Description

Dataset for RealLaborHH (emoin).
During this project, a demand-oriented bus system using automatic driving vehicles was established in Hamburg-Bergedorf.
The project was conducted in collaboration with our transdisciplinary partners Continental AG, Dekra Automobil GmbH, EasyMile and the regional public transport 
provider (Verkehrsbetriebe Hamburg-Holstein GmbH, VHH).
In Hamburg-Bergedorf, the system was put into place and tested as a so-called living lab. It was operational from September 2021 to October 2021 and contributed to the local public transportation system.

Area of operation

The emoin project was conducted in Hamburg-Bergedorf, which is a suburb of Hamburg. 
Hamburg-Bergedorf is located in the south-east of Hamburg. 
The suburb is connected via train to Hamburg central station. 

3 autonomous driving shuttles where used to serve the area (2 in active service, 1 in reserve).
These shuttles where provided by the company EasyMile. 
Each shuttle was accompanied by bus operator from the VHH (local public transport provider), who acted as safety operator. 

The demand-oriented bus shuttle service was operational from September 2021 through the end of October.

Datatypes and datasets

This section provides some additional information on the provided files. It also explains some of the datatypes that are being used, if their meaning is not obvious.

Generic:

* All geo information is provided as wkt (well-known text) POINT (10.2163094038 53.4876823815)
* Times are local time

edges.csv

Dataset contains edges within the area of operation. Data is based on OpenStreetMap (© OpenStreetMap contributors).

• vehicleTypes: 12 characters: 0 = not allowed, 1 = allowed, U = undefined: [0] -> all, [1] -> passenger cars, [2] -> residential vehicle (12; only Teleatlas), [3] -> high occupancy vehicle, [4] -> emergency vehicle, [5] -> taxi, [6] -> public bus, [7] -> delivery truck, [8] -> transport truck, [9] -> motorcycle, [10] -> bicycle, [11] -> pedestrian'

legs.csv

A leg describes the trip between two stops.

• journeyId: a journey is a vehicle round-trip, composed of multiple legs

journeys.csv

Matches journey to vehicle.

operation-times.csv

Describes the operation times of the vehicles. Very important constraint for route planning, because no planned journey was allowed to violated the opertation times. This resulted in
many rejected passenger requests.

• fleetVehicleId: id of vehicle, matches id in vehicles.csv and journeys.csv

passenger-requests.csv

Contains all passenger request. All bookings had to be done at least 15 minutes in advance. Furhermore it was not allowed to book trips that are to far away in the future.

• state: state: 1 = accepted, 2 = not accepted, 3 = cancelled, 4 = temporarily_accepted, 5 = final
• timeOfRequest: time when the user issued the request
• searchTime: requested start time

vehicles.csv

Ids for available vehicles.

Additional attribution

Edge information of the operation area is also given. These data is based on OpenStreetMap (© OpenStreetMap contributors).