ITS Monday: Edition 28 2024

New transport plan for Hobart aims to improve cycling infrastructure, reduce car congestion

“Hobart City Council has recently approved its 2024 Transport Strategy, which focuses on increasing “climate-ready, efficient transport.” It aims to increase cycleways and public transport use and decrease car reliance.”

Related iMOVE articles:

• Traffic Congestion: Info, Projects & Resources
  
• Active Transport: Info, Projects & Resources

Related iMOVE projects:

• Safer cycling infrastructure: Design and policy
• Impacts & community benefits of a regional active travel network
• Improving Darebin’s streets: The community speaks

Strategizing sustainability and profitability in electric Mobility-as-a-Service (E-MaaS) ecosystems with carbon incentives: A multi-leader multi-follower game

A new academic paper co-authored by Haoning Xi, Mengjie Li, David Hensher, Chi Xie, Ziyuan Gu, and Yuan Zheng. The abstract:

Electric Mobility-as-a-Service (E-MaaS) emerges as a promising solution for environmentally-friendly mobility in the future, yet MaaS operators have been struggling to achieve profitability. We introduce a novel E-MaaS ecosystem where platforms can leverage carbon credits revenue from the government’s emissions reduction fund (ERF) by incentivizing travelers to choose more E-MaaS services, thereby reducing carbon emissions.

In such an E-MaaS ecosystem, travelers can select either electric (E)-MaaS or traditional (T)-MaaS services and submit heterogeneous requests, such as distance, service time, tolerance for inconvenience, and travel delay budget, which are modeled as inputs. We propose a multi-leader multi-follower game (MLMFG) model where each leader (MaaS platform) competes to maximize its profits by making operational decisions such as pricing, EV acquisition ratio, and E(T)-MaaS bundle allocation while anticipating travelers’ participation levels. In response to the platforms’ decisions, each follower (traveler) aims to minimize her travel costs by determining the participation levels for E(T)-MaaS services via multiple MaaS platforms.

We develop a customized alternating direction method of multipliers (ADMM) algorithm to solve the proposed MLMFG efficiently. Comprehensive numerical experiments based on real-life data in Australia demonstrate the convergence and robustness of the proposed ADMM algorithm. Further, experimental results reveal how factors such as market size, travel demand, ERF budget, subsidy rate, and unit price boundaries impact the profits and operational strategies of different MaaS platforms.

Overall, the proposed MLMFG model for the E-MaaS ecosystem provides valuable insights for MaaS operators aiming to balance profitability with environmental responsibility, navigating a future where sustainability and profitability goals could converge.

Related iMOVE articles:

• MaaS (Mobility as a Service) in Australia: Info, Projects & Resources
  
• Report: MaaS: What have we learned, and where to next?

Related iMOVE projects:

• Mobility landscapes: Mobility as a Service customer impact trial

How green pedal power misses out on perks other battery vehicles enjoy

“Electric bikes are slowly winning over a new cohort of commuters who want an active, green and cheaper way to get to work. But a quirk of the tax system means battery-powered cyclists don’t enjoy the same perks as electric car owners.”

Modal shift implications of e-bike use in the Netherlands: Moving towards sustainability?

Staying on the topic of e-bikes, this new academic paper. The abstract:

This paper investigates the modal shift patterns of e-bike users in the Dutch context. We focus on the change in e-bikers’ travel behavior to assess whether this change benefits sustainability. Our study provides direct ecologically valid evidence on modal shift by using a longitudinal dataset from the Netherlands Mobility Panel survey. We examine e-bikers’ modal shift patterns before and after acquiring an e-bike.

The findings indicate that after e-bike adoptions, conventional bike use reduces significantly, while car use reduces less strongly. Nonetheless, the share of car kilometers is much larger than that of conventional bikes at the baseline. Besides, the emission rate per passenger kilometer of an e-bike is several times lower than that of a car. These imply a net environmental gain after e-bike adoptions. The present study also sheds light on modal shifts at a disaggregated level by investigating those e-bikers who are more likely to drive less after e-bike adoption.

The findings suggest that e-bikers younger than 50 and those around retirement age (60–69) seem more likely to step out of their cars. Additionally, people living in rural areas tend to be more likely to reduce their car use than their counterparts in highly urbanized areas. Based on our findings, we present policy recommendations for achieving a greener shift in mobility systems.

Traffic Safety Impact of the COVID-19 Pandemic: Fatal Crashes in 2020–2022

“Traffic fatalities surged in the USA during the COVID-19 pandemic. This research from the AAA Foundation for Traffic Safety highlights the fact that disadvantaged communities bore the brunt of the increase and calls for holistic solutions to promote equitable access to safe transportation.’

Related iMOVE articles:

• Road Safety: Info, Projects & Resources
  
• Effects of COVID on the transport sector

Related iMOVE projects:

• Speed and safety evaluation of shared spaces in NSW

How one state is using technology to curb high pedestrian fatality rates

Details of the tech strategies being used in Texas to reduce road fatalities. Texas currently has the USA’s second-highest road fatality rate.