Literature Reviews

Carshare may, relative to private auto travel, confer some safety benefits. For example,users generally have to go through a screening process to sign up for the programs and establish valid licenses. Safe driving behavior does, of course, vary by individual; a study of Australian carshare users found that infrequent users, users in households that owned other cars, and users that had fewer previous accidents, chose more expensive vehicle insurance, and had been licensed for longer, were less likely to be in a vehicle crash [1]. To enhance safety, the study recommended establishing incentives for carshare users with more driving experience and more extensive insurance [1].

More research may be necessary to better establish safety differences among carshare users, whether carshare users travel more safely relative to private vehicle owners, and if so, what the mechanisms are that promote additional precautions while driving.

A scoping review of public health impacts from on demand food and alcohol delivery published in SSM Population Health found that on-demand delivery services increase geographical access to food but tend to market unhealthy and discretionary foods, and are likely increasing existing health issues and inequities [1]. The review also highlighted concerns over poor age verification processes potentially allowing minors to access alcohol more easily [1].

Demand-responsive transit and microtransit can benefit public health by improving accessibility. Microtransit services are often more direct or even door-to-door and can serve users with limited mobility. They typically target users whose transportation needs are not met by traditional public transit, including shift workers, low-income individuals, the elderly, disabled, and communities with low levels of fixed-route public transit service [1], [2]. A study on demand-responsive microtransit programs’ return on social investment found that social benefits can outweigh costs by 4 to 6 times, due to their ability to increase access to essential services, foster social inclusion, and improve sustainability [1].
While there are some case studies on microtransit programs, there is limited research on public health impacts. Additional research is needed to understand the extent to which microtransit can meet transportation needs that are not filled by public transit, and how it can best serve different populations and uses, and how it impacts public health. Some of this research is in progress. For example, the "Safety and Public Health Impacts of Microtransit Services" research initiative at the University of Massachusetts Amherst is currently evaluating safety and public health impacts of microtransit services [3].
Finally, on-demand transit/microtransit programs are often meant to improve equitable access, but there is little research on how to design programs to best meet that goal. Survey data from four US cities found that men, younger riders, the highly educated, and transit riders were more likely to be interested in using microtransit. Additional research is needed to understand who on-demand transit/microtransit most frequently serves, and how that impacts public health across demographic groups.

The introduction and potential proliferation of highly automated vehicles (AVs) present the classic challenge of balancing the freedom of private manufacturers to innovate with the government's responsibility to protect public health. AVs raise many public health issues beyond their potential to improve safety, ranging from concerns about more automobile use and less use of healthier alternatives like biking or walking, to concerns that focusing on autonomous vehicles may distract attention and divert funding from efforts to improve mass transit. There are, additionally, issues of access, especially for the poor, disabled, and those in rural environments [1].

As the classic Code of Ethics for Public Health recommends [2], public health advocates can advocate for the rights of individuals and their communities while protecting public health by helping to establish policies and priorities through “processes that ensure an opportunity for input from community members.” Public health thought leaders can ensure that communities have the information they need for informed decisions about whether and how autonomous vehicles will traverse their streets, and they can make sure that manufacturers who test and deploy autonomous vehicles obtain “the community’s consent for their implementation.” Finally, public health leaders can work for the empowerment of the disenfranchised, incorporating and respecting “diverse values, beliefs, and cultures in the community” and collaborating “in ways that build the public’s trust” [2].

Emerging micromobility options such as e-bikes and e-scooters can improve accessibility and connectivity for vulnerable population groups, such as those with physical limitations or without access to a car [1], [2]. Compared to biking or walking, electric micromobility (EMM) vehicles are often more accessible to users with lower interest in or capacity for physical activity, while still providing exercise and outdoor enjoyment [1], [2], [3]. For instance, e-bikes are favored by older adults as a form of physical activity and can encourage micromobility use for distances over 3 miles typically covered by cars [4], [5], [6]. An observational study found that starting to e-bike may increase overall biking frequency among older adults, potentially extending the number of years they are able to bike [4], [5], [6]. Despite being less physically demanding than conventional biking, e-biking offers many of the same cardiovascular benefits [5], [7].
In addition to health benefits from access, physical activity, and outdoor enjoyment, increased EMM vehicle usage has the potential to reduce air pollution from cars by substituting car trips and improving access to public transit. EMM vehicles can address the first-mile-last-mile problem, supporting the use of public transit [8], [9]. They also provide an alternative mode of transportation for short trips, which can help alleviate overcrowding on public transport and support social distancing when necessary [8]. Moreover, EMM vehicles may contribute to noise pollution reduction, which is linked to adverse health effects such as cognitive impairment in children and sleep disturbance [9]. However, studies indicate that not all EMM vehicles have the same environmental health benefits; e-scooters, for instance, may have a negative environmental impact compared to the modes they replace (for example, they may replace pedestrian trips) [9], [10], [11]. Additionally, the collection vehicles used for relocating and charging EMM vehicles in shared vehicle programs can contribute to emissions, particularly in less densely populated areas [9].
Safety remains a primary concern for public health regarding EMM usage, and is discussed in more detail in the section devoted to safety impacts. Cyclists, including e-bike users, are vulnerable to injuries and fatalities from collisions with cars. Electric scooter usage can also result in serious injuries, especially head and limb injuries, exacerbated by low helmet usage [9], [12]. Injuries to pedestrians from e-scooter riders on sidewalks are another significant concern [9]. Providing separate, designated infrastructure for EMM can enhance safety [1].
Future research could include the development of best practices for maximizing public health benefits of micromobility programs, as well as further analysis of the health impacts of different micromobility modes.

A review of the literature yielded no social equity concerns that were independent of workforce-related issues. Those issues are covered under the heading “Education and Workforce.”

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

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.

Automated vehicle technologies hold significant promise for benefiting vulnerable populations and bridging urban-rural disparities. Demographically, numerous studies highlight the potential of automated vehicles to improve mobility for people with disabilities, elderly individuals, and low-income populations by offering accessible and affordable transportation options [1], [2], [3], [4], [5].
Automated vehicles offer a game-changing solution for individuals with disabilities, including those with vision impairments [6], [7], [8], cognitive impairments [9], [10], [11], or limited mobility [12], [13], [14]. Equipped with advanced sensors and navigation systems, these vehicles could provide safe and reliable transportation for people with disabilities. They could incorporate user-friendly interfaces and assistive technologies, such as wheelchair ramps and voice-activated controls, to ensure accessibility and ease of use [15], [16], [17]. By removing physical barriers and offering personalized assistance, automated vehicles empower individuals with disabilities to travel independently and participate more fully in their communities.
Geographically, the deployment of automated vehicles has the potential to address “transportation deserts” in small urban, rural, or remote areas, providing residents with access to essential services and opportunities that were previously out of reach [18], [19], [20]. For rural areas, where transportation infrastructure may be lacking and population densities are lower, automated vehicles, like other shared ride services, could provide on-demand mobility options and connect residents to employment opportunities, healthcare services, and education centers [21]. Similarly, in small urban areas, where public transportation may be less extensive compared to larger cities, automated vehicles could serve as a flexible and efficient transportation solution, improving mobility and access to resources for residents.
However, the literature also emphasizes the need for careful planning and implementation to ensure that these technologies do not exacerbate existing inequalities. Concerns such as the digital divide [22], [23], [24], affordability [1], [25], [26], [27], and infrastructure limitations [28], [29], [30], [31] in rural and small urban areas must be addressed to ensure that the benefits of automation are equitably distributed across demographic and geographic lines. In addition, the literature emphasizes the importance of community engagement and inclusive planning processes to ensure that the deployment of automated vehicle technologies is responsive to the needs and priorities of diverse communities [18], [32], [33], [34].

Demand-responsive transit (DRT) and microtransit optimization has been studied using models and theoretical networks. From a strategic design perspective, continuous approximations of demand over time and space in highly theoretical networks were used to determine optimal flexible service types as a function of demand density [1], [2], [3], [4]. For tactical decision making, studies have used optimization methods in highly theoretical networks to optimize slack times [5], [6], longitudinal velocities [7], service cycle times [8], and compulsory stop selection and sequence [9]. Finally, from an operations standpoint, previous studies have evaluated policies such as dynamic stations [10], flag stops [4], point deviations[11], and optimal cycle lengths [12] in off-line settings. Few studies have also evaluated real-time operational strategies, such as optimal shuttle departure times [13] and routing/stopping decisions for rail connector services [14]. Generally, previous studies consider highly simplified or theoretical network conditions (e.g., grid networks, uniform travel times and uniform trip types), which can lead to suboptimal decision-making and unrealistic performance estimates. Though there are a number of DRT or microtransit pilots throughout the country, analysis and evaluation of real-world microtransit systems do not necessarily improve the overall system performance on efficiency, accessibility and financial sustainability. There is potential for DRT and microtransit service to be improved by innovative technologies, such as real-time demand prediction, real-time ride requests, coordination with both fixed-route mainline public transit and privately operated ride-hailing or mobility service. Both technologies of sensing, communication and service, and AI-powered algorithms could improve DRT and microtransit performance.

Demand-responsive transit/microtransit services can prove a cost-effective alternative to fixed-route services in rural and outlying areas where people and destinations are spread across large geographies, and the great majority of residents drive [1]. In those cases, a tailored, small scale on-demand service can flexibly meet the needs of a small group of riders better than a larger bus service that operates on a fixed schedule can. For rural transit agencies with a small budget, a microtransit pilot program offers an opportunity to lease vehicles and pay a third-party service provider to operate the program without spending the capital costs, liability and long-term labor costs associated with a permanent in-house microtransit operation. In contrast, in urban regions where densely clustered populations can more efficiently use fixed-route services, a microtransit program can bloat a transit agency’s budget. Traditionally, on-demand transit services have mostly been limited to paratransit rides, which due to low ridership rates (vehicles are often largely empty) and labor costs, are some of the most expensive services to provide per passenger [2].

The success of demand-responsive transit (DRT) and microtransit programs, measured by ridership, depends in part on land use. Whereas traditional fixed-route public transit services are most efficient in densely-populated areas, DRT/microtransit programs offer a smaller-scale alternative that can prove a more cost-effective solution in lower-density suburban and rural areas [1]. There are some exceptions: DRT/microtransit programs in urban areas are sometimes designed to complement fixed-route transit by providing a first-last mile solution to connect riders to transit, or by offering supplemental services for gaps in the transit network (during off-hours, or expanding the service area) [2]. However, evidence that DRT/microtransit can increase transit ridership in cities is mixed [3]. In rural and suburban areas, however, DRT/microtransit may serve particular demographic groups, such as older adults as a form of paratransit, and commuters who can collectively share a service to a specific jobs center [1]. In areas where vehicle ownership and use is high, and the DRT/microtransit service operates in a limited area, ridership can be low [1].

On-demand microtransit programs address four aspects of equity: geographic, temporal, economic and social equity. First, microtransit expands transit service by providing flexible routes in lower-density suburban and rural areas where fixed-route services are inefficient or cost-ineffective. Second, microtransit fills gaps in transit operating hours, such as late nights or weekends. Third is economic equity. Microtransit programs are often specifically designed to facilitate commutes and provide a lower-cost alternative to private driving to get to work [2]. Lastly, microtransit placed in disadvantaged neighborhoods can improve mobility access for people who can least afford cars, or people who face mobility barriers, such as elders, low-income individuals, and people with disabilities [3]. Findings are mixed as to whether microtransit programs offer a first-last mile solution to enhance transit ridership, or replace transit trips. Ridership outcomes depend on the specific demands and existing transportation alternatives [1].

Carsharing may reduce air pollution (and thus provide public health benefits) by complementing public transit use and providing a substitute for private car-ownership. While some people use carsharing to replace public transit, more people increase their public transit and non-motorized trips (like walking and biking) after joining carsharing [1]. A case study of carsharing in Palermo showed a 25 percent reduction in particulate matter (PM10) and 38 percent reduction in carbon dioxide emissions from the shift from private to shared cars [2]. Survey-based estimates have shown that a carshare vehicle tends to replace roughly 15 private vehicles [3], [4].
Carsharing may have also provided public health benefits related to the COVID-19 pandemic. At the beginning of the COVID-19 pandemic public transit was seen as high-risk for exposure, and people with high incomes disproportionately switched from public transit to cars [5], [6], [7]. Carsharing may have provided an alternative for people without a private vehicle, as surveys show that car sharing was preferred over public transit and taxis due to reduced exposure risk [8].
Areas for further research include the impact of carsharing on access to healthcare and other basic needs and services, as well as accessibility of carsharing across groups.

The rise in ride-hail apps and Transportation Network Companies (TNCs) has had mixed effects on public health.
One benefit of TNCs is the enhanced mobility they offer to people who have difficulty driving or navigating public transit, such as seniors and people with disabilities [1], [2]. Access to transportation constitutes a significant obstacle to medical care, particularly for older, lower-income, and non-white patients [3]. Piloted TNC non-emergency transportation initiatives have shown promise in addressing this issue [3]. One study found that ridesharing services make it easier for certain groups—young, low-income, and non-critical patients—to get to the emergency room [4]. Subsidized TNC programs can also help fill gaps in public transit service, providing a way to access medical care and groceries for lower-income travelers [5]. While there is potential for the use of TNC services in transit and special needs ride programs, significant barriers remain. For example, most vehicles cannot accommodate a full wheelchair and require the use of a smartphone app to request a ride [1], [6], [7]. Additionally, drivers may lack training in assisting people with disabilities [8].
Studies have correlated TNC ridesharing availability with decreased fatalities from alcohol-related collisions, particularly if ride subsidy programs are available [9], [10]. However additional research is needed, as there is not a consensus in the literature [11].
Driver health is a significant concern when it comes to TNCs. Health risks include stress, fatigue, musculoskeletal disorders, and urinary disorders [12], and are compounded by job insecurity and the absence of traditional employment benefits [12], [13]. The absence of designated rest areas akin to taxi-stands further exacerbates these challenges [12].

Further research is needed regarding the TNCs’ potential for filling gaps in non-emergency medical transportation, as well as mechanisms to protect driver health and wellbeing.

Researchers have theorized about potential effects of Mobility-as-a-service (MaaS) programs and public health. A study in Transportation Research highlighted health concerns related to possible reductions in active transport like walking and biking, since MaaS products are based on monetizable modes of transport and emphasize door-to-door service [1]. However, another study in Research in Transportation Business & Management argues that MaaS has the potential to incentivize use of active transport [2].

There is a lack of research studying how MaaS models have impacted public health in practice.

Safety is a paramount concern - and barrier to more use - for people who want to travel by bike or scooter, motorized or not. Street connectivity and dedicated bike routes offer some of the strongest safety protections for micromobility users [1]. In places without protected infrastructure for active transportation, where cars compete for the road with all other vehicle types, the most vulnerable travelers are the people outside of automobiles. To avoid the dangers of the road, scooter users and cyclists sometimes resort to traveling on sidewalks, which in turn can create conflicts with pedestrians.Younger riders (under 18 years old) are most likely to injure themselves riding scooters [2], while pedestrians who are older adults and children are particularly at risk of sustaining injuries in sidewalk collisions [3]. Experience with micromobility, too, can impact rider behavior and safety. Regular cyclists, for example, are more likely to take longer detours to avoid dangerous routes than infrequent cyclists [4].

Payment structures may also affect how safely people use a shared mobility service. When users pay per minute, rather than by distance, they may choose to speed and compromise road safety [5]. A global study of bikeshare programs found that, in cities with bikeshare programs, bikeshare users were less likely than private cyclists to sustain fatal or severe injuries [6]. However, bikeshare users were less likely than private cyclists to wear helmets [7].

Infrastructure policies to improve road safety for micromobility users may involve establishing separate travel networks for automobiles and micromobility, or, when users share the roads, designing streets that slow motorized traffic and thus reduce the severity of crashes [8].

Ride-hail may improve general road safety by providing an alternative to drivers who would otherwise drive inebriated. A study from Great Britain found that the introduction of Uber was associated with a nine percent decrease in severe traffic-related injuries, which the authors hypothesized resulted from fewer drunk-driving trips [1]. Dills and Mulholland (2018) similarly found a decrease in drunk driving incidents, fatal car crashes, and arrests for assault and disorderly conduct with the introduction of Uber [2].

Ride-hail services can also provide an alternative travel mode for users who feel safer taking ride-hail trips than public transit [3]. However, safety concerns can also discourage people from using ride-hail services, particularly women [4].

Relative to taxis, a study in Chicago found that ride-hail trips may be more likely to result in minor injury crashes, though equally likely to result in severe crashes [5]. The authors attributed these crash differences to three potential factors: 1) drivers may be more distracted by the ride-hail app that may abruptly change routes for new passengers, 2) taxi drivers may have more experience than semi-professional ride-hail drivers, and 3) taxi driver regulations may encourage safer driving, such as limited overtime [5]. Job insecurity may explain riskier behavior on the part of ride-hail drivers; Lefcoe et al (2023) found that ride-hail drivers juggling multiple jobs engage in riskier driving behavior than full-time ride-hail and taxi drivers [6].

Passenger safety is one factor that may encourage people to use demand-responsive transit or microtransit, particularly people who are hesitant to take fixed-route public transit. In cases where walking to a fixed route transit stop can be dangerous, like in areas with limited sidewalks and high-speed arterial routes, a door-to-door service can offer a safer journey [1]. In cases where microtransit algorithms select stops for passengers to most efficiently route them, the algorithms may not incorporate local traffic and pedestrian infrastructure, leaving riders exposed to dangerous intersections [2]. Drivers may use their discretion, however, to bring passengers to a safer stopping point and ignore the algorithm’s recommendation. Even microtransit services that are not door-to-door can offer safety improvements over fixed-route services when walk routes are hazardous; microtransit programs designed around a smaller customer base can flexibly tailor their stations to ensure they are both in safe areas to wait and located close to where riders need them, and nimbly alter them based on customer feedback. Ensuring driver competency is key for safe microtransit systems; in cases where pilot programs use private contractors, rather than operators that must follow Federal Transit Administration standards, driver screening may be less stringent [2].

Mobility-as-a-service (MaaS) applications may have mixed impacts on measures of social equity. Research on the impact of digital apps to facilitate ride-hail shows they lowered transportation inequities for seniors in Japan [1], but maintained existing regional rural-urban disparities in Finland [2]. Unbanked users and those without smartphones may also be left out of use, as well as non-native English speakers, which may exacerbate barriers to mobility faced by those groups [3]. Market dominance by private MaaS companies may also lead to monopolization and price discrimination, which may impact those most reliant on public transportation [3]. Public transportation is crucial for low-income groups, who, paradoxically, find it harder to access than people in wealthier neighborhoods. While MaaS presents an opportunity to enhance accessibility and equity, it's essential for policy makers to address and eliminate barriers that maintain the status quo of exclusion for these communities [4].