Typical and critical traffic situations with small electric delivery vehicles – indications for future automated delivery vehicles, RISE report 2022:130
This study investigated what typical traffic situations drivers of small manual delivery vehicles (MDV) are facing during their daily routes and how they handle these, sometimes critical, traffic situations. The purpose was to get an understanding of what challenges future automated delivery vehicles (ADV) may encounter and need to manage. Nine drivers of MDVs at one of Postnord’s terminals in Gothenburg, Sweden, were interviewed about their daily working tasks, their experiences of typical and critical situations and how they handle these situations. The interviews showed that many potentially critical situations were related the MDV’s relative slow speed (max 45 km/h). They could not always keep the same speed as other vehicles, which resulted in other vehicles driving closely behind the MDV and overtaking the MDV in narrow and busy roads. The interviews also revealed that the drivers often need to remove obstacles. Since an ADV cannot solve these kinds of problems like human drivers do the ADVs’ Operational Design Domain (ODD) may need to be adapted to the ADV’s capacity, e.g. being free of obstacles. The letters and packages are delivered to the addressees by the drivers. With ADVs, these “hand-over” operations need to be either taken care of by someone at the addressees or be replaced by a delivery system that does not involve the hand-over to the addressees. Another matter is that some general traffic rules are often vaguely formulated (“… adapt the speed to the bicycles…”, “…adjust the speed so there is no danger…”, “…to… in time…”) and leave much to the drivers to interpret their meanings and to act accordingly. How ADVs should comply with this kind of traffic rules could be a challenge. The drivers’ gained experiences seemed to be key to handle unforeseen events and to solve problems as they occur, for example through compensating behaviour, such as position in lane, acceleration/deceleration, steering manoeuvres etc. A “dynamic learning function” could be an important feature to implement in a future ADV-system. Overall, the interviews showed that the drivers are handling complex traffic situations and environments and that they need to manage many practical tasks to deliver the letters and packages to the addressees. Without human drivers a delivery system with ADVs would require a systems perspective throughout the whole logistics chain.