Achieving ‘Active’ 30 Minute Cities: How Feasible Is It to Reach Work within 30 Minutes Using Active Transport Modes?

Confronted with rapid urbanization, population growth, traffic congestion, and climate change, there is growing interest in creating cities that support active transport modes including walking, cycling, or public transport. The ‘30 minute city’, where employment is accessible within 30 min by active transport, is being pursued in some cities to reduce congestion and foster local living. This paper examines the spatial relationship between employment, the skills of residents, and transport opportunities, to answer three questions about Australia’s 21 largest cities: (1) What percentage of workers currently commute to their workplace within 30 min? (2) If workers were to shift to an active transport mode, what percent could reach their current workplace within 30 min? and (3) If it were possible to relocate workers closer to their employment or relocate employment closer to their home, what percentage could reach work within 30 min by each mode? Active transport usage in Australia is low, with public transport, walking, and cycling making up 16.8%, 2.8%, and 1.1% respectively of workers’ commutes. Cycling was found to have the most potential for achieving the 30 min city, with an estimated 29.5% of workers able to reach their current workplace were they to shift to cycling. This increased to 69.1% if workers were also willing and able to find a similar job closer to home, potentially reducing commuting by private motor vehicle from 79.3% to 30.9%.

SWOT Analysis and a Case Study at Kayseri Airport

In this study, Kayseri Airport, which operates under Dhmi in Kayseri, is discussed within the scope of SWOT analysis. As a result, the most powerful aspect of Kayseri Airport is its proximity to the city, and the weakest dimension of Kayseri Airport is the low frequency of flights during the daytime. The outstanding features of Kayseri Airport regarding the opportunities arising from the external environment are tourism potential of the city, transport modes supporting each other, investments around the airport, supporting civil aviation nationwide, development of trade volume of the city. The most important feature of Kayseri Airport regarding the threats arising from the external environment are that it is not seen as a direct departure/destination point for international flights and distorted construction around the airport land.

Virtual reality as a new tool for transport data collection

Transport studies that adopt complex analyses present methodological challenges that lead to the use of innovative techniques to address the limitations of traditional methods. In the Latin American context, people consider security as a relevant variable in their daily lives. Thus, when people travel around the city and choose a mode of transport, secu-rity becomes an important factor and should therefore be included in transport studies. However, the definition of security in terms of transport in the Colombian context remains unclear. Therefore, we examined the security percep-tion effect on transport mode choice by addressing security as a latent variable consisting of three elements: environ-ment, subject and transport mode. We proposed the use of virtual reality (VR) to recreate travel routes and offer partic-ipants a scenario of choice closer to the natural conditions of a trip. The participants were provided routes in the form of immersive 3D videos recreating natural trip conditions to identify their choices and travel behaviour. Recordings were made of daily scenarios and existing urban environments portraying real and active modes of transport, giving respondents an almost-natural experience. The use of 360-degree immersive videos offers a multisensory experience allowing both the capture of socioeconomic and travel information and the collection of journey perception. The experiment evaluated two environments in Medellín, Colombia (secure (E1) and insecure (E2)) and studied the effects of lighting conditions (day (D) and night (N)). A total of four videos (E1D, E1N, E2D and E2N) depicting six transport modes in tandem were assessed by 92 participants from Medellín and Bogotá, Colombia. We found that environment-associated security perception varies depending on the time of the journey (day/night) and one’s familiarity with the environment. The research results position VR as a tool that offers high potential to support transport studies. We found that people’s movements, gestures and expressions while participating in the VR experiments resembled what was expected from journeys in reality. VR constitutes a relevant tool for transport studies, as it allows for an assessment of active transport mode perceptions. It prevents participants from being exposed to the risk associated with travel to specific places and carries out several routes in different transport modes even when participants cannot or have never undertaken journeys in the modes under assessment.

Passenger Capacity and Safety: Investigating the Likelihood of COVID-19 Transmission in Public Transport Modes within Makurdi Metropolis

Following its outbreak in the Wuhan region of China, the spread of Corona Virus (COVID-19) across the world has threatened national and local authorities or policy makers and transport experts due to its effects on human mobility. This study investigated the transmissibility of COVID-19 among passengers in transit using public transport modes in Makurdi metropolis. Analytical simulation using stochastic search method called Genetic Algorithm (GA) technique was used to simulate the transmissibility of the infectious disease within enclosed spaces of transport modes based on layouts and capacities. The sum of arithmetic sequence was used as the objective function of individual arrivals in each mode, it was minimised to obtain optimum safe capacity. Capacities of public transport modes were subdivided into; Normal, Above Normal and Below Normal (50% of Normal). Findings of the experiments indicated that optimum safe capacity of minibuses, taxies, tricycles and motorcycles used in Makurdi metropolis were at 8, 3, 2 and 1 person respectively. This occurred at 50% capacity which agreed with findings of previous studies. An efficient and sustainable public transport policy framework was designed for policy makers and transport experts to help achieve safe travel and healthier living in Makurdi metropolis during the COVID-19 era. Keywords— COVID-19 transmission, Makurdi Metropolis, Modal Split, Mode capacity, Passenger Safety, Public Transport.

FAHP FOR SELECTING TRANSPORT MODES OF TAIWAN OFF-SHORE ISLANDS’ MILITARY LOGISTICS

Three off-shore islands of Taiwan: Penghu, Kinmen and Matsu are critical in tactical position for Taiwan military, but lack of scarcity resource. Therefore, logistics is very important especially for the off-shore islands. Practically, most of the goods and materials are transported to the islands in the way of shipping and air transportation by Taiwan. However, the severe weather of the islands makes the transportation difficult or even to delay, which is a serious problem for the military logistics of the islands. To raise transportation performance, a proper evaluation method is necessary for military logistics to select the best transport mode based on reducing cost and emphasizing efficiency. Generally, analytic hierarchy process (AHP) may be a method in the selection of transport modes for Taiwan off-shore islands’ military logistics. However, some computation procedures in AHP are hard or complicated especially for processing numerous interviewees’ messages. To resolve the above tie, we utilize fuzzy analytic hierarchy process(FAHP) in selecting transport modes for Taiwan off-shore islands’ military logistics in this paper. After integrating interviewees’(i.e., querying soldiers’) opinions into fuzzy pair-wise comparison matrices, FAHP, being different from AHP, simply and efficiently yields priorities of the fuzzy pair-wise comparison matrices to find the best transport mode of Taiwan off-shore islands’ military logistics.

Transport Modes and the Green Economy

This chapter provides empirical evidence regarding the various transport modes and the green economy in the Limpopo Province of South Africa. Issues pertaining to green transport, strategies for implementation and any challenges associated with the transition towards green transport are grounded on empirical research conducted in the province. In South Africa, transitioning to a green economy is envisioned as a vital means to respond to critical development challenges that the country is facing and will continue to face in the near future. Many of these challenges are intertwined and they range from high levels of unemployment, poverty and inequality, to energy, security and climate change. The transition to a greener economy is articulated in the national development policy through a series of frameworks, strategies, policies and Acts which all enshrine sustainability or the notion of making the South African economy greener (Department of Environment Affairs (2016) . However, the implementation of green transport in general and particularly in the Limpopo province, is still in the infancy stage.

Integrative analysis of multimodal traffic data: addressing open challenges using big data analytics in the city of Lisbon

Worldwide cities are establishing efforts to collect urban traffic data from various modes and sources. Integrating traffic data, together with their situational context, offers more comprehensive views on the ongoing mobility changes and supports enhanced management decisions accordingly. Hence, cities are becoming sensorized and heterogeneous sources of urban data are being consolidated with the aim of monitoring multimodal traffic patterns, encompassing all major transport modes—road, railway, inland waterway—, and active transport modes such as walking and cycling. The research reported in this paper aims at bridging the existing literature gap on the integrative analysis of multimodal traffic data and its situational urban context. The reported work is anchored on the major findings and contributions from the research and innovation project Integrative Learning from Urban Data and Situational Context for City Mobility Optimization (ILU), a multi-disciplinary project on the field of artificial intelligence applied to urban mobility, joining the Lisbon city Council, public carriers, and national research institutes. The manuscript is focused on the context-aware analysis of multimodal traffic data with a focus on public transportation, offering four major contributions. First, it provides a structured view on the scientific and technical challenges and opportunities for data-centric multimodal mobility decisions. Second, rooted on existing literature and empirical evidence, we outline principles for the context-aware discovery of multimodal patterns from heterogeneous sources of urban data. Third, Lisbon is introduced as a case study to show how these principles can be enacted in practice, together with some essential findings. Finally, we instantiate some principles by conducting a spatiotemporal analysis of multimodality indices in the city against available context. Concluding, this work offers a structured view on the opportunities offered by cross-modal and context-enriched analysis of traffic data, motivating the role of Big Data to support more transparent and inclusive mobility planning decisions, promote coordination among public transport operators, and dynamically align transport supply with the emerging urban traffic dynamics.