Parking Behavior of Autonomous Vehicles (AVs) | Research Centre for Integrated Transport Innovation (rCITI)
Parking Behavior of Autonomous Vehicles (AVs)
When developing an Integrated Equilibrium Model for Autonomous Vehicles (IEMAV) parking behaviour needs to be considered.
The modeling framework reflects the interaction between transport performance and the economy in the AV environment, where travel demand is elastic with regard to multiple influencing factors such as travel cost, population, and household income.
The IEMAV framework is madeup of two submodels:- a Computable General Equilibrium (CGE) and the Autonomous Traffic Equilibrium (ATE).
The CGE submodel describes the behaviour of firms and households interacting in markets over a set of regions. Household activities are madeup of working, shopping and leisure-associated journeys. These journeys are assigned to the road network in the ATE submodel, and the derived travel costs are fed back to the CGE submodel. These two submodels iterate until equilibrium is reached in both simultaneously.
To demonstrate the model behaviour, we used the Sydney Metropolitan Area for our casestudy. We found when behavioural realisms of autonomous vehicles (AVs) were considered with broader economic impacts, it woud likely lead to significant societal detriments both in terms of the spatial economy and regional transport with the introduction of AVs.
This multidisciplinary study results suggest that without any intervention, society may be worse off with the introduction of AVs due to differences in travel behavior from non-AVs. Strategies to mitigate these potential negative impacts could cover diverse social and scientific fields such as - policy, labor, industry, behavior, market, or planning.
Paper: Zhang X; Robson E; Waller ST, 2021, 'An integrated transport and economic equilibrium model for autonomous transportation systems considering parking behavior', Computer-Aided Civil and Infrastructure Engineering, vol. 36, pp. 902 - 921, http://dx.doi.org/10.1111/mice.12611
E: xiang.zhang1@unsw.edu.au