In the pursuit of sustainable mobility and the decarbonization of transport systems, public authorities are increasingly scrutinizing the impact of travel speed on emissions within both low-speed and high-speed environments. This study critically examines the evidence concerning emission impacts associated with speed limit changes in different traffic environments by conducting a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 25 studies that met the eligibility criteria were assessed. The results reveal mixed evidence for reducing emissions through speed limit reductions in low-speed areas. However, emerging evidence suggests that reduced urban speeds may abate emissions through enhanced traffic flow and a shift in modal preferences away from personal vehicle use. Additionally, in urban areas, minor observed emission reduction per vehicle can add up to large overall reductions due to the high number of vehicles. In high-speed contexts, the evidence is much clearer, showing that reduced speed limits correlate with significant reductions in NOx, CO₂, and particulate matter emissions. The extent of these reductions is highly variable and contingent upon the specific speed limits or limit reductions, the local context, the vehicle type, and the baseline types and levels of pollutants. Notably, there is a lack of research on the effects of speed on emissions, especially in low- and middle-income countries (LMICs), highlighting a critical area for future investigation. The findings of this study underscore the potential environmental benefits of speed management policies and advocate for the promotion of smoother and less aggressive driving behavior to mitigate emissions and enhance sustainable mobility in both low-speed and high-speed settings.

Non-motorized transportation modes, especially cycling and walking, offer numerous benefits, including improvements in the livability of cities, healthy physical activity, efficient urban transportation systems, less traffic congestion, less noise pollution, clean air, less impact on climate change and decreases in the incidence of diseases related to vehicular emissions. Considering the substantial number of short-distance trips, the time consumed in traffic jams, the higher costs for parking vehicles and restrictions in central business districts, many commuters have found that non-motorized modes of transportation serve as viable and economical transport alternatives. Thus, local governments should encourage and stimulate non-motorized modes of transportation. In return, governments must provide safe conditions for these forms of transportation, and motorized vehicle users must respect and coexist with pedestrians and cyclists, which are the most vulnerable users of the transportation system. Although current trends in sustainable transport aim to encourage and stimulate non-motorized modes of transportation that are socially more efficient than motorized transportation, few to no safety policies have been implemented regarding vulnerable road users (VRU), mainly in large urban centers. Due to the spatial nature of the data used in transport-related studies, geospatial technologies provide a powerful analytical method for studying VRU safety frameworks through the use of spatial analysis. In this article, spatial analysis is used to determine the locations of regions that are characterized by a concentration of traffic accidents (black zones) involving VRU (injuries and casualties) in São Paulo, Brazil (developing country), and Rome, Italy (developed country). The black zones are investigated to obtain spatial patterns that can cause multiple accidents. A method based on kernel density estimation (KDE) is used to compare the two cities and show economic, social, cultural, demographic and geographic differences and/or similarities and how these factors are linked to the locations of VRU traffic accidents. Multivariate regression analyses (ordinary least squares (OLS) models and spatial regression models) are performed to investigate spatial correlations, to understand the dynamics of VRU road accidents in São Paulo and Rome and to detect factors (variables) that contribute to the occurrences of these events, such as the presence of trip generator hubs (TGH), the number of generated urban trips and demographic data. The adopted methodology presents satisfactory results for identifying and delimiting black spots and establishing a link between VRU traffic accident rates and TGH (hospitals, universities and retail shopping centers) and demographic and transport-related data.

The automotive industry is on a continuous transition towards a more sustainable and integrated ecosystem influenced by the fast-paced adoption of Electrical Vehicles (EVs) and the developments of emerging technologies such as Automated Vehicles (AVs). The road transportation sector is also experimenting with the emergent decentralized blockchain technology in various ways ranging from supply chain transparency to insurance and tokenization. Some of the recent use cases are the use of Non-Fungible Tokens (NFTs), unique digital assets designed to be immutable, to certify ownership of a vehicle, the data history of it or just for fan base development. The current paper reviews the literature findings concerning the potential of Non-Fungible Tokens for the automotive industry and proposes a new car ownership and revenue generation model using the ERC-1155 token standard. Our proof-of-concept based on fractional vehicle ownership demonstrates the feasibility of such a model that allows for revenue distribution amongst the vehicle owners according to the percentile invested in the vehicle acquisition.

This study estimated the social costs of road traffic crashes (RTCs) in Cameroon, motivated by a lack of empirical evidence for economic loss and social suffering associated with RTCs menace in developing countries particularly Sub-Sahara Africa. A model for estimation of cost based on a combination of valuation methods was developed following international guidelines, and can be adapted for other developing countries similar to Cameroon’s context. Five cost components were estimated namely: production loss; human costs; medical costs; property damage costs and administrative costs. Data from the field, secondary databases and transfer values were used together with adjustments for under-reporting of road traffic crash data that is prevalent particularly in developing countries. Total social cost of RTCs in Cameroon in 2018 was USD 3.6 Billion and is equivalent to 3.8% of GDP in 2018. This estimate is way above RTCs cost estimates obtained by studies in Sub-Sahara Africa using the human capital approach, and slightly outside the range of social cost estimates found in Lower- and Middle-Income Countries (LMICs) literature. The estimate is also larger than the conservative figures used for policy purposes such as the current National Road Safety Strategy, implying that under-reporting of RTCs data under-represents apparent socio-economic value of RTCs. The study recommends improvement in the procedures of crash data by operationalizing the recently established centralized RTCs database, as well as adoption of systematic approaches to estimation of crash costs by policy makers.

The transition to sustainable mobility is a recognized socio-economic and environmental challenge, particularly among young adults. In addressing the gap in the literature on young adults’ travel behaviors, especially in Cameroon, this paper investigates the transport mode choices, influencing factors, and barriers to sustainable mobility of students at the National Advanced School of Public Works, Yaoundé (NASPW). Data were collected through online questionnaires with 360 valid responses. Findings revealed that most students used multiple modes of transport for commuting, with moto-taxis being the most common. Accessibility, vehicle speed, and flexibility appeared as the most important reasons for the preferred transport modes, while driver’s license possession, safety perceptions, speed, and proximity were significant predictors for mode choice. Demographic factors were found to influence transport preferences, with distinct clusters prioritizing different aspects. Barriers to public transport were primarily long waiting times and congestion, while active mobility was hindered by distance, infrastructure, and weather. The usage of public transportation was encouraged by its affordability and reduced travel time, whilst active options were preferred due to cost savings and health benefits. To promote sustainable mobility for campus travel, it is crucial to encourage active modes, develop mass transport systems, and raise awareness through symposia and conferences among students and staff.