Vehicle automation and freeway \u2018pipeline\u2019 capacity in the context of legal standards of care

Scott Le Vine,John Polak,Xiaobo Liu,You Kong

doi:10.1007/s11116-017-9825-8

Abstract

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). The objective is to characterize the impacts of ACDA-compliant driving behavior on the system-level indicator of roadway-network capacity. We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDA-compliant automated-driving model to analytically estimate freeway ‘pipeline’ capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. We demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive “fundamental diagrams” (relationships between speed and flow). Our results suggest that such automated-driving strategies (under a baseline set of assumptions) would sustain higher flow rates at free-flow speeds than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion would be steeper. ACDA-compliant automated cars also would have a higher level of maximum-achievable throughput, though the impact on maximum throughput at free-flow speed depends on the specific interpretation of ACDA. We also present a novel quantification of the tradeoff between freeway-capacity and various degrees of safety (one failure in 100,000 events, one failure in 1,000,000, 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.

Highlights

With the commercial rollout of increasingly-sophisticated vehicle-automation concepts, there is growing interest in the nature of potential impacts to various aspects of the transportation system, such as safety (Fagnant and Kockelman 2014; Kalra and Paddock 2016), parking (Zhang et al 2015; Kong et al 2016), pollutant emissions (Wadud et al 2016), regulations (Smith 2014, Anderson et al 2016; Gasser 2016), possible shifts from car-ownership to car-rental (Fagnant and Kockelman 2016), and how in-vehicle time is used (Malokin et al 2015; Zmud et al 2016).This paper’s focus relates to the impacts of highly-automated cars on traffic flow on mainline freeway segments
We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDAcompliant automated-driving model to analytically estimate freeway ‘pipeline’ capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty
We consider operating regimes in which the automated vehicle’s (AV’s) longitudinal-control system makes and implements control decisions regarding speed and following-distance-from-forward-vehicle without input from the vehicle’s occupant(s). This is a more highly automated concept than adaptive cruise control (ACC), in which a human driver makes an initial selection of speed and following distance, and the automated control system subsequently operates pursuant to this guidance

Summary

Introduction

With the commercial rollout of increasingly-sophisticated vehicle-automation concepts, there is growing interest in the nature of potential impacts to various aspects of the transportation system, such as safety (Fagnant and Kockelman 2014; Kalra and Paddock 2016), parking (Zhang et al 2015; Kong et al 2016), pollutant emissions (Wadud et al 2016), regulations (Smith 2014, Anderson et al 2016; Gasser 2016), possible shifts from car-ownership to car-rental (Fagnant and Kockelman 2016), and how in-vehicle time is used (Malokin et al 2015; Zmud et al 2016).This paper’s focus relates to the impacts of highly-automated cars (cf. SAE 2014) on traffic flow on mainline freeway segments. We consider operating regimes in which the automated vehicle’s (AV’s) longitudinal-control system makes and implements control decisions regarding speed and following-distance-from-forward-vehicle without input from the vehicle’s occupant(s). In other words, this is a more highly automated concept than adaptive cruise control (ACC), in which a human driver makes an initial selection of speed and following distance, and the automated control system subsequently operates pursuant to this guidance. Whether AVs will be ‘selfdirected’ or will rely on V2X communications to ‘direct their movement’ is noted by Glancy et al (2016) as a major point of uncertainty

Methods

Results

Conclusion