Autonomous mobility on demand

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Autonomous mobility on demand (AMoD) is a service consisting of a fleet of autonomous vehicles used for one-way passenger mobility. An AMoD fleet operates in a specific and limited environment, such as a city or a rural area. [1] [2]

Contents

Origin

Mobility on demand (MoD)

The idea of developing a form of passengers transportation based on shared vehicles rather than private cars comes from the research in the field of sustainable mobility, which aims at creating an efficient and environmentally-friendly way for people to move. [3] As at the end of April 2022, the number of cars in the world has reached 1.1 billion, meaning that there is approximately a vehicle for every seven people on earth. [4] Such large number of private vehicles in the streets causes several issues, namely a huge release of greenhouse gases and request for fossil fuels, since most cars are still fuel-powered, [4] as well as infrastructural issues such as roads congestion and parking spots lacking. [5] The concept of mobility-on-demand (MoD) addresses these issues providing a potential solution to them: in MoD, people do not need a private vehicle to travel. Mobility on demand is in fact a service in which shared vehicles are used for passenger mobility in one-way trips. The adoption of mobility-on-demand services has the potential of increasing the utilization rate of vehicles, which for private cars is on average below 10%, [6] thus allowing to transport the same number of people with a lower number of vehicles. In this way, both the congestion and the pollution in the cities can be reduced. [7] The service offered in the cities by taxi companies, which nowadays has been taken over also by other providers such as Uber [8] and Bolt, [9] is itself an expression of mobility on demand: upon request, a driver goes to pick up passengers to drive them to their desired destination, and then goes on with the next demand. The other manifestation of the concept of mobility on demand is the car-sharing, which allows people to rent a vehicle, drive it to their destination and then leave it there, so that it remains available for the next customers. The idea of car-sharing has become popular among the public since the end of 20th century, [10] and is gaining more and more success in the present years, with companies such as ShareNow [11] and Enjoy [12] that are delivering it all over the world. [13] A big drawback of mobility on demand systems is that an imbalance is periodically introduced in the system, consisting in an accumulation of vehicles in some areas and a lack in others, due to the fact that some zones are more popular than others. Imbalance makes the service inefficient, because customers are less likely to find a vehicle close to them. [14]

Autonomous cars in MoD

EasyMile shuttle, Sweden (2016) EZ10 Kista 160425 1.jpg
EasyMile shuttle, Sweden (2016)

The advent of the technology of self-driving cars has recently started to revolution the concept of mobility-on-demand, turning it into autonomous mobility on demand (AMoD). An AMoD fleet is composed of vehicles of level 5 autonomy, [15] controlled in a centralized way. The communication with the customers happens via phone applications, where they can request a vehicle in a precise location, which then picks them up and drives them to their desired destination. Many academic researchers and market players are focusing on the development of AMoD systems, the main companies that are already developing fleets of vehicles for AMoD are shown in the following table.

CompanyConcept
Zoox fleets of autonomous shuttles for urban passenger transportation [16]
EasyMile fleets of autonomous shuttles/tow tractors to transport passengers/goods for short/long distances [17]
Cruise fleets of autonomous electric cars/shuttles for urban passenger transportation [18]
Waymo fleets of autonomous cars/trucks to transport passengers/goods for short/long distances [19]
AutoX fleets of autonomous robotaxis for urban passenger transport [20]

Control

Different aspects of a fleet of vehicles used for AMoD are accurately controlled for it to function in a proper way. [1]

Routing

Waymo car prototype, California (2017) Waymo self-driving car front view.gk.jpg
Waymo car prototype, California (2017)

Being the vehicles autonomous, an accurate control of their trajectories is operated by providing them with an optimized routing system. [21] The routes of the cars are calculated in real-time according to specific objectives defined in the design phase of the fleet control algorithms. Those aim at minimizing the distance travelled or the time needed to reach a specific location, so they need to take into account different metrics such as the traffic in the streets and the condition of the roads. [22]

Dispatching

A crucial aspect of AMoD technology is the assignment of vehicles to open customer requests. To take the dispatching decisions, the controller first registers the real-time positions of all the vehicles and open requests. Different strategies can be adopted to perform the assignments, and the choice among them affects the complexity of the fleet control and the effectiveness of the whole system. [22] An option is to assign customers to the closest vehicle following a first come, first serve rule, which is easy in terms of computational time but only leads to suboptimal solutions. [22] [23] For this reason, researchers are proposing approaches based on the mathematical programming. [22] Those consist in formulating an assignment problem by defining the cost value of each potential vehicle-customer assignment and the constraints present in the system. [24] The problem is then solved using an algorithm for the optimal resource-task assignment. [24] The cost value of each possible assignment can be computed basing on different metrics. Most of the dispatching strategies proposed up to now are based on one of the following parameters or on a combination of some of them: [24]

Rebalancing

The stochasticity of the customer demand makes AMoD systems unstable, causing them to become unbalanced after some time. This results in an uneven distribution of resources along the network, which sensibly affects the quality of the service. For this reason the empty vehicles of an AMoD fleet are periodically redistributed in their whole operating area, for them to be available where they will be most needed in the future. [1] When planning the rebalancing, it is necessary to take into account the fact that moving empty vehicles has a cost. Besides, this action contributes to the congestion of the streets. For these reasons, to compute the optimal rebalancing decisions an accurate trade-off between the different cost factors is operated. [25] Various strategies can be adopted to decide where vehicles should be rebalanced: [26] [27]

Benefits

Sustainability and traffic reduction

The introduction of AMoD fleets constitutes an alternative to the usage of private cars for passenger mobility, so it has the potential to sensibly reduce the number of vehicles in the streets. This has the effect of decreasing both the congestion in the streets and the emissions of greenhouse gases, besides bringing an increase in fuel efficiency. [6]

Safety

Evidence shows that the vast majority of road accidents in the world is caused by human errors. [28] The adoption of self-driving vehicles would then eliminate the human risk factor from car trips, thus sensibly decreasing the probability of an incident to occur. [29]

Automatic rebalancing

The biggest limit that characterizes MoD systems is the problem if the imbalance of resources caused by uneven demand across the area serviced. The introduction of self-driving vehicles provides a solution to this issue, in fact the autonomous drive technology allows the fleet to periodically rebalance itself without the need of human intervention. [1] This brings an increase in the quality of the service, in fact customers are more likely to find cars when and where they need them. [1]

Accessibility

AMoD systems allow mobility for non-drivers, and give travellers the possibility to employ the time of the ride in useful ways, or even to relax. [30] The absence of the drivers grants the same availability of the service during all the hours of the day and night: the only interruptions of the service happens in case of faults of the vehicles, or when they are being refueled. [30]

Limits

Cost

In order for an AMoD service to start making the difference in terms of congestion and pollution mitigation and safety, it needs to be adopted in large-scale. Before a large number of people can start preferring such kind of system to their private cars, it is necessary to optimize AMoD fleets and infrastructures production and management in order for it to be advantageous in terms of costs compared to owning a vehicle. [30]

Responsibility

The emerging world of self-driving vehicles is full of open ethical questions that make the adoption of such technology complicated even from a moral point of view: who should be held accountable for accidents involving self-driving cars?When an autonomous vehicle is in a harmful situation when it is inevitable to harm somebody, how should it decide who to save? [31] [32] Agreed solutions to these questions do not yet exist in the scientific community, but researchers and legislators are working to produce regulations on the matter. [33] [34]

Safety

Autonomous vehicles have the potential of eliminating road accidents caused by human errors, but they are not exempt from concerns themselves. Failures might occur in their system and potentially harm passengers or other road users. [30] They could also be subjected to criminal activities such as hacker attacks that could affect their safety and performance. [30]

Open challenges

Ride sharing

The possibility of sharing AMoD rides between strangers who have to travel along the same route would have the effect of improving both the quality of the service, by reducing waiting and travel times, and decreasing the cost, because the price of the ride would be divided between the passengers. Moreover, less vehicles would be necessary to fulfill the customer demand, bringing benefits also in terms of sustainability and traffic reduction. [35] Researchers are thus working to develop control systems able to combine the needs of different customers to better satisfy all of them and optimize the whole system. [35]

Electric vehicles

A further advancement in the technology of AMoD, that some companies such as Cruise are already working on, would be to use fleets of electric vehicles. This would bring a huge advantage in terms of sustainability, but introduces an additional complexity in the system. [36] Charging an electric vehicle, in fact, takes longer than re-fuelling a petrol car, so the charging aspect needs to be optimized to see the benefits of such system. [36]

See also

Related Research Articles

<span class="mw-page-title-main">Self-driving car</span> Vehicle operated with reduced human input

A self-driving car, also known as an autonomous car (AC), driverless car, or robotic car (robo-car), is a car that is capable of traveling without human input. Self-driving cars are responsible for perceiving the environment, monitoring important systems, and control, including navigation. Perception accepts visual and audio data from outside and inside the car and interpret the input to abstractly render the vehicle and its surroundings. The control system then takes actions to move the vehicle, considering the route, road conditions, traffic controls, and obstacles.

<span class="mw-page-title-main">Carsharing</span> Model of car rental where people rent cars for short periods of time

Carsharing or car sharing or car clubs (UK) is a model of car rental where people rent cars for short periods of time, often by the hour. It differs from traditional car rental in that the owners of the cars are often private individuals themselves, and the carsharing facilitator is generally distinct from the car owner. Carsharing is part of a larger trend of shared mobility.

Vehicular communication systems are computer networks in which vehicles and roadside units are the communicating nodes, providing each other with information, such as safety warnings and traffic information. They can be effective in avoiding accidents and traffic congestion. Both types of nodes are dedicated short-range communications (DSRC) devices. DSRC works in 5.9 GHz band with bandwidth of 75 MHz and approximate range of 300 metres (980 ft). Vehicular communications is usually developed as a part of intelligent transportation systems (ITS).

<span class="mw-page-title-main">Transportation demand management</span> Policies to reduce transportation demands

Transportation demand management or travel demand management (TDM) is the application of strategies and policies to increase the efficiency of transportation systems, that reduce travel demand, or to redistribute this demand in space or in time.

<span class="mw-page-title-main">Vehicular automation</span> Automation for various purposes of vehicles

Vehicular automation involves the use of mechatronics, artificial intelligence, and multi-agent systems to assist the operator of a vehicle such as a car, lorries, aircraft, or watercraft. A vehicle using automation for tasks such as navigation to ease but not replace human control, qualify as semi-autonomous, whereas a fully self-operated vehicle is termed autonomous.

<span class="mw-page-title-main">Shared transport</span> Demand-driven vehicle-sharing arrangement

Shared transport or shared mobility is a transportation system where travelers share a vehicle either simultaneously as a group or over time as personal rental, and in the process share the cost of the journey, thus creating a hybrid between private vehicle use and mass or public transport. It is a transportation strategy that allows users to access transportation services on an as-needed basis. Shared mobility is an umbrella term that encompasses a variety of transportation modes including carsharing, Bicycle-sharing systems, ridesharing companies, carpools, and microtransit.

<span class="mw-page-title-main">Waymo</span> Autonomous car technology company

Waymo LLC, formerly known as the Google Self-Driving Car Project, is an American autonomous driving technology company headquartered in Mountain View, California. It is a subsidiary of Alphabet Inc, the parent company of Google.

<span class="mw-page-title-main">Last mile (transportation)</span> Last leg of the movement of people or goods from hubs

In supply chain management and transportation planning, the last mile or last kilometer is the last leg of a journey comprising the movement of passengers and goods from a transportation hub to a final destination. The concept of "last mile" was adopted from the telecommunications industry, which faced difficulty connecting individual homes to the main telecommunications network. Similarly, in supply chain management, last-mile describes the logistical challenges at the last phase of transportation getting people and packages from hubs to their final destinations.

<span class="mw-page-title-main">History of self-driving cars</span> Overview of the history of self-driving cars

Experiments have been conducted on self-driving cars since 1939; promising trials took place in the 1950s and work has proceeded since then. The first self-sufficient and truly autonomous cars appeared in the 1980s, with Carnegie Mellon University's Navlab and ALV projects in 1984 and Mercedes-Benz and Bundeswehr University Munich's Eureka Prometheus Project in 1987. Since then, numerous major companies and research organizations have developed working autonomous vehicles including Mercedes-Benz, General Motors, Continental Automotive Systems, Autoliv Inc., Bosch, Nissan, Toyota, Audi, Volvo, Vislab from University of Parma, Oxford University and Google. In July 2013, Vislab demonstrated BRAiVE, a vehicle that moved autonomously on a mixed traffic route open to public traffic.

A robotaxi, also known as robo-taxi, self-driving taxi or driverless taxi, is an autonomous car operated for a ridesharing company.

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Torc Robotics (Torc), an independent subsidiary of Daimler Truck, is an American autonomous truck company headquartered in Blacksburg, Virginia, with operations in Albuquerque, New Mexico; Austin, Texas; and Stuttgart, Germany. Torc is testing autonomous trucks in Virginia, New Mexico, and Texas and is taking a pure play approach to commercialization – focusing at first on one platform in one region.

<span class="mw-page-title-main">Microtransit</span> Form of demand-responsive transport with no fixed routes or schedules

Microtransit is a form of bus demand responsive transport vehicle for hire. This transit service offers a highly flexible routing and/or highly flexible scheduling of minibus vehicles shared with other passengers. Microtransit providers build routes ad-hoc exclusively to match only each demand (trip) and supply and to extend the efficiency and accessibility of the transit service. Possible pick-up/drop-off stops are restricted, and transit can be provided as a stop-to-stop service or a curb-to-curb service.

Cruise LLC is an American self-driving car company headquartered in San Francisco, California. Founded in 2013 by Kyle Vogt and Dan Kan, Cruise tests and develops autonomous car technology. The company is a largely autonomous subsidiary of General Motors.

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References

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  35. 1 2 Tsao, Matthew; Milojevic, Dejan; Ruch, Claudio; Salazar, Mauro; Frazzoli, Emilio; Pavone, Marco (May 2019). "Model Predictive Control of Ride-sharing Autonomous Mobility-on-Demand Systems". 2019 International Conference on Robotics and Automation (ICRA). Montreal, QC, Canada: IEEE. pp. 6665–6671. doi:10.1109/ICRA.2019.8794194. ISBN   978-1-5386-6027-0. S2CID   53443981.
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