ITS Monday: Edition 4, 2025

Australia spends $714 per person on roads every year – but just 90 cents goes to walking, wheeling and cycling

Writing for The Conversation here is Matthew Mclaughlin – Adjunct Research Fellow, The University of Western Australia. Grant Ennis – Lecturer, Monash University, and Peter McCue – PhD Candidate, School of Population Health, UNSW Sydney.

“What could you buy for 90 cents? Not much – perhaps a banana. Unfortunately, that’s how much the Australian government has invested per person annually on walking, wheeling and cycling over the past 20 years. How would Australians’ lives change if that figure rose?”

Related iMOVE article:

• Active Transport: Info, Projects & Resources

Related iMOVE project:

• Modelling cycling investments in regional areas
• Safer cycling infrastructure: Design and policy
• Impacts & community benefits of a regional active travel network

Who doesn’t like a battery electric truck? Heterogeneous motivations in the uptake of low-emissions trucks in Australia

A new academic article co-authored by Magnus Moglia, Sorada Tapsuwan, Hadi Ghaderi, Christian A Nygaard, Hussein Dia, and Dia Adhikari Smith. The abstract:

Reducing greenhouse gas emissions in the freight sector requires greater use of Battery Electric Trucks (BETs) and/or Hydrogen Fuel Cell Trucks (HFCTs). There is limited evidence on freight operator willingness to pay (WTP) for such trucks, or which factors may influence preferences.

This study addresses this by reporting on a Choice Experiment survey of 199 decision-makers across Australia in various freight services sectors during mid-2023. Results show high WTP, but more so for HFCTs compared to BETs. Reasons for these preferences appear to be linked to a combination of business context, perceived performance for the transport task, including misconceptions that are confounded by limited experience with and exposure to these types of vehicles.

The greatest influence on preferences remains purchase price and ongoing costs. Using Latent Class analysis, we identify three clusters of respondents. One group prefer to buy diesel trucks. A second group prefer HFCTs but is less positive about BETs. A third group prefer anything but diesel trucks. An implication of these findings is that BET/HFCTs transitions requires both financial and non-financial policies.

Related iMOVE articles:

• Alternative Fuels: Info, Projects & Resources
• Electric Vehicles: Info, Projects & Resources

Related iMOVE projects:

• Zero emissions heavy vehicles: Analysis, planning and policy
• Investigating the viability of hydrogen fuel for heavy vehicle use
• Clean fuels, lower emissions in red meat processing transport

Ford to invest in range-extender EVs amid slump in pure-electric vehicle demand

“Blurring the lines between an EV and plug-in hybrid (PHEV), EREVs typically function as an EV but have a combustion engine that acts solely as an electricity generator to power up the battery when it runs out of charge or is close to doing so.”

Determinants of bicycle ownership and use: A case study of apartment residents in Melbourne, Australia

A new paper from Chris De Gruyter and Andrew Butt. The abstract:

Cycling can offer a range of benefits for individuals and society, yet factors influencing bicycle ownership and use are not well understood, particularly among apartment residents where the provision of bicycle parking is stipulated by planning requirements. A survey of 480 apartment residents was undertaken in Melbourne, Australia, with results analysed using descriptive statistics and logistic regression modelling.

Results show that households owned 0.86 bicycles on average, much higher than the current bicycle parking requirement of 0.2 spaces per household for new apartment developments. Additionally, 28% of respondents reported using a bicycle in the last week. Factors associated with bicycle ownership and use included various socio-demographics, attitudes, preferences, and built environment and transport characteristics

In general, these factors were far more extensive than previous studies that have considered all housing types together. Notably, the availability of off-street bicycle parking was found to increase the odds of an apartment household owning one bicycle, compared with none, by more than two times.

The results imply that increasing bicycle ownership and use among apartment residents requires a multifaceted approach, including adequate bicycle parking requirements that vary both spatially and by apartment size, along with programs and events that can foster positive attitudes towards cycling.

Enhanced utility estimation algorithm for discrete choice models in travel demand forecasting

Co-authors on this new paper are Amir Ghorbani, Neema Nassir, Patricia Sauri Lavieri, Prithvi Bhat Beeramoole & Alexander Paz. The abstract:

Recent data-driven discrete choice models in travel demand forecasting have achieved improved predictability. However, such prediction improvements come at the cost of black-box models and lost transparency in travel demand forecasting, which makes scenario testing and transportation planning difficult (if not impossible). Furthermore, these predictability gains have often been modest compared to handcrafted parsimonious models, which benefit from enhanced behavioural interpretability and transparency.

This paper introduces a novel bi-level model and estimation framework (DUET) to enhance predictability in traditional utility-based discrete choice models. The proposed model improves the specification process by identifying effective variable transformations and interactions in utility functions. Utilising a genetic algorithm, the upper level of our framework selects feasible functional forms from an extensive array, while the lower level applies iterative singular value decomposition and maximum likelihood estimation to optimise model parameters and prevent overfitting.

This approach ensures superior predictability through a general utility functional form that considers extensive variable interactions. Case studies on both synthetic data and the Swissmetro dataset highlight the framework’s effectiveness in improving model performance and uncovering critical behavioural patterns and latent trends. Notably, incorporating interactions among variables in Swissmetro data, our model demonstrates a 6.5% improvement in the Brier score (probabilistic prediction accuracy) compared to the state-of-the-art deep neural network-based discrete choice model.Lastly, our results on transport mode choice data align with existing literature, indicating that younger individuals are less sensitive to travel costs. This confirms the need for targeted pricing policies to encourage public transit use among different age groups.

TfL publishes new Safety Standard for cargo bikes

“Transport for London has published a new ‘Safety Standard’ to support cargo bike operations across the UK capital. Included in the standard are 19 key risks identified for cargo bikes, operators and riders, and 21 mandatory safety requirements as well as additional recommendations for operators.

With the potential of cargo bikes replacing 17% of van kilometres in London by 2030 and cutting 30,000 tonnes of carbon emissions each year, the purpose of the standard is to make cargo bikes a “prime option” for last-mile logistics in London.”