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Research on vehicle automation has launched many years ago. Over the last decade, autonomous vehicles (AVs) have witnessed tremendous improvement because of the significant effort dedicated to AVs from both research and industry. Despite the enthusiastic speculation of AVs, little is known about the influence of vehicle automation on the public transit service. Thus, the main goal of this paper is to investigate and explore the implications of vehicle automation on the shape of public transit. In this paper three scenarios of AVs adoption are explored: autonomous vehicles are used for the entire trip (AV as a competitor to the public transportation), integrated AVs with the current public transit system (AVs are used to solve the first mile last mile problem to increase the attractive ness of the transit service), and fully autonomous buses. Finally, results show that a combination between scenario two and three is the recommended scenario in order to derive the optimal benefits of the automation technology.
Keywords: Autonomous vehicles; Autonomous buses; Public transportation
It is commonly known that mobility is affected by technology. Trough history, technology and innovation have had a significant influence on peoples’ life such as mode of transportation, residence location, and thus their lifestyle. However, the integration of these new technologies with the existing transportation service might be a harsh process that might force the old technology to diminish. Nowadays, as most of the world’s population are using smartphones, technology appears to be the most important factor that influence people’s mobility.
Over the past few years, extensive number of studies have been dedicated to vehicle automation. Additionally, AVs are already in the market and have been tested for few years now. Thus, many researchers study the chances, implications, benefits, drawbacks, public acceptance, and challenges of autonomous vehicles. AV is poised to be one of the most disruptive technologies in the near future. It is expected that the adaption and commercialization of AVs will have extensive impacts in the shape of our lives. Previous studies show that AVs will have a significant influence on the safety level, congestions, land use, level of emissions and energy consumption. Definitely, public transportations (PT) will be affected by the introduction of AVs.
Studies on AVs indicate that AVs promises many benefits such as the increase in the level of safety, the reduction in the required fleet size, and the increase in value of land use. With the anticipated benefits of AVs, it is expected that AVs have the potential to adversely impact the ridership, and viability of the public transportation service [1-3]. This impact can be considered as threat to public transit and social equity. However, limited number of studied provide insights on the relationship between AVs and public transportation service and AVs are mostly considered as a competitor to the public transit service [4,5]. Additionally, the level of mobility increases in all cities across the world. This increase is associated with increase in the levels of congestion, noise, greenhouse gas emissions, and traffic accidents. Thus, one of the most important strategies to meet urban transportation challenges and its unintended outcomes is to facilitate a shift from personal car use into public transportation use. Thus, the main goal of this study is to investigate the impact of AVs technology on the public transportation service by instigating different scenarios and provide some insights and guidelines for the future on how to integrate AVs with transit service in order to derive the optimal benefits of the new technology.
Scenario 1: Autonomous vehicles as a competitor to
public transportation (the entire trip is made by AVs)
Most of the studies in the literature focus on this scenario and
assumes that all or private car trips will be made by AVs or shared
AVs. Table 1 summarizes some of these studies and show their
assumptions and results:
As shown in Table 1, AVs will increase the VKT even if it was
used as shared mode and replace the private car trips, which in turn
means increase in the emissions, and congestion. Additionally, as
shown in the previous studies AVs have the potential to reduce the
trip cost significantly. Thus, AVs will be attractive to users because
of different reasons: for private cars users, AVs are much cheaper,
while for public transport users, AVs reduce the waiting time and
avoid the walking distance . Additionally, this reduction in the
waiting time and trip cost might attract people to make additional
trips or make longer trips, which again increase the VKT and
worsen our lives.
Scenario 2: Autonomous vehicles integrated with the
public transit service
This scenario is based on the assumption that AVs will be used
as a first mile last mile solution to the support the existing transit
system. In this case, it is assumed the AVs are owned and operated
by transit agencies or transit operators. AVs are as a first mile last
mile solution can increase the reliance and attractiveness of PT
system. However, studies on integrated AV+PT solutions have just
begun recently [7,8]. In these studies, AVs were used as an ondemand
service that allow passengers to travel from their location
to their preferred transit point. In these studies, AVs were used as
an on-demand service that allow passengers to travel from their
location to their preferred transit point.
For example, Wen J et al.  used agent-based simulation
model to study the opportunities of using shared AVs to support
public transit as a first mile- last mile solution. Additionally, the
impact of sharing of AVs was studies as three scenarios were
considered: AV operator limits the capacity to 1 (non-sharing),
sharing of 2 or 3 or 4 are investigated. Wen J et al.  built their
study based on the following assumptions:
a. As AVs are used to support the transit system, passengers
share their vehicles by default.
b. Service pricing is based on a cost based fare structure
that include three main costs: based fare to discourage people
of making short trips that can be made by other modes, per unit
distance, and per unit time fare similar to the dynamic pricing.
c. AVs are assigned dynamically to satisfy constraints such
as maximum waiting time and detour time with the objective of
minimizing costs in terms of total travel times for all travelers.
d. AVs with a maximum capacity of 4 passengers is
Results show that:
e. The total VKT increase with the increase in the fleet size
which in turn means higher operating costs. This increase is due to
the idle trips because of the rebalancing strategy to provide better
service. Thus, the fleet sizing problem is a trade-off between the
benefits to the travelers and the cost to the operators.
f. Sharing has a significant impact on the system
performance. Results show that the required AVs can be reduced
by more than half when a maximum of 4 passengers can be shared.
Thus, in this scenario, VKT increase with the increase in the
fleet size. However, as in this scenario the required fleet size
is way smaller than the required fleet size to serve the entire
trips in scenario , the increase in the VKT in scenario 2 is much
smaller than the increase in the VKT in scenario 1. Thus, it can be
concluded that this scenario is much better in our lives.
Scenario 3: Application of vehicle automation in public
transportation (Adaption of Autonomous buses)
Research on automation of buses is rare and most of these
studies are published in 2020. However, there are many benefits
of using autonomous buses as follows:
a. On the era of autonomous buses, it is anticipated that
passengers could expect to receive accurate information about
b. Vehicle automation will exclude the influence of driver
(driving style, acceleration or deceleration, good or bad driver) on
the bus performance.
c. Additionally, autonomous buses will not rely of drivers
which means elimination of the wage costs of bus drivers.
d. Reduction or elimination of the fuel costs because of the
expectations that autonomous vehicles will use electric engines.
Additionally, vehicles are the most expensive component on
the transit system. However, vehicles and drivers are connected to
each other because the vehicle remain idle in case of driver’s break
time which reduce the vehicle utilization. Thus, the efficiency of
the current system is usually between 60 to 70% which means that
the vehicle does not generate income for almost one third of the
working time because of the rest time. For example, Nagy Horváth
 studied the implications of adaption of autonomous buses for
the city of Eger, Hungry which is a medium sized city with about
50.000 inhabitants based on the following assumptions:
a. Autonomous buses were considered as not requiring
inter-job breaks and can be used from the start to the end of the
b. The calculations in this study were made using the
software PTV VISUM to create block system under specified
Results show that:
c. Assuming the continuous service provided by
autonomous buses, only 35 buses are enough to provide the
service instead of the 37 bus in the current condition. Additionally,
the required number of autonomous buses can be reduced to 32
buses to provide the same service in case of optimizing the bus
d. In addition to the savings in the required number of
buses, autonomous buses provide significant savings in the
e. Financial analysis show that although the purchasing
cost of autonomous buses is much higher than the conventional
human driven bus, the operating cost of ABs is much lower than
human driven buses as follows:
a. The operating costs of the current system are almost €
10 200 per day or € 3.08 million annually.
b. The daily operating cost of autonomous buses with the
current schedule is € 6 900 or € 2.08 million annually.
c. In the case of schedule optimization, the daily operational
costs of autonomous buses is € 6 644 or € 1.9 million annually.
d. It means that autonomous buses have the potential to
reduce the operating costs by almost 30%.
e. Additionally, the financial analysis shows that the bigger
vehicle purchase cost will be equalized (breakeven) by operational
cost savings in about 5 years so the system will be cheaper than
the current system.
Additionally, Dai et al.  studies a new operating strategy
that can deal with the sudden changes in demand (demand
responsive strategy) for one-way loop high frequency bus line
with 10 equally spaced stops. What is unique on this study is that
it considers mixed fleet of human driven and autonomous buses
with different penetration rates: 0%, 50%, and 100% autonomous
buses. Additionally, this study considered two demand patterns:
high crowdedness and low crowdedness. While the term “dynamic
headway” is a common term in transit as transit agencies uses
dynamic headways to serve the demand during the peak and offpeak
periods, the term “dynamic capacity” was used for the first
time in 2020 by Dai et al. .
Dai et al.  used the following assumptions in their study:
a. The dynamic capacity is obtained by assembling and/or
dissembling multiple autonomous minibuses at terminals.
b. Autonomous buses have a capacity of 6 passengers, and
the capacity of the human driven bus is 45 passengers.
c. A maximum of 5 autonomous buses can be assembled
d. Considering a single line.
e. Autonomous buses can self-adjustment their headway
based on the headways of the forward and backward buses by
adjusting their travel time.
Results show that:
a. Providing dynamic headway and dynamic capacity have
the potential to provide high level of service as it reduces the
average passenger waiting time
b. The dynamic scenario (dynamic headway and capacity)
reduce the headway deviation. Additionally, this deviation
diminishes with the increase the level of penetration of
c. Autonomous buses increase the bus capacity utilization.
Thus, the introduction of autonomous buses will increase the bus
In conclusion, automation of buses has many benefits to
passengers (reduce the average waiting time) which increase
the attractiveness of the transit service. Additionally, agencies
will benefit from the introduction of autonomous buses as it will
increase the vehicle utilization, attract more people and increase
their revenue. Additionally, this solution might increase the
VKT slightly because of the increase in the number of required
buses. On the other hand, this might not be harmful because of
the adaption of electric and autonomous buses. In this scenario,
the first mile last mile problem still exists. Thus, the use of a
combination of the two scenarios two and three in order to
derive the optimal benefits of the automation technology. In this
combined scenario, shared autonomous buses will be used as a
first mile last mile on demand service to support the public transit
system and transit lines will switch gradually from human driven
buses to autonomous buses. Additionally, the use of electric buses
is a must to increase the economic and social value of transit [11-
The introduction of autonomous vehicles is expected to have
a significant influence on the entire transportation system. In
this paper three scenarios of adaption of autonomous vehicles
are discussed. Figure 1 summarizes these scenarios and it is
recommended to use a combined scenario to maximize the gain
and derive the optimal benefits of the automation technology.
In this combined scenario, shared autonomous buses will be
used as a first mile last mile on demand service to support the
public transit system and transit lines will switch gradually from
human driven buses to autonomous buses. Additionally, the use of
electric buses is a must to increase the economic and social value
of transit. Additionally, it must be mentioned that regulations will
play an important rule on the impact of vehicle automation on
public transportation. Additionally, the public preference will play
a significant rule on which scenario to people will adopt.