When it comes to creating travel demand models there are a few aspects that could hold more significance. These include the quality and availability of data as well as changes in trip purpose and distance due to autonomous vehicles.

1. Quality and Availability of Data

Autonomous vehicles present an opportunity to collect massive amounts of real-time traffic data that can provide valuable insights to improve travel demand models. The data gathered from monitoring the vehicle can reveal traffic patterns, vehicle speeds, and journey times. Additionally, the vehicle's sensors and cameras can provide important behavioral insights of the passengers such as patterns, duration of trips, reason for travel, and use of facilities.

To better understand what affects travel demand for autonomous vehicles advanced analytics and machine learning techniques are employed to detect patterns and relationships which can reveal insights about the demand for autonomous vehicles based on weather conditions, road conditions and traffic patterns.

Data accessibility has expanded beyond urban areas with the development of technology to enable data collection and analysis in rural areas, offering important information regarding the need for autonomous vehicles in such places.

2. Changes in Trip Purpose and Distance

Autonomous vehicles could lead to a shift in how people travel, altering the purpose and length of trips. People may be more likely to travel farther for work and leisure activities if the commute can be used productively. This could have a major positive impact on the economy as it could lead to increased demand for travel.

Moreover, driverless vehicles could make it easier and more convenient for people to accomplish tasks and run errands with frequent long-distance travel to locations previously inaccessible. This could increase access to goods and services for those with poor availability of public transportation or mobility challenges that make carrying bulky items difficult.

Furthermore, the use of autonomous vehicles could lead to environmental benefits by reducing the number of cars on the road and the need for parking spots, resulting in fewer traffic jams and less air pollution, creating a safer and healthier environment for everyone.

Sources:

"Safety." NHTSA, https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety#topic-road-self-driving.

Bagloee, Saeed Asadi, et al. "Autonomous Vehicles: Challenges, Opportunities, and Future Implications for Transportation Policies." SpringerLink, Springer Berlin Heidelberg, 29 Aug. 2016, https://link.springer.com/article/10.1007/s40534-016-0117-3.

Hardman, Scott, et al. "Estimating Travel Demand Impacts of Semi-Automated Vehicles." Transportation Research Part D: Transport and Environment, Pergamon, 20 May 2022, https://www.sciencedirect.com/science/article/pii/S1361920922001390.

"J3016_201806: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles." SAE International, https://www.sae.org/standards/content/j3016_201806/.