Public FAQs

FAQs

Each part of Texas provides specific opportunities for AV companies. From long stretches of interstates in West Texas to both large and small cities sharing common borders, Texas offers unique opportunities for industry to not only pilot, but to successfully build the operations for future growth.

The Texas Legislature has adopted legislation over the last few years regarding CAVs in Texas. Please follow this link for summaries of each bill: Current Texas Laws

CAVs at a limited level of autonomy currently co-exist with human drivers. It is foreseeable that there will be challenges as humans evaluate and react to roadway situations differently than computers. As the automation levels advance toward driverless vehicles so will the CAV industry’s assurances of safety, cyber security, and environmental performance.

Many vehicle already have advanced driver assistance features such as:

Rearview Video Systems
Automatic Emergency Braking
Pedestrian Automatic Emergency Braking
Rear Automatic Emergency Braking
Rear Cross Traffic Alert
Lane Centering Assist
Lane keeping assist
Adaptive cruise control
Traffic jam assist
Self-park

Research indicates that CAVs can have a positive impact on fuel economy through continual speed management to reduce the amount of vehicle braking and acceleration with fewer speed fluctuations.

The statute just passed September 1, 2021, SB 1308, relates to a border traffic study on the impacts of using certain motor vehicle technologies. This research requires TxDOT and DPS, in consultation with the Texas A&M Transportation Institute and the appropriate federal agencies, to jointly conduct a study on:

the potential benefits of using automated driving systems, connected driving systems, and other emerging technologies to alleviate motor vehicle traffic congestion at ports of entry on the Texas-Mexico border; and

the overall impact of using automated driving systems, connected driving systems, and other emerging technologies on the transportation industry workforce and the broader Texas economy, including the effects on driver and public safety.

https://capitol.texas.gov/tlodocs/87R/billtext/pdf/SB01308S.pdf

Prioritize roadway maintenance along CAV corridors, focusing on lane striping, pavement quality, and signage.
Cooperative effort for common infrastructure challenges such as work zones, forced merges, and transfer points.
Workforce development programs

According to the Minnesota DOT, Preparing Roads for Connected and Autonomous Vehicles, the infrastructure considerations for CAV include the following:

Pavement Markings – width and material.
Signing – standardized, easily visible, and not blocked, damaged or faded.
Traffic Signals – Create space at signal control cabinets for additional hardware related to CAV technologies.
Consistency and Standardization – Install and maintain striping, signing and signals consistent with CAV algorithms and technologies.
Pavement Maintenance.
Data Capture and Information Sharing – Begin or continue collecting and organizing data for bridge heights, speed limits, load restrictions, crosswalks, roadway curvatures and other infrastructure characteristics.
Communication Infrastructure. – In new construction and information technology infrastructure built for agency use, ensure adequate conduits for power and fiber optic cables.
High-Resolution Mapping – Consider developing high-resolution mapping capabilities (MnDOT 2019).

Infrastructure maintenance is a key component for CAV operations. The CAV must be able to assimilate the data it receives from the V2X, surrounding infrastructure and roadway. Roadways, signage and other infrastructure that are in need of repair may impede the CAV’s ability to establish and maintain accurate and timely situational awareness of the roadway environment and may contribute to inefficient operation or functional errors.

As with any other system that is fully connected to the cyber world, CAVs face some of the same security issues. The three key elements potentially vulnerable to cyberattacks identified by Kim et al. 2021 are automotive control systems, autonomous driving system components, and V2X.

An automotive control system consists of an in-vehicle network that connects the main device and the other devices. These are classified as units and networks. The most important units are electronic control units (ECU) that manages all of the systems within the vehicle from powertrains to door locks.

The autonomous driving system consists of the components that “read” the roadway and surrounding areas. These are technologies such as GPS, Bluetooth, LiDAR, RADAR and cameras, central computer, and ultrasonic sensors.

The V2X communication technologies communicate with all of the other technologies including Vehicle ad-hoc networks (VANETs). Attack methods and defenses are being vigorously studied by the CAV industry and IT companies.

According to the National Highway Traffic Safety Administration (NHTSA) a comprehensive and systematic approach to developing layered cybersecurity protections for vehicles includes the following:

A risk-based prioritized identification and protection process for safety-critical vehicle control systems;
Timely detection and rapid response to potential vehicle cybersecurity incidents on America’s roads;
Architectures, methods, and measures that design-in cyber resiliency and facilitate rapid recovery from incidents when they occur; and
Methods for effective intelligence and information sharing across the industry to facilitate quick adoption of industry-wide lessons learned. NHTSA encouraged the formation of Auto-ISAC, an industry environment emphasizing cybersecurity awareness and collaboration across the automotive industry (USDOT)

Figure 3. Categories of Attack Research on Autonomous Vehicles. Source: Kim et al. 2021.

Connected vehicles (CVs) rely their ability to maintain situational awareness through multiple communication systems collectively known as vehicle-to-everything (V2X). This V2X consists of vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P) and vehicle-to-network (V2N). These communication systems rely on wireless technologies such as dedicated short range communications (DSRC) developed specifically for CV usage. Signals are sent via DSRC by on-board units (OBU) and roadside units (RSU). CVs also use technologies such as GPS, Bluetooth, LiDAR, RADAR and cameras to “read” the roadway and its surroundings and send data to the vehicle to achieve an appropriate response to the given situation.

Critical AV systems do not rely on a single point of failure. System redundancy is a recognized need within the industry.

For more information.

Weather and other issues such as debris can adversely affect the AV performance. Research and the AV industry are developing systems to reduce the impacts of weather such as specially designed wipers, heated shields, and specially treated surfaces are used to prevent precipitation buildup from ice and snow. AV systems are designed to interpret and identify objects distorted by weather. The AVs are programmed to direct the vehicle to the shoulder and/or re-route to safer conditions.

Figure 2. – Key elements of autonomous vehicles. Source: Kim et al. 2021

Autonomous vehicles rely on sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software.

Autonomous vehicles create and maintain a map of their surroundings based on a variety of sensors situated in different parts of the vehicle. Radar sensors monitor the position of nearby vehicles. Video cameras detect traffic lights, read road signs, track other vehicles, and look for pedestrians. Lidar (light detection and ranging) sensors bounce pulses of light off the vehicle’s surroundings to measure distances, detect road edges, and identify lane markings. Ultrasonic sensors in the wheels detect curbs and other vehicles when parking.

Sophisticated software then processes all this sensory input, plots a path, and sends instructions to the car’s actuators, which control acceleration, braking, and steering. Hard-coded rules, obstacle avoidance algorithms, predictive modeling, and object recognition help the software follow traffic rules and navigate obstacles.

https://www.synopsys.com/automotive/what-is-autonomous-car.html

Level 4 automation is the same for any vehicle type. Autonomous trucking generally refers to commercial truck platooning whereby the follow vehicles communicate with a lead truck that controls the “driving” for the other truck connected in the platoon. The driver in follow vehicle is on board to respond to a request to intervene but does not drive the vehicle.

The levels of automation are the same regardless of vehicle type. These levels range from the driver being responsible for all vehicle actions, no automation (Level 0) to fully automation where the “driver” is just a passenger in the vehicle (Level 5).

Level 0 – The human driver does all the driving.
Level 1 – An advanced driver assistance system (ADAS) on the vehicle can sometimes assist the human driver with either steering or braking/accelerating, but not both simultaneously.
Level 2 – ADAS on the vehicle can itself actually control both steering and braking/accelerating simultaneously under some circumstances. The human driver must continue to pay full attention (“monitor the driving environment”) at all times and perform the rest of the driving task.
Level 3 – An automated driving system (ADS) on the vehicle can itself perform all aspects of the driving task under some circumstances. In those circumstances, the human driver must be ready to take back control at any time when the ADS requests the human driver to do so. In all other circumstances, the human driver performs the driving task.
Level 4 – ADS on the vehicle can itself perform all driving tasks and monitor the driving environment – essentially, do all the driving – in certain circumstances. The human need not pay attention in those circumstances.
Level 5 – ADS on the vehicle can do all the driving in all circumstances. The human occupants are just passengers and need never be involved in driving.

IMPROVE PUBLIC SAFETY.

Fewer conflicts and crashes will lead to improved passenger and pedestrian safety.

ALTER THE APPROACH TO FUTURE LONG-TERM CAPACITY PROJECTS.

Self-driving cars may alter travel patterns and change how the vehicles are used and operate together, which may change how road capacity needs are addressed.

MORE RELIABLE TRAVEL TIME.

The ability to constantly monitor traffic will substantially reduce uncertainty in travel times via real-time, predictive assessment of travel times on all routes

IMPROVED MOBILITY FOR THE ELDERLY, DISABLED, AND YOUTH.

Driverless vehicles could be the conduit to provide needed transportation to those who currently have difficulties with mobility

IMPROVED ENERGY EFFICIENCY.

Reduced energy consumption in at least three ways: more efficient driving; lighter, more fuel-efficient vehicles; and reduced carbon emissions

NEW MODELS FOR VEHICLE OWNERSHIP.

Self-driving vehicles could lead to a major redefinition of vehicle ownership and expand opportunities for vehicle sharing

NEW BUSINESS MODELS AND SCENARIOS.

CAV technology will blur the lines between public and private industries, creating an emphasis on collaboration transportation innovation

ENABLE NEW BUSINESS OPPORTUNITIES FOR TEXAS.

Empower appropriate regulations.

Prepare the state for Connected and Autonomous (CAV) advancements (good with the bad)

Be the primary coordination and information source for CAV technology use and testing in Texas;
Be the source to inform the public and leaders on current and future CAV advancements and what they mean in Texas.
Report on current status, future concerns and how these technologies are changing future quality of life and well-being;
Be a champion making Texas a leader in knowing how to best prepare and wisely integrate these technologies in a positive way.
Promote positive development and experiences for the state.

The state of Texas and its partners believe on-going success and support will be achieved by promoting economic efficiency and safety of commercial vehicles and freight first, followed by passenger cars and other users

Figure 2. CAV technologies

Reference Source: Texas Department of Transportation

Figure 3. CAV technologies

Reference Source: Texas Department of Transportation

Statewide strategic planning and policy on CAVs
Provide reports to state legislators and governors regarding CAV opportunities, challenges, and guidance
Advise local governments on CAV technology
Look at both passenger and freight challenges
Identify strategic partnership opportunities for CAV testing, pilots and deployment
Provide guidance on preparing transportation technology and network infrastructure
Provide guidance on preparing for CV Data and information: management, storage, ownership
Evaluate and make recommendations on testing, voluntary certification, Pilot Programs/Projects and deployment of CAV
Review operation and safety of CAVs
Review impacts on public safety and perception
Review Privacy & Security and make recommendations

Reference Source: Texas Department of Transportation

Figure A. Reference Source: Texas Department of Transportation

Figure 1. States with Autonomous Vehicles Enacted Legislation and Executive Orders

Reference Source: National Conference of State Legislatures (NCSL)

Statewide strategic planning and policy on CAVs
Provide reports to state legislators and governors regarding CAV opportunities, challenges, and guidance
Advise local governments on CAV technology
Look at both passenger and freight challenges
Identify strategic partnership opportunities for CAV testing, pilots and deployment
Provide guidance on preparing transportation technology and network infrastructure
Provide guidance on preparing for CV Data and information: management, storage, ownership
Evaluate and make recommendations on testing, voluntary certification, Pilot Programs/Projects and deployment of CAV
Review operation and safety of CAVs
Review impacts on public safety and perception
Review Privacy & Security and make recommendations