Studies conducted using app-based ridesharing suggest it can reduce road congestion and carbon emissions in urban areas, complement public transport services, and be used as the first and last miles of journeys.
However, ride-hailing services remain controversial when it comes to their effects on traffic congestion, partly because rebound effects nullify any savings in CO2 emissions that are expected from them.
Ridesharing services have long been debated as to their impact on traffic congestion. Some studies indicate an increase in congestion while other show no impact or even potential benefits, reflecting different research designs and methodologies that produce inconsistent results.
Space, time of day/week differences, and choice of congestion measurement metrics could all play an impactful role in distorting results. A study by Rayle et al. [Reference Rayle Dai Chan Cervero and Shaheen 31] is one example. They conducted intercept surveys which only captured TNC passenger trips – and not taxi or other types – thus missing most ridesharing trips altogether.
Unaccountable results could also be attributable to studies considering only single-occupant private hire vehicles and failing to take into account trip chaining, sharing and deadheading (i.e. passengers taking ridesharing services between home and work or vice versa). TNC trips’ negative effect on public transit (which tends to be less congested) may negate congestion mitigation benefits provided by ridesharing.
Public Transport Ridership
Some studies indicate that ride-hailing services contribute to traffic congestion. Although increased private hire vehicle usage is one factor, it cannot explain all of the increased congestion seen in cities like London. Furthermore, most before-and-after studies fail to take into account other important aspects such as population growth, substitution of personal car usage with ride-hailing, deadheading etc.
These studies overlook rebound effects that could counteract or negate any traffic congestion mitigation achieved through shared rides, as evidenced by one from New York City showing that most e-hailed trips shifted away from yellow taxis were not shared and thus did not contribute to decreased congestion levels.
Spatial variations among urban areas where ride-hailing services operate could also have an immense effect on their congestion impacts, as a strong network effect in a major city may quickly cause its market share to grow beyond initial expectations.
Private Vehicle Ownership
As ridesharing services gain in popularity, some studies have speculated that they contribute to traffic congestion. Unfortunately, such studies often lack comprehensive consideration of factors which could potentially influence traffic such as population growth, replacement of personal car usage with ridesharing services and deadheading.
Further, many studies fail to account for spatial variations in travel patterns. For instance, research has indicated that lower income passengers are more likely to share rides – possibly because they must make multiple journeys to work daily.
Studies have also demonstrated that people who prioritize their time more heavily tend to use ride-sharing services. Therefore, when assessing the effect of ride-sharing services on urban mobility and traffic congestion it is crucial to take these factors into account in order to identify effective policy solutions which mitigate its negative consequences for traffic congestion reduction.
Research on ridesharing largely focuses on its negative externalities, such as congestion. But this type of investigation must also account for multiple factors and take spatial differences into consideration.
A large city may experience TNC monopoly due to the speed with which one company gains market share and makes entry difficult for new competitors, potentially shifting rides from shared trips towards nonshared ones.
TNCs may also eliminate the need for trips in personal vehicles to search for parking spots, thus decreasing VMT. Although this aspect of ride-hailing has yet to receive significant consideration in literature, more should be made of this aspect as it could provide more accurate conclusions regarding its effects on urban mobility and traffic sustainability, while further helping us understand its complementarity with public transit systems as well as its role in decreasing vehicle ownership.