Concept of the Future Operations Control Center

This chapter will clarify how automated shuttle buses affect the functional areas and tasks of an OCC and what opportunities the OCC has to increase the safety and service level of automated shuttle buses. Finally, a rough concept of the OCC is presented.

4.1 Factors Influencing the Future Operations Control Center

In addition to the typical tasks of an OCC, such as monitoring regular operations, fault and emergency management, dynamic passenger information and passenger communication, dispatching of on-demand services, performance and quality controlling (Berger et al. 2015, 4;

Janecke et al. 2005, 167-174; The World Bank Group 2019), future OCCs must meet the challenges of automated traffic and ensure its safety. In this context, the main challenges or tasks in automated driving can be classified as follows: road detection, lane detection, vehicle detection, pedestrian detection, drowsiness detection, collision avoidance, and traffic sign detection for which numerous methods such as machine learning and V2X communication exists (Muhammad et al. 2020, 2). The control center is to support the automated shuttle buses with human assistance where their own sensors and AI reach their limits, thus forming an essential fallback level in the system. The German government’s latest draft law on autonomous driving also already specifies a number of requirements. The OCC, as the technical supervisor, must be able to access the vehicle at any time, e.g., to deactivate it or to carry out necessary releases (BMVI 2021, 20). For this purpose, the remote operator must be able to view the required data in the form of a video stream of the bus environment or the bus interior or information from the infrastructure in real time at any time and use it for a quick assessment of the traffic situation.

The teleoperation approach offers the remote operator this possibility (Neumeier et al. 2018, 1-2). This can be a fully featured remote cockpit that replicates the design of a bus driver’s seat, including the steering wheel and accelerator and brake pedals. It can also be a simpler setup in the form of a computer, monitors, camera and microphone to perform less complex control functions (driving maneuvers), such as stopping the vehicle or giving the command to proceed.

The focus here is on decision support for the AI, especially in the areas of the more complex traffic circles or traffic lights, when, for example, V2I communication should fail and, due to adverse weather conditions, automated detection of the traffic light phase using the optical sensors is subject to high uncertainties. The image display can be done e.g. on multiple monitors or by means of augmented reality. The operator can be supported by intelligent predictive assistance systems that compensate for the possible latency-related delays (Davis, Smyth, and

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McDowell 2010, 4). Thanks to today’s mobile phone (cellular) network, data transmissions over long distances and with low latency are well feasible (T-Sytems 2021; Inam et al. 2016, 1).

Providers for teleoperation systems like Phantom Auto or Ottopia in cooperation with T-Systems offer software solutions to monitor fleets or draw a path for a vehicle to follow (Ottopia 2021;

Phantom Auto 2021). If necessary, the operator can even take over the vehicle steering manually (Ottopia 2021; Phantom Auto 2021). Other prominent examples of teleoperation application providers such as Fernride (Fernride 2021), Cognicept (Cognicept Systems 2021) or Voysys (Voysys 2021) also offer remote control solutions to increase the availability of different types of vehicles within logistic processes.

The elimination of the bus driver as the safety and contact person in the bus also brings passenger communication to the foreground as one of the central tasks of the OCC (Jaap et al.

2015, 14). This requires an audio-visual interface for passenger communication in the control center.

4.2 Requirements for the Future Operations Control Center

In the following, the essential functional areas, such as operational handling, measures to maintain safety and service tasks of a conventional control center, are supplemented by the tasks and requirements caused by the automated shuttle buses and presented in Table 1. Tasks that remain largely unchanged or have little relation to operational handling are omitted from the overview. The functions and the necessary information flows between the control center and the automated shuttle bus were determined primarily from the perspective of a remote operator.

Task Requirement Information needs¹ other information should be indi-cated, e.g. status of routes in a transport lines; vehicle technical sta-tus; vehicle driving mode; vehicle speed; door status; vehicle occupancy (capacity); battery status, range, ex-pected charging time ope-rations; customer requests and data (GPS position, direction of travel,

Biletska, Beckmann et al. sha-dow, or better as a digital twin

as for monitoring of regular operation;

status data from the infrastructure (technical faults); reporting data from the infrastructure (congestion infor-mation, traffic density, etc.)

emergency

management automated communication with the traffic management center and the emergency service

operator gives information, in-structions, etc. to passengers through an audio-visual interface in the shuttle bus

decentralized Environmental Notifi-cation Messages (DENM); audio and video stream from vehicle inside and outside; operational status: vehicle occupancy, speed, door status, po-sition and range; technical status:

connection status, sensor status, number and location of technical faults remote control

of the vehicle remote control maneuver-based (provide a new path for the ve-hicle) or fully manual and then return control (remote cockpit for teleoperation needed)

remote operation by approval (e.g. continuation of the ride after and rear camera) and from inside the bus; additional information from infra-structure such as images from came-ras or sensor data; operational status:

vehicle occupancy, speed, door status, position and range; technical status:

connection status, sensor status, number and location of technical faults infrastructure

monitoring big Data algorithms dynamic interactive map

manual access to the individual infrastructure objects and their data images of complex traffic junctions (traffic circles, intersections); traffic density; charging infrastructure

infrastructure

control dynamic interactive map of infra-structure objects, including bus routes

coordinated prioritization of traffic flow by influencing the signaling systems

as for monitoring of the infrastructure;

relevant information from other au-thorities (emergency service)

passenger

safety answering of the emergency calls rapid alerting of the authorities

alarm plans, bidirectional video and audio transmission

Future Operations Control Center of Automated Shuttle Buses

communication answering requests from bus, stops, etc.

voice communication preferred, but also app messages possible

fault messages and causes; actual and target timetable, deviations; forecast (e.g. estimated time of arrival, avai-lable connections, etc.)

Table 1. Key tasks of an operations control center for automated shuttle buses and requirements as well as concrete information needs

The key requirements for a future OCC are thus the technical interfaces and a user (operator) friendly interface for rapid situation assessment and remote control of automated shuttle buses when needed, communication with passengers especially in emergency situations, stronger networking with the infrastructure, and cyber security.

While currently the information transmission from the bus is mainly done as predefined text blocks or voice calls, the OCC must be able to process large data (video) streams in the future.

In the interviews with an operator of a transport company, for example, there were concerns about the permanent use of VR glasses because of the possible stimulus overload. When designing the control center, attention should be paid to reducing the workload of employees (especially when dealing with faults and smaller incidents). There is also a great fear of manipulation and hacker attacks, both on the part of the providers and operators of automated shuttle buses and on the part of potential users. For this reason, as well as for economic reasons, it is desirable that the vehicle can operate as autonomously as possible or with automated support from infrastructure, as described in chapter 2. Nevertheless, the level 5 of automation should not be waited for and a balance must be found between the minimum possible need for intervention in the vehicle control and the guarantee of safe operation. An obvious solution therefore is to support the sensor detection of the shuttle bus by V2X technologies. If this is not sufficient, the operator can manually assess the situation and issue commands such as the release to continue driving. If a driving maneuver is required to avoid an obstacle, the driving route can be executed by entering certain parameters or by drawing it on an interactive map.

The role of the charging infrastructure and innovative concepts such as inductive charging while driving will increase significantly, so the operator will need the related displays (e.g. battery status) and control instruments.

In the future, the control center operators can be supported by the cloud-based assistance systems, up to the complete takeover of the vehicle control by the AI, which analyzes diverse information of the infrastructure and the individual vehicles and gives maneuver instructions to the vehicle (cloud-based driving). Thus, human teleoperators could be replaced by automated teleoperation through cloud-based AI services. Figure 1 illustrates the role of the OCC for monitoring and controlling automated shuttle buses and places it in the overall ecosystem.

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Figure 1. Digital ecosystem of the future operations control center