Development of an experimental protocol for testing new electric personal mobility vehicles: Vehicle instrumentation, data collection procedure, data processing and analysis, and performance indicators computation
| dc.contributor.author | Violin, Alessio | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper | sv |
| dc.contributor.examiner | Dozza, Marco | |
| dc.contributor.supervisor | Rasch, Alexander | |
| dc.date.accessioned | 2020-09-04T06:53:09Z | |
| dc.date.available | 2020-09-04T06:53:09Z | |
| dc.date.issued | 2020 | sv |
| dc.date.submitted | 2020 | |
| dc.description.abstract | The growing trend toward electric personal mobility vehicles introduces new participants in the world of mobility, giving new challenges and new potential hazards to traditional road users. This fast growth has also given hard times to road regulators to follow the trend which generated a lack of rules, especially due to a lack of knowledge on the behavior of these vehicles and their users. The goal of this thesis was to develop a data collection and data analysis procedure to objectively compare these vehicles. Four vehicles were chosen to be tested: a conventional bike, an e-bike, an e-scooter, and a segway. A set of four different maneuvers was developed to simulate real-world riding scenarios: 1) a "gentle" and 2) a "harsh" maneuver to evaluate the longitudinal behavior of these vehicles, 3) a "slalom" maneuver to evaluate the lateral motion and 4) an "unexpected" maneuver to evaluate the rider's reaction after an unpredicted event. Performance indicators of stability, maneuverability, and comfort, that were to be analyzed for the four vehicles, were defined. In order to record the performance indicators, motion, steering, and speed sensors were mounted on the vehicles, while an external LIDAR sensor recorded the vehicles' trajectories. An experimental procedure capable of collecting the data for the analysis was developed. The procedure consisted of a briefing with the participant, a test phase in which the participant completed the four tasks on each of the four vehicles, and a questionnaire to be filled at the end regarding the experience during the test phase. Two pilot tests were organized in order to assess the procedure and to collect data from nine participants. The experimental procedure has demonstrated to be solid and ready for future data collections. Some guidelines have been defined after the pilot tests for what concerns the analysis of the vehicles' behavior. The segway demonstrated to be the most difficult to be used by the participants as it required longer training time and was graded as the least safe in the questionnaire. A long brake reaction time and low braking capabilities confirmed this observation. For the e-scooter, instead, high maneuverability in the slalom and fast acceleration from standing still are counterposed to low braking capabilities. Bike and e-bike, instead, were mainly graded the same according to safety. Riders exhibited excellent braking capabilities for both bicycles, that proved to be very stable and maneuverable in the longitudinal direction, while less maneuverable in the lateral direction. The short brake reaction times for both bikes resulted in a high level of maneuverability and safety. | sv |
| dc.identifier.coursecode | MMSX30 | sv |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/301631 | |
| dc.language.iso | eng | sv |
| dc.relation.ispartofseries | 2020:20 | sv |
| dc.setspec.uppsok | Technology | |
| dc.subject | personal mobility vehicle | sv |
| dc.subject | bike | sv |
| dc.subject | e-bike | sv |
| dc.subject | e-scooter | sv |
| dc.subject | segway | sv |
| dc.subject | safety | sv |
| dc.subject | stability | sv |
| dc.subject | maneuverability | sv |
| dc.subject | comfort | sv |
| dc.subject | riding performances | sv |
| dc.title | Development of an experimental protocol for testing new electric personal mobility vehicles: Vehicle instrumentation, data collection procedure, data processing and analysis, and performance indicators computation | sv |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.uppsok | H | |
| local.programme | Automotive engineering (MPAUT), MSc |