Abstract
This paper analyses the factors that affect the impact of autonomous vehicles (AVs) on the capacity of a freeway in Brazil using an adaptation of the HCM-6 procedure for truck PCE estimation. A version of Vissim, recalibrated to represent traffic streams and AVs on Brazilian freeways, was used to simulate more than 25,000 scenarios representing combinations of traffic (e.g., AV fleets, AV platoons, percentage of AVs and of heavy goods vehicles) and road (grades and number of lanes) characteristics. AV impacts on capacity were evaluated by means of the capacity adjustment factor (CAF) and a model to estimate CAF from control variables was fitted and validated. The results indicate increases of up to 30% in capacity with 60% of platooning-capable AVs. Statistical analyses show that the fraction of AVs in the stream and the proportion of platooning-capable AVs are the factors with the greatest impact on this increase in capacity.
Highlights
One of the attractions of autonomous vehicles (AVs) is the increase in capacity due to the more intensive use of traf ic lanes, and consequent improvements in the ef iciency of road operations (Zhao and Sun, 2013; Bierstedt et al, 2014)
How to incorporate AVs when assessing the capacity and quality of service is an aspect that should be considered by managers, mainly for freeways that are under concession contracts and where the maintenance of a minimum quality standard is guaranteed under contract
In Brazil, as in many other countries, the quality of services is assessed by the Highway Capacity Manual (HCM), which still does not provide an instrument that includes AVs in the process, in its most recent edition, HCM-6 (TRB, 2016)
Summary
One of the attractions of autonomous vehicles (AVs) is the increase in capacity due to the more intensive use of traf ic lanes, and consequent improvements in the ef iciency of road operations (Zhao and Sun, 2013; Bierstedt et al, 2014). Various studies suggest that AVs will be able to improve traf ic low with a high level of penetration in traf ic streams and cooperation. The effects of AVs on the capacity of freeways with a low and medium level of penetration are not yet well known (Milanes et al, 2014). The present study is part of a broader project, which proposes a way to include AVs in quality-of-service assessments based on the HCM-6 passenger-car equivalents (PCE) method. The impacts considered include: the type of AVs and their penetration rate; the maximum number of platooning vehicles; the number of lanes; the proportion of heavy goods vehicles (HGV) in the traf ic stream; and the length and magnitude of the slopes. Based on the capacity of each scenario, the capacity adjustment factor (CAF) and a model for estimating the CAF value as a function of the simulation control variables were obtained
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