Background Trials with automated mini buses (AV shuttles) are going on in many cities. According to game-theoretic reasoning, in mixed traffic normal road users will soon take advantage of the defensive driving style of the AV shuttles, and may eventually totally block their accessibility (Camara et al., 2018; Michieli & Badia, 2018; Millard-Ball, 2018). So far there are few studies on the interaction between AV shuttles and ordinary road users. The present study is probably the first to look at changes in interaction patterns with AV shuttles in real traffic over time, making it possible to empirically test the predictions based on game theory. Method In order to study ordinary road users’ interaction with AV shuttles, and whether interaction patterns change over time, evidence from two Norwegian pilots at Kongsberg and in Oslo, have been collected. Field surveys and video recordings have been conducted at both places and repeated over several months to measure any changes in behaviour. Results Results from survey analyses show very small changes in pedestrians’ interactions with the AV shuttles over time, whereas cyclists seem increasingly to take advantage of the defensive driving style of the AV shuttles. Video data will be analyzed during spring 2020 and results will be presented at the conference. Possible mechanisms producing the differences between cyclists’ and pedestrians’ interactions with the AV shuttles, will also be presented and discussed at the conference. Conclusions Survey results show that pedestrian interaction with AV shuttles do not confirm with the hypothesis based on game theoretic modelling. However, cyclist interaction seems to change over time in line with the game theoretic expectations.@en

The current paper presents the results of behavioural observations in a field experiment with automated shuttles in Oslo, Norway. Video observations were conducted at five fixed locations along a challenging 1.2 km automated shuttle line with varying traffic conditions. Observed interactions between vulnerable road users and automated shuttles were coded using a predefined codebook, which allowed a structured quantitative analysis. The paper identified several potentially risky types of situations in which the automated shuttles did not always behave according to the traffic rules. Generally, the automated shuttles failed to give way to pedestrians at pedestrian crossings in 26%–50% of the interactions. Right-turning shuttles failed to yield to cyclists going straight in 38% of the interactions at observation Site 1 (the only location where the automated shuttle takes a right turn). In majority of same direction interactions between cyclists and automated shuttles, the interactions resulted in the cyclist overtaking the automated shuttle, usually on the left-hand side. Generally, the paper found little evidence of road users trying to bully or otherwise take advantage of the defensive driving style of the automated shuttles and identified only a limited number of interactions in which a vulnerable road user behaved ignorant or aggressive towards the automated shuttles. In addition, the paper found very little indication of temporal effects that suggest changes in the interaction patterns over time.@en

In order to overcome the shortcomings of crash data a number of surrogate measures of safety have been developed and proposed by various researchers. One of the most widely used temporal indicators is time-to-collision (TTC) which requires the road users to be on a collision course. Road users that are strictly speaking not on a collision course actually might behave and take evasive actions as if they were, thus indicating that such near-miss situations might also be relevant for safety analysis. Taking that into account, a more flexible indicator T₂, which does not require the two vehicles to be on a collision course, describes the expected time for the second road user to arrive at the conflict point. Recently extreme value theory (EVT) offering two approaches, block maxima (BM) and Peak over Threshold (POT), has been applied in combination with surrogate indicators to estimate crash probabilities. Most of this research has focused on testing BM and POT as well as validating various surrogate safety indicators by comparing model estimates to actual crash frequencies. The comparison of collision course indicators with indicators including crossing course interactions and their performance using EVT has not been investigated yet. In this study we are seeking answers to under what conditions these indicators perform better and whether they are transferable. Using data gathered at a signalized intersection focusing on left-turning and straight moving vehicle interactions our analysis concluded that the two indicators are transferable with stricter threshold values for T₂ and that POT gives more reasonable results.

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