A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging SituationsShow others and affiliations
2021 (English)In: IEEE Transactions on Intelligent Transportation Systems, ISSN 1524-9050, E-ISSN 1558-0016Article in journal (Refereed) Accepted
Abstract [en]
Platooning refers to a group of vehicles that--enabled by wireless vehicle-to-vehicle (V2V) communication and vehicle automation--drives with short inter-vehicular distances. Before its deployment on public roads, several challenging traffic situations need to be handled. Among the challenges are cut-in situations, where a conventional vehicle--a vehicle that has no automation or V2V communication--changes lane and ends up between vehicles in a platoon. This paper presents results from a simulation study of a scenario, where a conventional vehicle, approaching from an on-ramp, merges into a platoon of five cars on a highway. We created the scenario with four platooning gaps: 15, 22.5, 30, and 42.5 meters. During the study, the conventional vehicle was driven by 37 test persons, who experienced all the platooning gaps using a driving simulator. The participants' opinions towards safety, comfort, and ease of driving between the platoon in each gap setting were also collected through a questionnaire. The results suggest that a 15-meter gap prevents most participants from cutting in, while causing potentially dangerous maneuvers and collisions when cut-in occurs. A platooning gap of at least 30 meters yield positive opinions from the participants, and facilitating more smooth cut-in maneuvers while less collisions were observed.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2021.
Keywords [en]
cooperative adaptive cruise control., cut-in, Driving simulator, highway platooning, Vehicle to vehicle communications, Highway merging, On-ramp, Public roads, Simulation studies, Traffic situations, V2V communications, Vehicle automations, Road vehicles
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-52104DOI: 10.1109/TITS.2020.3040085Scopus ID: 2-s2.0-85098774184OAI: oai:DiVA.org:ri-52104DiVA, id: diva2:1522484
2021-01-262021-01-262025-09-23Bibliographically approved