Vehicle automation and freeway 'pipeline' capacity in the context of legal standards of care

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

During and After Event Analysis of Cell Phone Talking and Texting-A Driving Simulator Study

A number of studies have been done in the field of driver distraction, specifically on the use of cell phone for either conversation or texting while driving. However, till now, researchers have focused on the driving performance of drivers when they were actually engaged in the task, i.e. during the texting or phone conversation event. The primary objective of this study is to analyze the post event effect of cell phone usage in order to verify whether the distracting effect lingers on after the actual event had ceased. The research utilizes a driving simulator study of thirty-six participants to test whether a significant decrease in driver performance occurs during and after cell phone usage (texting and conversation). The standard deviations of lane position and mean velocity was used as dependent measures to represent lateral and longitudinal control of the vehicle respectively. Linear mixed model with subject as a random factor and F-test for the equality of variance were used as statistical measures. The results from the study suggest that there was no significant decrease in driver performance during and after the cell phone conversation both laterally and longitudinally. On the contrary, during the texting event, a significant decrease in driver performance was observed both in the lateral and longitudinal control of the vehicle. The diminishing effect of texting on longitudinal control ceased immediately after the texting event but the diminishing effect of texting on lateral control lingered on for an average of 3.388 seconds. The number of text messages exchanged did not affect the magnitude and duration of the diminished lateral control. This indicates that the distraction and subsequent elevated crash risk of texting while driving linger on even after the texting event has ceased. Such finding has safety and policy implications in the fight to reduce distracted driving

Customer preferences and implicit tradeoffs in accident scenarios for self-driving vehicle algorithms

The development of self-driving vehicles is proceeding rapidly and with significant investment of resources. However, a full-scale deployment is not imminent. Among the challenges self-driving vehicles are facing, they will have to navigate complex ethical challenges. The algorithms governing their behavior will have to decide how to steer them in situations where accidents cannot be avoided. In some of these situations they will have to decide which of several potential parties to injure in the process. We investigate the preferences of Swiss customers for this decision by forcing a selection between simplified scenarios where a given number of car passengers or a given number of pedestrians will be killed in the accident. Both passengers and pedestrians can be adults or children. The passengers are explicitly identified as the respondent themselves and their family. While children are implicitly valued higher than adults, Swiss customers value passengers and pedestrians implicitly roughly equally, and assign increasingly higher marginal values to additional people, both passengers and pedestrians. These results seem to partially contradict similar studies conducted in other countries and recent statements by automotive companies, potentially indicating the need to adapt both corporate communications and steering algorithms in different geographies

Two-Hop Connectivity to the Roadside in a VANET Under the Random Connection Model

We compute the expected number of cars that have at least one two-hop path to a fixed roadside unit in a one-dimensional vehicular ad hoc network in which other cars can be used as relays to reach a roadside unit when they do not have a reliable direct link. The pairwise channels between cars experience Rayleigh fading in the random connection model, and so exist, with probability function of the mutual distance between the cars, or between the cars and the roadside unit. We derive exact equivalents for this expected number of cars when the car density $\rho$ tends to zero and to infinity, and determine its behaviour using an infinite oscillating power series in $\rho$, which is accurate for all regimes. We also corroborate those findings to a realistic situation, using snapshots of actual traffic data. Finally, a normal approximation is discussed for the probability mass function of the number of cars with a two-hop connection to the origin. The probability mass function appears to be well fitted by a Gaussian approximation with mean equal to the expected number of cars with two hops to the origin.Comment: 21 pages, 7 figure

Inter Vehicle Distance based connectivity aware routing in vehicular adhoc networks

Connectivity in vehicular traffic environment has witnessed significant attention due to the direct impact on the performance of most of the traffic safety applications of intelligent transport system. Various parameters such as density, speed, direction, link quality and inter vehicle distance (IVD) have been utilized for measuring connectivity. IVD has greater impact on connectivity and controls the impact of other parameters. Usage of real time IVD for measuring connectivity has not received sufficient attention in VANETs. This paper proposes IVD based connectivity aware routing (Ivd-CAR) for enhancing connectivity aware data dissemination. IVD calculation is robust and can effectively handle instantaneous GPS failure. Two localization techniques; namely, cooperative localization and Geometry based Localization are developed. Standard deviation of real time IVDs of a forwarding path is derived. Distribution of IVDs of a forwarding path is employed for estimating connectivity. Segment vehicle based next hop vehicle selection is utilized for incorporating network load, link quality and direction into consideration while selecting forwarding path. Simulations are carried out in ns2 to evaluate the performance of Ivd-CAR in realistic traffic environment. Comparative analysis of simulation results attests the superiority of Ivd-CAR to the state-of-the-art techniques: CSR and A-CAR