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Posted on January 8, 2019 By Luisa Reis

Robotic driverless vehicles as a supplement for public transportation system

Abstract: This article explores the importance of a current and emerging subject, Autonomous Vehicles, in the public transportation scenario. The advantages of this automated system could overcome the technical, legal and logistical challenges of its implementation, which are being improved every day, in order to provide a more efficient, environmentally cleaner and safer public transport service. The adoption of robotic driverless vehicles as on-demand feeders, running on pre-defined routes and stops, can be a solution to grant last mile transportation for commuters in remote locations, where public transportation ridership is low and operational costs are high and non-profitable. The system needs to be properly integrated with the existing mass transport service, as a supplement, not a replacement, assuring service reliability and fleet optimization. This can be guaranteed through the assistance of a mobility digital platform with trip booking and payment services.

Along the growth and development of cities, a new era for transportation has come into sight. First, the insertion of automation features for improving safety, efficiency and convenience. And now, self-driving vehicles, an advanced driver-assistance system that is emerging to revolutionize the auto sector. This intelligent system is based upon advanced radar sensors, optics, GPS, processors and algorithms that instruct the vehicle on how to react in different situations, sense its’ surrounding and undertake all aspects of dynamic driving in real time. According to SAE – Society of Automotive Engineer – there are levels and definitions of Autonomous Vehicles (AV), as presented in Figure 1 (Automated Vehicles for safety, in: NHTSA website). The stages are based on automation capabilities, intelligence level and necessity of engagement of the driver.

Although research on robotic driverless vehicles started years ago, some specialists believe that the implementation of this technology in public roads is probably five to ten years away, considering that it still has some technical, legal and logistical challenges to overcome. Since most traffic crashes are due to human error, automation could help save lives, decrease injuries and, therefore, save money, reduce traffic jams and contribute to safer roads. Besides that, these vehicles could increase mobility inclusion by facilitating the transportation of elderly, disabled and children, and benefit the environment, with efficient and electric vehicles. However, AV are more expensive upfront and they still require government regulation, insurance strategies and technological improvements to protect personal data and avoid hackers (Hendricks, D. (2016). In: Startup Grind website).

When talking about Autonomous Vehicles, the first things that come into people’s minds are cars and personal vehicles. However, this concept can also be introduced in the field of public transportation, after all this service must fulfill residents’ basic access to their needs. Aiming at an egalitarian public transportation system, last mile connectivity must be provided. This can be a challenge in some areas with large geographical range to be covered, especially in sparsely populated regions. In this situation operational costs are high, ridership is low and the wage of a driver is proportionally high in comparison to the number of passengers. Therefore, robotic driverless vehicles could be used to strengthen public transport in these areas, operating as feeders between small settlements and public transport stations, running, in the beginning, in pre-defined routes and stops (UITP Policy Brief, (2018)).

Considering the need to ensure an equitable public transportation service, robotic driverless vehicles as feeders (RDVF) can be the answer to the question: How to offer a more inclusive, cleaner and safer option, which uses roads more efficiently, free urban spaces, reduce travel times, traffic accidents, congestion and, beyond all, is financially sustainable? The solution is not simple, but aligning legal structures, fare policies and cohesive routes design, on-demand automated feeders can be implemented as a complement for public transportation, reaching less dense areas and reducing the need for a car ownership. According to Siemens Inc., one of its own research showed that if four underperforming London bus routes were replaced with an on-demand shuttle service, it would take 3 to 4 years to recover expenses and start being lucrative (Daw, Pete (2018). Cities in the Driving Seat. In: Cities Today website).

One of the main obstacles for the adoption of RDVF is to ensure suitable integration with the existing public transport system. The idea is to provide on-demand conveyance to commuters in fixed routes and stops, enhancing the trunk corridor’s area of coverage. In order to guarantee service reliability and a safe merge between traditional vehicles and AV, besides reduced waiting time, good coverage area, easy access and single ticket journey, there must be integration between transport planning efforts, local government authorities and land use policies (UITP Policy Brief, (2018)).

Another important thing to consider about RDVF is that it’s a complement for the existing public transport network, to offer more alternatives to commuters and expand the range of services. The adoption of AV in this scenario, instead of traditional vehicles, has some advantages. For instance, the reduction of CO2 emissions due to the decrease of traffic jams. It is also a positive cost efficient service, once there is no driver expense and, in general, AV have reduced costs of operation and maintenance. Beyond that, this on-demand system could be more efficient and flexible in terms of timing and zone coverage, operating during extended hours or with a higher frequency and lower costs. However, the use of AV also has some limitations. Until now, the vehicles are slow, have reduced capacity and, since it’s a novelty, public acceptance and reliance could be a challenge, as well as capital availability and willingness to invest in new technology.  Furthermore, while on one side it could help decrease the need for car ownership, on the other side it could weaken the use of means such as walking and cycling (Center for Sustainable Systems, University of Michigan (2018)).

The first step to plan this supplement RDVF is to understand residents’ needs, their origin-destination journeys and, therefore, analyze demand and mobility data to design consistent, efficient and suitable feeder routes. Then, thinking about the structure and coordination of the system, a mobility digital platform could conveniently gather trip booking, payment service and up-to-date information supply about travel options and tracking. To assure reliability, since the system has no fixed schedules, commuters will be presented with a list of travel options, depending on previous demand, minimizing wait time, when placing their request. Considering that this would be an on-demand service, the fleet optimization can be assured once RDVF is deeply immersed in the population habits, avoiding that vehicles have low ridership and allowing a shuttle to be in standby mode when not requested. (Almasi, M. (2014). Analysis of Feeder Bus Network Design and Scheduling Problems).

In the rush to acquire and disclose this innovative technology, some companies started testing vehicles models for public transportation. One interesting example is Autopiloten, the first autonomous mini-buses set to run on Sweden’s public roads, along a predefined path of 1.5 km at a speed of 20 km/h. Assuring a step-by-step approach, with defined plans for the following years, this project has the intention to mainly serve as last-mile connections, reducing barriers and implementing conditions to support the integration of mobility services (Drive Sweden, Autopilot, Kista (2017). In: Connected Automated Driving). Another interest project is HEAT (Hamburg Electric Autonomous Transportation), from HOCHBAHN: autonomous E-buses in Hamburg, Germany that can travel at up to 50 km/h. The main goal is to show that electrically powered shuttle buses can be safely integrated in urban traffic. The project has a gradual approach and, according to Henrik Falk, CEO at HOCHBAHN, the first trials on a defined test route, without passengers will begin in 2019. (Autonomous E-Buses in Hamburg (2018). In: IAV Automotive Engineering, Inc. website)

At first, since this driver-assistance system still needs further development and improvements, the idea of AV feeders running through a predefined path guarantee more safety, once physical conditions and roadway characteristics are known by the software. However, in the future, an interesting possibility would be to have routes and stops calculated dynamically, by an algorithm, in relation to requests and, then, provide a more comfortable and personalized commuting experience. Considering the intensive research in this subject, news and advances are announced on a daily basis and, soon, some cities will manage to introduce this technology in order to become safer, cleaner and have a more efficient and reliable flow of passengers and goods.



NHTSA, National Highway Traffic Safety Administration. Automated Vehicles for Safety. [Online] Available at: [Accessed 20 Sep. 2018]

Hendricks, D. (2016). 5 Reasons You Should Embrace Self-Driving Cars. [Blog] Startup Grind. Available at: [Accessed 25 Oct. 2018]

Foster, R. (2018). New report highlights advantages of AVs for first and last mile trips. [Online] Cities Today. Available at: [Accessed 02 Oct. 2018]

UITP International Association of Public Transport, (2018). Policy Brief on Autonomous Vehicles: A potential game changer for urban mobility. [PDF] Available at: [Accessed 01 Oct. 2018]

Almasi, M.; Mounes, S.; Koting, S.; Karim, M. (2014). Analysis of Feeder Bus Network Design and Scheduling Problems. The Scientific World Journal, [online] Volume 2014. Available at: [Accessed 03 Oct. 2018]

Connected Automated Driving, (2017). Autopilot, Kista from Drive Sweden. [PDF] Available at: [Accessed 24 Sep. 2018]

IAV Automotive Engineering, Inc., (2018). Autonomous E-Buses in Hamburg. [Online] Available at: [Accessed 08 Oct. 2018]

Speranza, M.; Weyland, D.; Archetti, C. (2015) On-demand public transportation. [PDF] Available at: [Accessed 9 Nov. 2018]

Center for Sustainable Systems, University of Michigan. (2018) “Autonomous Vehicles Factsheet.” Pub. No. CSS16-18. [Online] Available at: [Accessed 9 Nov. 2018]