Literature Reviews

Micromobility has mixed implications for urban transportation sustainability. A comprehensive study of 500 travelers revealed that while personal e-scooters and e-bikes tend to reduce carbon dioxide emissions compared to replaced transport modes, their shared counterparts might increase emissions [1]. Another emphasized the potential of micro-mobility to reduce greenhouse gas emissions, but highlighted that the real impact depends heavily on what transport modes are substituted, the types of trips, and the specific urban contexts, and suggests that existing shared micromobility programs often substitute for active transportation.[2] Policies and infrastructure adapted to these realities can enhance the benefits of micro-mobility. Systematic reviews further underscored that the shift to e-mobility often replaces walking and public transport, which could lead to increased energy demands - this is, however, not an intrinsic property, but a product of the availability of the service, ease of docking, and perceived safety of the service [2].

Universal Basic Mobility (UBM) may improve access to active transportation modes like bicycling. UBM may also improve health outcomes by increasing accessibility of health care and supportive services, especially among senior populations with limited existing access to mobility. A region’s health is related to its choice in transportation options - policies which provide better access to active transportation modes, such as cycling, or transit, which often requires walking to stops, may improve health outcomes, but the effect is likely to be marginal. At present, health is not a targeted outcome of any UBM programs, and research is needed to clarify the relationship between recipients of UBM and health outcomes.

By bundling multiple modes into one interface and payment scheme, Mobility-as-a-Service (MaaS) can both induce mode shift [1] and generate new trips [2], which has implications for urban land use. Early research suggests that those most likely to use MaaS services are those who already use public transit frequently [3]. However, price structure specifics, like the number of discounted rides, geofencing, and unlimited options, can determine MaaS user mode choice [4], which can then impact congestion and parking demand. MaaS schemes that incentivize private auto drivers to switch to public transit may ease parking demand and congestion, but schemes that incentivize the switch to services like ride-hail or carshare may exacerbate congestion. MaaS services may also induce mode changes from active transportation modes like biking and walking towards public transit and ride-hail [1], with unclear implications for congestion and use of infrastructure like bike lanes and sidewalks. Future research should consider the impact of MaaS on parking demand in dense urban areas.

The automotive industry is undergoing a transformative shift driven by advancements in technology, changing consumer preferences, and global sustainability goals. As the industry evolves, the need for a skilled workforce equipped with the knowledge and expertise to navigate this changing landscape becomes increasingly critical. On one hand, automated vehicles (AVs) will likely displace some jobs such as taxi drivers, bus drivers, and truck drivers. On the other hand, widespread AV deployment will create new jobs and fundamentally change many others. For example, skills needed to manufacture and maintain these vehicles will be very different from those currently needed in these markets. Understanding anticipated shifts in job availability, roles and responsibilities, and required skill sets over time will serve as a crucial foundation for developing targeted training programs, implementing strategic workforce development initiatives, and ensuring that individuals possess the requisite skills and competencies to thrive in this dynamic and rapidly evolving sector [1].

The workforce shift and changes in labor demands are directly related to the acceptance of AVs. While previous study has found several elements that contribute to the shift in acceptance of AVs following education, as of 2019 there was a paucity of investigation into the specific components that influence this change at the individual level [2]. Another aspect influencing workforce development strategies and efforts in AVs is the accuracy of AV technology advancement timeframes. This is because the widespread deployment of AVs will have an influence on a variety of transportation-related jobs [3]. As a result, having an accurate AV deployment schedule will aid in the development of appropriate and suitable public policies, as well as the creation of well-planned budgets for workforce development [1].

Automated Vehicles (AVs) have the potential to prevent 95 percent of pedestrian injury crashes in the US, particularly when a driver violation or pedestrian visibility occurred more than one second before crossing [1]. Vehicles equipped with Advanced Driver Assistance Systems, such as front collision prevention/warning, lane departure prevention, emergency braking, and adaptive cruise control, are already accessible for purchase by consumers. These systems are believed to provide safety benefits due to their ability to reduce human errors in driving and minimize the likelihood of accidents. For example, Scanlon et al. [2] found that lane departure warning and lane departure prevention systems could prevent 28 to 32 percent of road departure crashes in the United States under current road infrastructure conditions. Cicchino [3] observed a 27 percent reduction in front-to-rear crash rates and a 20 percent decrease in front-to-rear injury crash rates with the use of forward collision warning systems. Furthermore, Cicchino [3] noted a 43 percent decrease in front-to-rear accident rates and a 45 percent reduction in front-to-rear injury crash rates with the implementation of low-speed autonomous emergency braking. It is estimated that over 400,000 injuries and nearly a million collisions could have been prevented in 2014 if forward collision warning with autonomous emergency braking had been installed in all vehicles nationwide [3].

Recent safety studies have focused on comparing Autonomous Driving Systems (ADS) safety with that of human drivers. For example, Kusano et al. [4] compared Waymo (an SAE Level 4 ADS) rider-only crash data to human drivers, and found a human crash rate 6.7 times higher compared to the ADS for crashes that caused injuries, and 2.2 percent higher compared to the ADS for policed-reported crashed vehicle rates. In 2024, a working group of industry, academic, and insurance experts developed the Retrospective Automated Vehicle Evaluation (RAVE) checklist, which sets out 15 recommendations to ensure the quality and validity, transparency, and accurate interpretation of retrospective ADS performance comparisons [5].

Connected vehicles (CVs), connected autonomous vehicles (CAVs), and Vehicle-to-Everything (V2X) technologies can improve transportation system operations and efficiency. For example, Guler et. al [1] used simulations to assess the potential for CVs to optimize intersection efficiency, finding that CVs could reduce delays by up to 60 percent. The reductions in intersection delays were up to 7 percent greater for CAVs compared to CVs controlled by drivers [1]. Platooning technology can reduce fuel consumption and smooth traffic oscillation [2], and there is a growing body of research around autonomous intersection management [3], [3], [4], [5]. Vehicle to infrastructure (V2I) technology can also improve traffic efficiency by optimizing traffic signal control [6].

A significant body of research exists on how to optimize traffic and safety using connective technology, but it is primarily based on simulations since real-world data is limited [1].

Autonomous vehicles (AVs) applications can be categorized into a) private autonomous vehicles, b) shared autonomous taxis and c) heavy duty autonomous vehicles like trucks and buses. Research studies [1] based on simulation and hypothetical models suggest that connected and autonomous vehicles (CAVs) will result in increased vehicle miles, shift from active travel to more autonomous vehicle (AV) travel, and more urban sprawl. Thus, these technologies seem to be in conflict with sustainability goals. However, AVs can be environmentally friendly and have social equity benefits if used for public transport, shuttles and shared use mobility. Based on public perception [1], AVs are well accepted for public transport among the public as opposed to being used as personal vehicles.
Mouratidis & Cobeña Serrano [2] analyzed the intention for using autonomous buses within a case study area to see user perceptions of AVs. They observed that travelers would be willing to adopt autonomous buses if these offer more frequent departures. López-Lambas & Alonso [1] observed autonomous buses to decrease congestion, intersection wait time and reduce emissions as factors to influence perception of acceptance of these technologies.
Automated applications for trucks have received a lot of attention over the years due to ease of platooning with freight and the potential network wide operation and fuel consumption benefits. Z. Wang et al. [3] tested connected eco-driving system on heavy duty trucks in Carson, California on two corridors with six intersections. They observed smoothing of speed profiles when trucks approached signalized intersections and showed 9 percent and 4 percent fuel savings in acceleration and deceleration phases. Lee et al. [4] analyzed the safety and mobility of different market penetrations of truck platoons using simulation. They observed that safety improved with 2.5 percent higher speed difference by increasing market penetration rate of truck platoons. M. Wang et al., [5] tested truck platooning under different penetration rates in a simulation environment and observed truck platooning to reduce congestion and improve throughput at higher market penetration rates. They observed significant variability in merging speed under saturated traffic.
The literature has focused more on the benefits of AVs in personal vehicles than the use of heavy duty AVs. Additional research is needed regarding the use of heavy duty AVs for public transport, as well as potential system impacts of automated trucking.

A review of the literature using Google Scholar and ProQuest yielded no applicable research, indicating a probable gap in the literature.

Carsharing can increase the efficiency of the transportation system by allowing multiple individuals to access a single vehicle that uses a single parking space [1]. As with many transportation modes, carsharing serves different needs under different conditions within a broader transportation system. For example, carsharing works well in communities with low vehicle ownership rates [2] or co-located with bus services and areas that have mobility constraints in accessing metro services [3]. Additional research is needed to determine what specific pricing conditions and when and how public or privately-operated carsharing can be sustainable.