi, Vietnam. The findings show that the Covid-19 pandemic has been quite detrimental: once schools reopened, the prevalence of active school travel decreased from 53% to less than 31%. Where parents, especially mothers, did not face barriers to motorized travel, they assumed the role of chauffeur. Parents who were more concerned about community infections were more motivated to shift children to motorized modes. Walking was more affected than cycling because it was seen as more likely to lead to physical contact and virus transmission. Active school travel dropped more steeply in urban districts (as opposed to poorer, non-urban districts) and in those areas where home-school distances were the largest. It appears that the most common perceptions around barriers to active school travel have been exacerbated during the pandemic as parents and children adapt to “the new normal”.     

Identification of land-use characteristics using bicycle sharing data: A deep learning approach

Extensive research has shown that urban land-use characteristics, including resident, work, consumption, transit, etc., are significantly interrelated with travel behaviors and travel demands. Many research efforts have been made to evaluate the impact of land use planning or policies on travel behavior, however, few studies are able to quantitatively measure the land-use characteristics based on the data of travel behaviors or travel demand. In this paper, a new hybrid model that combines time series feature extraction and deep neural network is proposed to identify regional land use characteristics and quantify land use intensity using ridership data of bicycle sharing. This method consists of four main parts: (i) A set of land-use characteristic labels are evaluated based on planning and Geographic Information System (GIS) data. (ii) An ensemble clustering method is used to determine the segmentation points of ridership time series. (iii) The statistical characteristics of the segmented time series are extracted and used as input to the neural network. (iv) A deep neural network is established and trained based on the processed ridership features and land-use labels. In terms of data collection, ridership data of the bicycle-sharing parking spots and land-use planning data are obtained from bicycle-sharing system and planning department in San Francisco Bay Area, California U.S.A., respectively. The test results show that this approach has high accuracy for identifying land-use characteristics based on several standard evaluation measures and that the identification distribution can be well explained. The extension results further prove that the model can be applied to effectively analyze the main land-use characteristics of the region although the identification results may become unstable after 3–4 months.