Vehicle Automation, Legal Standards of Care, and Freeway Capacity

Abstract

Automated-control technology for road vehicles is advancing rapidly, presenting novel challenges to transportation planners and policymakers. One such challenge is the possibility that the standard value of road network capacity (vehicles per lane per hour) may substantially change within the typical infrastructure-planning horizon of several decades from the present day. The study evaluates, in the context of freeway segments, the interaction between automated cars’ kinematic capabilities and the standard legal requirement for the operator of an automobile to not strike items that are in its path (known as the ‘Assured Clear Distance Ahead’ criterion). We then model ACDA-compliant operating strategies that are based on rationally-specified kinematic parameters, extending from earlier simulation studies in which controls on automated cars’ motion are defined arbitrarily. The specific contributions of this paper’s novel joint analysis of legal standards and engineering criteria comprise: 1) an in-depth assessment of the structural barriers to automated cars operating non-ACDA-compliant driving strategies, 2) a straightforward ACDA-compliant automated-driving model to estimate freeway ‘pipeline’ capacity analytically, placed in the context of comparable models of humans’ driving behavior, and 3) interpretation of quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. Among other results, we demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive “fundamental diagrams” (relationships between speed and flow). Our results suggest that automated cars (under a baseline set of assumptions) may sustain higher flow rates at their free-flow speed than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion may be steeper for automated cars. ACDA-compliant automated cars also may have a higher level of maximum-achievable throughput (irrespective of speed) than human drivers, though the impact on maximum throughput at free-flow speed is ambiguous. We demonstrate that vertical grades (but not horizontal curves) are likely to have impacts on capacity that differ from when human are driving. We also present a novel quantification of the trade-off between freeway-capacity and various degrees of safety (one failure in 10,000 events, one failure in 100,000, etc.) that explicitly accounts for the irreducible uncertainty in emergency braking performance, by drawing on empirical distributions of braking distance testing. Finally, we assess the vulnerability of ACDA-compliant automated cars to lateral ‘cut-ins’ by vehicles making lane changes.The paper concludes with a brief discussion of policy questions and research needs.