Literature Reviews

Collectively referred to as connected and automated vehicles (CAVs), connected vehicles (CVs), which communicate wirelessly with one another, and automated vehicles (AVs), in which a computer partially or entirely replaces the driver, have the capacity to revolutionize road maintenance and transportation operations [1]. According to Egan Smith (Managing Director of the Intelligent Transportation Systems (ITS) Joint Program Office of the United States Department of Transportation), "Successful deployment and operation of these new technologies depend largely on a knowledgeable, trained, and skilled workforce to support them” [2].

According to the California Department of Transportation's (Caltrans) strategic strategy, workforce development is a key action plan for CAV deployment [3]. Caltrans emphasized the importance of identifying labor difficulties and needs, as well as encouraging state efforts to recruit and retain the future workforce, in order to continue CAV. It could necessitate developing proper job categories, role descriptions, hiring procedures, and competitive salary ranges. Another option is to create a pool of highly skilled individuals (such as data scientists and network engineers) who can be housed in one functional unit and then transferred to other functional units or districts to share their technical expertise.

As CV and V2X technology advances, the Intelligent Transportation Systems (ITS) transportation workforce will require advanced knowledge, skills, and abilities. As a result, new and modified training opportunities are important for the ITS workforce to develop the advanced skill sets required to maintain a transportation network populated by evolving technologies [2].

Workforce development is essential not just for CAV deployment, but also for maintenance and repair (M&R). To stay up with technological advances, employees in this field must be upskilled and trained on a regular basis [4]. Crane et al. [5] also acknowledged that there is an increasing need to comprehend middle-skill positions, such as technicians, engineers, systems architects, managers, and IT specialists (that require at least a bachelor’s degree).

According to Parikh et al. [1], the most significant expense associated with CV deployment is the cost of labor for CV installation/deployment and people training. According to the author, operations and maintenance expenditures only account for about 20 percent of time, while the complexity of personnel training accounts for the other 80 percent.

Studies considering the impacts of automated trucks on the workforce find that automation may first effect long-haul trucking or over-the-road drivers [1]. These drivers travel throughout a region or the continental United States for work, typically on a limited set of federal interstates and highways. Wang et al. [2] suggest assessing the potential for job displacement by looking at growth in alternative positions with similar requirements for skills, knowledge, and abilities in a truck operator’s home state. According to their study, only 10 states have sufficient alternative employment opportunities to absorb a greater than 15% displacement in truck driving jobs, indicating a need for worker retraining if trucking displacements.

A survey of trucking logistics managers, supervisors, and drivers found that drivers were the most likely to believe that automated trucks would reduce the size of the U.S. truck driving workforce (62%), followed by supervisors (50%), and managers (25%) [3]. Interviewees in this study noted that they thought the introduction of additional technologies into trucking, such as automation, would lead to a shift towards younger drivers rather than older drivers.

The transportation industry is changing rapidly due to technological advances. As a result, skillsets have diversified and expanded, requiring education and workforce development to adapt to these needs. Labor market research has shown that low-skilled workers tend to be most affected by the technological substitution of labor driven by new technologies such as automation [1]. New training tools are needed to equip the future workforce with the technical, adaptation, and capacity skills needed to react to the evolving industry [2].

There is limited research on workforce development specific to a transportation mode such as micromobility. Overall, the literature on transportation and workforce development recommends partnerships with industry and academia, increasing investment in workforce development, integrating training to pre-apprentice and apprentice programs, and collecting data to inform policies and decision-making [1], [3].

Early operations of shared e-micromobility services relied heavily on independent contractors, with one account estimating 40 percent of Bird’s operational costs at one point went towards workers to collect, charge, and distribute dockless e-scooter and bikes [4] . In 2019, California passed a law (AB5) reclassifying who could be considered independent contractors, shifting the labor market toward third party companies and away from part-time workers [5]. Future research could investigate how regulation of independent contractors has influenced the micromobility workforce.

Ride-hail drivers, part of the gig economy, are contracted as independent employees and often lack legal protection on labor rights and employment benefits that would be offered to traditional employees [1]. Existing research on ride-hail drivers focuses on the labor conditions of the workforce and understanding the motives behind becoming a ride-hail driver. Research reveals ride-hail drivers attract a diverse group of populations. According to Benner [1], 78 percent of the workforce is people of color and 56 percent are immigrants. Hall [2] concludes drivers are attracted to gig work due to schedule flexibility and additional income outside of their full-time or part-time jobs. There is limited research on the interests and capabilities of current workers in order to develop effective workforce development programs that will empower drivers to take collective action [3]. The current research suggests workforce development tools should also be aimed towards individuals outside the gig workforce, self-employed individuals, or platform workers [3]. While the industry lacks widespread collective action among drivers, many drivers have taken to various strategies to advocate for themselves such as business planning, leveraging platform competition, activism through social media, and using technology to manage the workforce [3].

Ghost kitchens, or restaurants without dining space that focus on online food orders, can reduce overhead costs from front-of-house staff and single-facility expenses [1]). This may affect the demand for hospitality workers and food service establishments in a jurisdiction.

One workforce-related concern for gig economy workers, who are independent contractors, is that they will be exploited if they become overly-dependent on a single platform [2] . Delivery service workers can increase their revenues by strategically switching between services (known as multihoming) and repositioning their locations to areas of high demand [3].

On-Demand Delivery Services can provide ride hail drivers with an alternative platform for gig work, and ride hail and delivery platforms must compete for workers, as Liu and Li [4] illustrate below:

No specific literature was found; rather the focus of the literature was on the general concerns of how workers with low skills and low wages will be affected by technological substitution and how to manage the transfer of skills.

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

Increased access to education and job opportunities are cited as benefits of Universal Basic Mobility (UBM), based on robust existing research demonstrating the relationship between mobility and access to opportunity and early research on UBM pilot programs [1], [2]. Research assessing how effectively UBM policies and programs improve access to education and job opportunities is sparse.

Following the historical research gaps on carsharing, Shaheen [1] recommended longitudinal monitoring to better understand market developments and social and environmental impacts due to growth and policymakers’ interests. For a brief period of time, carshare literature focused on workforce development and labor conditions related to rebalancing in one-way carsharing systems [2]. Today, carsharing evolving with the rise of shared autonomous vehicles have created a gap in research. More research is needed to understand how drivers, barriers, and carsharing will be impacted with autonomous vehicles [3]. Chan and Shaheen [4] predict that carsharing in the next decade will include greater interoperability among services, technology integration and stronger policy support [4]. Understanding how carsharing will develop and its impact can help inform policy related to education and workforce development. However, literature explicitly related to education and workforce development was nonexistent which reveals a major research gap.

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].