Auckland Transport Research Articles

Deep Learning Based LSTM Model for Predicting the Number of Passengers for Public Transport Bus Operators

The bus public transportation system has low reliability and ability to predict the number of passengers. The accuracy of predicting the number of passengers by public transport bus operators is still weak, which results in failure to implement solutions by operators. A prediction model with LSTM based on deep learning is proposed to predict passengers for 4 bus public transportation operators (Go Bus, New Zealand Bus, Pavlovich, and Ritchies) which are evaluated by MSLE, MAPE, and SMAPE with variations in epoch, batch size, and neurons. The dataset is a CSV performance report on Auckland Transport (AT) New Zealand metro patronage buses (01/01/2019-07/31/2023). The best prediction model was obtained from the lowest evaluation value and relatively fast time at variations of epoch 60, batch size 16, and neurons 32. The prediction results on training and testing data improved with the suitability of the model tuning. The proposed prediction model performs predictions 12 months later for 4 predictions simultaneously with predicted fluctuations occurring simultaneously. Strong negative correlation on New Zealand Bus-Pavlovich, strong positive correlation on Go Bus with Ritchies and Pavlovich. Predictions that are less closely related and dependent are New Zealand Bus against Go Bus, Pavlovich, and Ritchies. The proposed prediction modeling can be used as a basis for creating operator policies and strategies to deal with passenger fluctuations and for the development of new prediction models.

COVID-19 and Public Transport in Auckland, New Zealand: Investigating Vulnerable Population Groups’ Ridership Behavior

Public transit ridership was severely affected during the COVID-19 pandemic in 2020 and the effects have continued since. The present study examines changes to ridership immediately post-pandemic in 2021. Research investigating the effects of COVID-19 on disadvantaged population groups is limited and the present study addresses this knowledge gap. Ridership of socially-disadvantaged groups such as low-income, female, and ethnic minority people is examined using order logit regression models. The study uses data from an online travel survey conducted in Auckland, New Zealand, immediately after all COVID-19-related restrictions were lifted. This allowed the collection of revealed preference data for the post-pandemic period. The regression models included the effects of socio-demographic characteristics of individual riders, travel attributes, and built environment factors. Findings suggest that those with lower income and from an ethnic minority group are likely to continue using transit frequently post-pandemic. Younger riders from the ethnic minority group are less likely to use transit frequently, while pre-COVID-19 they were more likely. Access to transit stops near home and work are significant factors for the ethnic minority group. Higher land use mix near the residence and work locations are found to induce more transit trips for all. It is critical for transit agencies to understand how the usage has evolved post-pandemic. These findings highlight the importance of considering the effects of the pandemic on different disadvantaged groups. Public transport service providers are encouraged to consider equity as they develop strategies to improve transit ridership.

Auckland Transport’s Mass Action Pedestrian Improvement Programme

Auckland's road safety performance deteriorated significantly with death and serious injury crashes increasing by more than 70% between 2014-2017 compared to the previous five years. A fifth of all pedestrian related crashes in Auckland occurred at existing zebra crossings. In response, the Mass Action Pedestrian Improvement Programme (MAPI) delivered 37 upgrades of existing at grade crossings to raised zebra crossings over 2018/19 financial year and since this time, Auckland Transport have upgraded more than 100 crossings across the network. This paper discusses the research and evaluation that were undertaken to inform the design and implementation of MAPI and to determine safety outcomes and impacts. Key learnings from the programme and the challenge of balancing safety benefits, community acceptance, and the efficient operation of the network, are discussed.

Efficient Network Selection Using Multi-Depot Routing Problem for Smart Cities

Smart cities make use of a variety of smart technology to improve societies in better ways. Such intelligent technologies, on the other hand, pose significant concerns in terms of power usage and emission of carbons. The suggested study is focused on technological networks for big data-driven systems. With the support of software-defined technologies, a transportation-aided multicast routing system is suggested. By using public transportation as another communication platform in a smart city, network communication is enhanced. The primary objective is to use as little energy as possible while delivering as much data as possible. The Attribute Decision Making with Capacitated Vehicle (CV) Routing Problem (RP) and Half Open Multi-Depot Heterogeneous Vehicle Routing Problem is used in the proposed research. For the optimum network selection, a Multi-Attribute Decision Making (MADM) method is utilized. For the sake of reducing energy usage, the Capacitated Vehicle Routing Problem (CVRP) is employed. To reduce the transportation cost and risk, Half Open Multi-Depot Heterogeneous Vehicle Routing Problem is used. Moreover, a mixed-integer programming approach is used to deal with the problem. To produce Pareto optimal solutions, an intelligent algorithm based on the epsilon constraint approach and genetic algorithm is created. A scenario of Auckland Transport is being used to validate the concept of offloading the information onto the buses for energy-efficient and delay-tolerant data transfer. Therefore the experiments have demonstrated that the buses may be used effectively to carry out the data by customer requests while using 30% of less energy than the other systems.

Multi-Attribute Decision Making for Energy-Efficient Public Transport Network Selection in Smart Cities

Smart cities use many smart devices to facilitate the well-being of society by different means. However, these smart devices create great challenges, such as energy consumption and carbon emissions. The proposed research lies in communication technologies to deal with big data-driven applications. Aiming at multiple sources of big data in a smart city, we propose a public transport-assisted data-dissemination system to utilize public transport as another communication medium, along with other networks, with the help of software-defined technology. Our main objective is to minimize energy consumption with the maximum delivery of data. A multi-attribute decision-making strategy is adopted for the selction of the best network among wired, wireless, and public transport networks, based upon users’ requirements and different services. Once public transport is selected as the best network, the Capacitated Vehicle Routing Problem (CVRP) will be implemented to offload data onto buses as per the maximum capacity of buses. For validation, the case of Auckland Transport is used to offload data onto buses for energy-efficient delay-tolerant data transmission. Experimental results show that buses can be utilized efficiently to deliver data as per their demands and consume 33% less energy in comparison to other networks.

Clearing the path to transcend barriers to walking: Analysis of associations between perceptions and walking behaviour

Walkability is much studied, but the relative importance of perceptions and motivations is still not consensual. This study took a holistic approach to examine the comparative importance of a range of possible perceptions, motivations and individual characteristics on walking levels.Data from Auckland Transport's Active Modes online survey (AT survey, N = 4,114) captured environmental perceptions and travel behaviour. Machine learning (gradient boosting) was used to predict walking levels from perceptual data and individual characteristics and determine the relative importance of each variable. Strong predictors of walking included the use of public transport, walking perceived as saving money and avoiding parking hassle, age group, and overall satisfaction with walking. Surprisingly, the importance of expected dimensions such as perceived availability of destinations or internal motivations was null in the general model.These findings suggest a more holistic view of walking behaviour is needed, one that moves beyond the pure availability of destinations.

A Neural Network-Based Sustainable Data Dissemination through Public Transportation for Smart Cities

In recent years, there has been a big data revolution in smart cities dues to multiple disciplines such as smart healthcare, smart transportation, and smart community. However, most services in these areas of smart cities have become data-driven, thus generating big data that require sharing, storing, processing, and analysis, which ultimately consumes massive amounts of energy. The accumulation process of these data from different areas of a smart city is a challenging issue. Therefore, researchers have started aiming at the Internet of vehicles (IoV), in which smart vehicles are equipped with computing and storage capabilities to communicate with surrounding infrastructure. In this paper, we propose a subcategory of IoV as the Internet of buses (IoB), where public buses enable a service as a data carrier in a smart city by introducing a neural network-based sustainable data dissemination system (NESUDA), where opportunistic sensing comprises delay-tolerant data collection, processing and disseminating from one place to another place around the city. The objective was to use public transport to carry data from one place to another and to reduce the traffic from traditional networks and energy consumption. An advanced neural network (NN) algorithm was applied to locate the realistic arrival time of public buses for data allocation. We used the Auckland transport (AT) buses data set from the transport agency to validate our model for the level of accuracy in predicted bus arrival time and scheduled arrival time to disseminate data using bus services. Data were uploaded onto buses as per their dwelling time at each stop and terminals within the coverage area of deployed RSU. The offloading capacity of our proposed data dissemination system showed that it could be utilized to effectively complement traditional data networks. Moreover, the maximum offloading capacity at each parent stop could reach up to 360 GB with a huge saving of energy consumption.

Exploring tertiary students' travel mode choices in Auckland: Insights and policy implications

It is crucial that policymakers and public transport operators comprehend tertiary students' travel mode choices and understand the factors that inform these choices in order to manage travel demands effectively and to optimise the use of public transport and improve its quality of service, particularly during the peak hours. This study aims to examine tertiary students' travel mode choices in Auckland, which is recognised as one of the most car-dependent cities in the world. The city is struggling with traffic congestion, particularly around its Central Business District (CBD) during peak hours. Auckland is New Zealand's largest city, with a population of 1.4 million residents. The main campuses of two major public universities, The University of Auckland (UoA) and Auckland University of Technology (AUT), are located in the CBD, attracting a large number of daily trips by both staff and students, particularly during the teaching semesters. However, there is a limited understanding of tertiary students' travel mode choices, particularly the factors that inform these choices when they travel to the universities' city campuses. A mixed methodology approach was used to comprehend the travel mode choices of students attending The University of Auckland and to identify the key factors that are drivers of these choices. The data collection included a questionnaire-based survey, which received 249 responses, and 10 semi-structured interviews with students. Thematic analysis was utilised to codify and then analyse the interviews. Despite the significant car dependency in Auckland, the survey demonstrated that most respondents utilised public transport and active modes when commuting to the university's city campus. Seven factors were identified that inform tertiary students' travel mode choices: cost, parking availability and cost, access to a car, travel time, physical environment, reliability, and attitudinal variables. The interviewees mostly argued that travel cost and lack of or limited access to a private car were the primary drivers of their travel mode choices. The study suggests that different stakeholders, such as Auckland Transport (AT) and The University of Auckland, should work collaboratively to provide an inclusive travel demand management policy. The university could rearrange classes for off-peak hours, and AT could offer tertiary students further discounts during these hours. These actions would result in the optimisation of public transport efficiency, improvement of the quality of the public transport service, and mitigation of traffic congestion around Auckland's Central Business District (CBD).

Impact of changing road infrastructure on children's active travel: A multi-methods study from Auckland, New Zealand

IntroductionBuilt environment infrastructure that supports active travel may help increase rates of children's active travel to school. Knowledge gaps exist in terms of how small-to-medium scale, school-focused infrastructural changes might impact children's active school travel and associated variables along the pathway to behaviour change. The aim was to work with a regional transport agency to evaluate the impact of infrastructural changes in a school neighbourhood. MethodsChildren in school years 5–8 and their parents/caregivers from two schools involved in a school travel intervention were invited to participate. The study area was identified in partnership with Auckland Transport (responsible for delivering all intervention elements). Children completed a geographic informations systems survey that captured behaviours and neighbourhood perceptions. Parents completed a telephone interview to measure neighbourhood perceptions and reasons for school travel mode. Tube counters and video cameras were used to measure traffic speeds and volume, and counts of pedestrians and cyclists, respectively. Baseline measures were taken in 2015 (traffic data) and from May-July 2016 (all other measures), infrastructural works were delivered from November 2016 to May 2017, and follow-up measures were repeated in May-June 2018. ResultsAt baseline, 123 children and 88 parents participated. At follow-up, 152 children and 91 parents participated. Reductions in traffic speeds but increases in traffic volumes were observed post the intervention. Positive and negative shifts in child and parent neighbourhood perspectives were observed. Distance to school, convenience, and traffic saftey concerns were raised as key factors of importance by parents and children. Overall, rates of car use for the school trip increased, while video observation showed an increase in pedestrians. ConclusionsReversing declines in active travel may require more intensive, community-wide interventions that substantially improve neighbourhood safety and perceptions of safety. Longer term follow-up may be necessary to understand the true effect of the intervention.

The Production and Politics of Urban Knowledge: Contesting Transport in Auckland, New Zealand

ABSTRACTExpert technical knowledge has a central role in decision-making for urban transport and is subject to public scrutiny for major investments. This paper examines how expertise is produced and contested by advocacy groups in Auckland, New Zealand. A network of advocates has emerged, garnering considerable influence as “experts” on urban transport and planning. In response to the perceived over-reliance on outdated approaches to transport, advocates mobilised alternative expertise using blogs and social media. Internet platforms enabled groups to extend the public sphere online, creating spaces for deliberation and contestation. Their activities targeted the technocratic logics embedded in forecasting models, reasserted transport infrastructure’s function as urban space, and highlighted how transport infrastructure shapes everyday experience. This case shows how advocates countered the postpolitical condition by re-ordering the polity of transport in Auckland. Advocates have been instrumental in appropriating globally mobile policies and successfully promoted improvements to public transport and cycling. However, those interviewed showed limited consideration of equity issues related to income, race and gender. This raises questions over whether the expertise mobilised favoured privileged groups, as advocates may be unaware of marginalisation that they rarely experience themselves. Alliances with community groups and local researchers can support broader engagement with distributional issues.

Te Ara Mua –Future Streets: Knowledge exchange and the highs and lows of researcher-practitioner collaboration to design active travel infrastructure

Abstract Transforming vehicle-focused street infrastructure to support a shift to active travel modes can pose a complex interdisciplinary challenge requiring innovation and collaboration between residents, researchers and transport design and policy practitioners. Te Ara Mua-Future Streets is a street redesign intervention study that aims to slow traffic, change driver behaviour and make walking and cycling easier and safer in Māngere, a suburban neighbourhood in Auckland, New Zealand. It is a collaborative project between a research team, local community and the city's transport agency. Community engagement, evidence-based design innovation and outcome evaluation are primarily the responsibility of the research team while responsibility for infrastructure funding, procurement and delivery lies with Auckland Transport. Notwithstanding a shared commitment to the project's vision of street design innovation for health gain, the collaboration and implementation process has been challenging. Drawing on analyses of interviews conducted with researchers and transport agency personnel at two time points, the paper documents the collaborative process – factors that threatened to derail the design and delivery of innovative street design and those that ultimately enabled construction of a non-business-as-usual, neighbourhood scale intervention. Differences in the professional norms and practices of transport engineers and researchers, contrasting organisational cultures and approaches to risk, and lack of organisational readiness and capacity challenged the collaboration. Sharing insights on factors that had jeopardised the collaborative processes became a catalyst for change, and, coupled with the determination of individual researchers and engineers, enabled the collaboration to move forward to complete the intervention and identify mechanisms to facilitate knowledge exchange in future transport and health, researcher-practitioner collaborations.

Te Ara Mua -Future Streets: An Encounter with Business-As-Usual Transport Planning

Background Future Streets is a street redesign intervention study that aims to slow traffic, change driver behaviour and make walking and cycling easier and safer in Mangere, a suburban neighbourhood in Auckland, New Zealand. It is a collaborative project between research team, local community and the city’s transport agency. Community engagement, evidence-based design innovation and outcome evaluation are primarily the responsibility of the research team while responsibility for infrastructure funding and delivery lies with Auckland Transport. Four years on the new infrastructure is largely in place, and follow-up measures of transport mode use, resident perceptions and air quality are planned for 2017. Not with standing a shared commitment to the project’s vision of street design innovation, the collaboration and implementation process has been challenging. In 2015, two years into the project, an independent interview-based study examined the collaborative process. Methods Semi-structured interviews were conducted with four researchers and six transport agency personnel. Interviews were recorded and transcribed, a coding frame established, and data subsequently coded and analysed thematically. Results • Research and infrastructure delivery timelines were out of step – a four year research grant was aligned to a transport project that would take 6-7 years applying business-as-usual processes. • The intervention budget was initially low and/or uncertain. Researchers pushed hard for further funding, whereas the agency norm was to design and deliver to the available budget. • Researcher priorities were to engage residents in participatory design, and explore and test new ideas iteratively. Participatory design processes were not well understood by the agency. Agency priorities were to design, procure and deliver. Researchers had limited understanding of the time-consuming statutory steps required pre-delivery and of the complexities of procuring infrastructure funding from multiple sources. • Project governance and decision-making were loose in the early design stages. This allowed flexibility but also contributed to frustrations and delays. • Critical decision points highlighted the ‘cultural divide’ between parties resulting in relationship strain but also learning of the other side’s priorities, pressures and constraints. Conclusions Non-business-as-usual funding and planning mechanisms are needed to trial innovative street designs. Researcher-practitioner partnerships will benefit from: upfront negotiation of governance structures; explicit acknowledgement of the diverse drivers and constraints within which each party operates; relationship building; and early confirmation of an allocated budget for new infrastructure. Despite the difficulties encountered, a shared commitment to the vision endured, the research timeline was renegotiated and funding was forthcoming to complete a non-business-as-usual street intervention.

Auckland’s first spatial plan: Ambitious aspirations or furthering the status quo?

Auckland’s first spatial plan (locally known as the Auckland Plan) is the principal document providing strategic direction for the city’s development over the next 30years. The Auckland Plan aspires to radically transform transport in Auckland, from a car-dominant system into an integrated public transport network, by proposing a series of expensive infrastructure projects, including rail tunnels under the CBD, rail extension to the airport, and an additional harbour crossing. This paper critically assesses the transport strategies proposed by the Plan from a broad spectrum of sustainability perspectives. In drawing on the events leading to the 2009 Auckland local government reform, the Plan making process and the content of the Plan, this paper shows that the Plan’s transport strategy suffers a range of drawbacks, including limited political support, a rushed consultation process and lack of a robust framework for funding public transport projects. These problems raise questions about the Plan’s capacity to drive a ‘transformational shift’ in Auckland’s transport landscape and ultimately contribute to the vision of making Auckland the world’s most liveable city. This paper concludes by recommending Auckland Council adopts a more proactive approach to transport planning focusing on better civic engagement, more strategic mechanisms to incentivize public transport and to overcome institutional inertia.

Short-term public transport solutions in Auckland, New Zealand

This paper investigates policy approaches which will improve the existing public transport system in Auckland, New Zealand. The four principles of public transport network planning: line structure, frequency, transfers and fare systems, are applied to the Auckland Northern Express (the only Bus Rapid Transit (BRT) in New Zealand). The data concerning the Northern Express and its associated network was collected from policy and planning documents, timetables and websites. The data was further verified by conducting detailed fieldwork on the selected network. The results show that the Northern Express exhibits some network planning principles such as a simple straight-line route, high frequency and transferrable fares. However, the Northern Express is poorly coordinated with the surrounding bus network; this coordination could be improved to gain higher patronage levels. The analysis indicates that the poor performance of public transport in Auckland can be addressed in the short-term by improving public transport services at relatively little cost.

Analysis of Pedestrian Performance in Shared-Space Environments

The concept of shared space as applied in an urban road environment aims to reduce the dominance of motor vehicles by promoting pedestrian and cyclist activity and utilizing road space as a place. Unlike a conventional road, a shared space encourages all road users to legally occupy the same road space with little physical separation. The paper presents pedestrian-related performance measures that were developed under a multifaceted methodological framework to evaluate the success of shared-space schemes on the basis of study areas in the city center of Auckland, New Zealand. Analysis of the data before and after implementation revealed a positive result for pedestrian performance across all sites on the basis of a 24-h pedestrian profile, pedestrian trajectory, dwell time, and stationary activity. A comparative analysis of the data after implementation highlights the importance of the active frontage in enabling a lower (vehicular) speed environment in relation to the number of pedestrians within the shared space. The reported research analysis forms part of a doctoral research study at the University of Auckland with support from Auckland Transport, a regional transport agency in New Zealand.

Transportation safety issues: the student experience and their solutions

Millions of people each day move from their home to a place of work, a school, shop, or to engage in social and or leisure activity. Experts examine this flow...

Personal Exposure to Air Pollution for Various Modes of Transport in Auckland, New Zealand

This paper investigates the carbon monoxide (CO) doses received while commuting by different modes (car, bus, train, motorcycle, bicycle and running), taking into account the commute time as well as the level of physical activity required. While the participants were constrained to travel at specific peak traffic times and between designated start and end points, they were free to choose a route appropriate for their mode of transport. The results of this study suggest that the lowest exposures (concentrations of pollutants) are experienced by train commuters, largely a reflection of the routes being removed from any significant road traffic. Motorcyclists experienced significantly higher average concentrations as a result of high-concentration and very-short-duration peaks not seen in the traces of car and bus commuters travelling on the same road. Travel by bus along a dedicated busway was also found to be effective in reducing commuter air pollution exposure compared to travel by car on a congested stretch of motorway. The average concentrations to which cyclists and runners were exposed were found to be not significantly different for those travelling by car or bus (except when on dedicated pedestrian/cycleways). However, when the increased physical activity that is required is taken into account (leading to higher volumes of air breathed) along with the increased commuting time (especially in the case of runners), the air pollution doses (as estimated by the product of the concentration, commute time and breathing factor) were found to be significantly higher than for the motorised modes. The results suggest that separate pedestrian/cycleways go some way towards providing healthier options for cyclists and pedestrians.

Backtracking Auckland?: Technical and Communicative Reason in Metropolitan Transport Planning

Communicative planning has helped to illuminate the role of technical reason in planning processes. Transport planning has had little exposure to the communicative perspective. This paper examines transport planning in Auckland, New Zealand, from a communicative planning perspective. The paper argues that the historical dominance of technical reason has biased strategic transport policy towards supporting automobiles over more sustainable modes. The paper demonstrates the dominance of technical rationality in transport strategy-making processes and institutions in contrast to expressed public preferences. The paper concludes by arguing that the achievement of greater sustainability in Auckland's transport, and elsewhere, depends on a greater communicative emphasis in regional planning and transport strategy making.

Transport cost analysis: a case study of the total costs of private and public transport in Auckland

Abstract The current level of motorised transportation worldwide is increasingly a social, environmental and economic problem. Transport benefits come alongside injuries and death, unproductive travel time, energy dependence, and environmental damage. One reason for the increasing problem results from externalising various impacts on society. Many of these external – or ‘unpaid’ – costs have only gradually been recognised and most have either been under-valued or are considered impossible to estimate since they have no value in a market. This research assesses the external (unpaid) and internal (user paid) cost of transport. It focuses on estimating the total cost of both private and public transport, using a case study for Auckland, New Zealand's largest city. The external costs are significant −2.23% of the GDP produced by the 1.2 million Auckland region residents in 2001. Of this private transport generated 28 times more external cost than public transport. The internal cost assessment showed that total revenues collected did not even cover 50% of total transport cost. The research has shown that not only are the external costs of vehicle transport high, but that contrary to popular belief the total costs of private transport are subsidised by public transport users. This has implications for successful transport policy options.