Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation. Safety-critical tasks that must be executed by a self-driving vehicle include planning of motions through a dynamic environment shared with other vehicles and pedestrians, and their robust executions via feedback control. The objective of this paper is to survey the current state of the art on planning and control algorithms with particular regard to the urban setting. A selection of proposed techniques is reviewed along with a discussion of their effectiveness. The surveyed approaches differ in the vehicle mobility model used, in assumptions on the structure of the environment, and in computational requirements. The side by side comparison presented in this survey helps to gain insight into the strengths and limitations of the reviewed approaches and assists with system level design choices.

A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

The Righteous Mind: Why Good People Are Divided by Politics and Religion Jonathan Haidt Pantheon Books, 2012One has likely heard that, for the sake of decorum, religion and politics should never be topics of conversation with strangers. Even amongst friends or even when it is known that others hold opposing political or religious views, why is it that discussion of religion and politics leads to visceral-level acrimony and that one's views are right and the other's views are wrong? Professor Jonathan Haidt of the University of Virginia examines the psychological basis of our "righteous minds" without resorting to any of the pejorative labeling that is usually found in a book on politics and religion and eschews a purely comparative approach. Haidt proposes the intriguing hypothesis that our visceral reaction to competing ideologies is a subconscious, rather than leaned, reaction that evolved over human evolution to innate senses of suffering, fairness, cheating and disease, and that moral foundations facilitated intra-group cooperation which in turn conferred survival advantages over other groups. These psychological mechanisms are genetic in origin and not necessarily amenable to rational and voluntary control - this is in part the reason debating one's ideological opposite more often leads to frustration rather than understanding. Haidt also suggests that morality is based on six "psychological systems" or foundations (Moral Foundations Theory), similar to the hypothesized adaptive mental modules which evolved to solve specific problems of survival in the human ancestral environment.While decorum pleads for more civility, it would be better, as Haidt suggests, dragging the issue of partisan politics out into the open in order to understand it and work around our righteous minds. Haidt suggests a few methods by which the level of rhetoric in American politics can be reduced, such that the political parties can at least be cordial as they have been in the past and work together to solve truly pressing social problems.There are a number of fascinating points raised in the current book, but most intriguing is the one that morality, ideology and religion are products of group selection, as adaptations that increased individual cooperation and suppressed selfishness, thereby increasing individual loyalty to the group. That morality, political ideology and religion buttress group survival is probably highly intuitive. However, given the contemporary focus on the individual as the source of adaptations, to the exclusion of all else, to suggest that adaptations such as religion and political ideology arose to enhance survival of groups is heresy or, as Haidt recounts, "foolishness". While previous rejection of group selection itself was due in part to conceptual issues, one could also point out the prevailing individualist social sentiment, "selfish gene" mentality and unrelenting hostility against those who supported the view that group selection did indeed apply to humans and not just to insects. Haidt gives a lengthy and convincing defense of group selection, his main point being that humans can pursue self- interest at the same time they promote self-interest within a group setting - humans are "90 percent chimp, 10 percent bees". One can readily observe in the news and entertainment mediate that religion is a frequent target of derision, even within the scientific community - Haidt points to the strident contempt that the "New Atheists" hold for religion. They claim that religion is purely a by-product of an adaptive psychological trait and as a mere by-product religion serves no useful purpose. However, the religious "sense" has somehow managed to persist in the human psyche. One explanation by the New Atheists of how religion propagated itself is that it is a "parasite" or "virus" which latches onto a susceptible host and induces the host to "infect" others. As a "virus" or "parasite" that is merely interested in its own survival, religion causes people to perform behaviors that do not increase their own reproductive fitness and may even be detrimental to survival, but religion spreads nonetheless. …

The Righteous Mind: Why Good People Are Divided by Politics and Religion

In order to achieve autonomous operation of a vehicle in urban situations with unpredictable traffic, several realtime systems must interoperate, including environment perception, localization, planning, and control. In addition, a robust vehicle platform with appropriate sensors, computational hardware, networking, and software infrastructure is essential.

/pdf/towards-fully-autonomous-driving-systems-and-algorithms-58y9e7p2b1.pdf

Towards fully autonomous driving: Systems and algorithms

Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.

A Review of Motion Planning Techniques for Automated Vehicles

Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation. Safety-critical tasks that must be executed by a self-driving vehicle include planning of motions through a dynamic environment shared with other vehicles and pedestrians, and their robust executions via feedback control. The objective of this paper is to survey the current state of the art on planning and control algorithms with particular regard to the urban setting. A selection of proposed techniques is reviewed along with a discussion of their effectiveness. The surveyed approaches differ in the vehicle mobility model used, in assumptions on the structure of the environment, and in computational requirements. The side-by-side comparison presented in this survey helps to gain insight into the strengths and limitations of the reviewed approaches and assists with system level design choices.

A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles

Emergency scenarios may necessitate autonomous vehicle maneuvers up to their handling limits in order to avoid collisions. In these scenarios, vehicle stabilization becomes important to ensure that the vehicle does not lose control. However, stabilization actions may conflict with those necessary for collision avoidance, potentially leading to a collision. This paper presents a new control structure that integrates path tracking, vehicle stabilization, and collision avoidance and mediates among these sometimes conflicting objectives by prioritizing collision avoidance. It can even temporarily violate vehicle stabilization criteria if needed to avoid a collision. The framework is implemented using model predictive and feedback controllers. Incorporating tire nonlinearities into the model allows the controller to use all of the vehicle’s performance capability to meet the objectives. A prediction horizon comprised of variable length time steps integrates the different time scales associated with stabilization and collision avoidance. Experimental data from an autonomous vehicle demonstrate the controller safely driving at the vehicle’s handling limits and avoiding an obstacle suddenly introduced in the middle of a turn.

Collision Avoidance and Stabilization for Autonomous Vehicles in Emergency Scenarios

This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all ofthese topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of autonomous driving".

/pdf/autonomous-driving-technical-legal-and-social-aspects-488md5hik9.pdf

Autonomous Driving: Technical, Legal and Social Aspects

Safe driving envelopes for path tracking in autonomous vehicles

This paper demonstrates a method of estimating several key vehicle states-sideslip angle, longitudinal velocity, roll and grade-by combining automotive grade inertial sensors with a Global Positioning System (GPS) receiver. Kinematic Kalman filters that are independent of uncertain vehicle parameters integrate the inertial sensors with GPS to provide high update estimates of the vehicle states and the sensor biases. Using a two-antenna GPS system, the effects of pitch and roll on the measurements can be quantified and are demonstrated to be quite significant in sideslip angle estimation. Employing the same GPS system as an input to the estimator, this paper develops a method that compensates for roll and pitch effects to improve the accuracy of the vehicle state and sensor bias estimates. In addition, calibration procedures for the sensitivity and cross-coupling of inertial sensors are provided to further reduce measurement error The resulting state estimates compare well to the results from calibrated models and Kalman filter predictions and are clean enough to use in vehicle dynamics control systems without additional filtering.

Integrating Inertial Sensors With Global Positioning System (GPS) for Vehicle Dynamics Control

Racecar drivers have the ability to operate a vehicle at its friction limit without losing control. If autonomous vehicles or driver assistance systems had similar capabilities, many fatal accidents could be avoided. To advance this goal, an autonomous racing controller is designed to gain insights into vehicle control at the friction limits. A bicycle model and a ‘ g-g ’ diagram are used to mimic racecar drivers’ internal vehicle model. Lanekeeping steering feedback and wheel slip feedback controllers are used to imitate drivers making steering and throttle corrections according to the vehicle responses. Experimental results on a low friction surface demonstrate that the controller can robustly track a path while operating at the limits of tyre adhesion and provide insights for the future development of vehicle safety systems.

/pdf/autonomous-vehicle-control-at-the-limits-of-handling-bfbbj266cq.pdf

J. Christian Gerdes

Papers

Collision Avoidance and Stabilization for Autonomous Vehicles in Emergency Scenarios

Autonomous Driving: Technical, Legal and Social Aspects

Safe driving envelopes for path tracking in autonomous vehicles

Integrating Inertial Sensors With Global Positioning System (GPS) for Vehicle Dynamics Control

Autonomous Vehicle Control at the Limits of Handling