California Partners for Advanced Transportation Technology

Recent changes in California transportation policy have increased the importance of evaluating the impacts of highway capacity expansion on travel demand by shifting environmental review practices away from level-of-service toward assessing impacts on vehicle miles traveled (VMT) and travel demand. While established analytical tools exist for evaluating induced travel in urban regions, limited research and modeling resources have made it difficult to apply similar methods in rural areas.

This research investigates whether capacity-enhancing projects on rural elements of the California State Highway System (SHS) are associated with measurable increases in VMT. The study evaluates county-level statistical relationships using historical data from 1990 to 2024, describing roadway supply, travel demand, and socioeconomic conditions across California counties. Regression analyses were conducted using Highway Performance Monitoring System (HPMS) data, populationestimates, employment statistics, and other supporting variables to examine relationships between VMT, SHS roadway capacity, population, and employment. Analyses included comparisons across counties, changes over 5-year, 10-year, and 20-year intervals, and separate evaluations of rural, partly rural, and urban county groupings.

The findings indicate that relationships between roadway capacity and VMT in rural areas can be substantially variable and less consistent than expected. While some statistical relationships between SHS capacity and VMT were identified, the analyses did not consistently support strong or stable induced travel effects across rural counties. Population and employment changes were generally found to be important explanatory variables. However, data limitations associated with roadway supply measures and traffic estimation methods have affected analytical reliability. The results suggest caution in directly applying urban-based induced travel elasticity assumptions and tools to rural areas and point to the need for additional research with improved rural datasets to better understand the long-term impacts of rural capacity-enhancing

projects.

California’s transition to electric vehicles (EVs) requires more than additional charger counts. Public charging must be accessible, affordable, and reliable where people actually live and travel. This report presents a geospatial dashboard and time-series toolkit for the nine Bay Area counties that maps public charging stations, tracks price and charging-port status at 10-minute intervals, and identifies disadvantaged community (DAC) census tracts using the joint U.S. Department of Energy/U.S. Department of Transportation/National Electric Vehicle Infrastructure (DOE/DOT/NEVI) framework. The tool reports charger availability, utilization, pricing, reliability, and average session cost, and supports equity metrics such as ports per 1,000 residents or renters, travel time to a direct-current fast charger, and tract-levelcomparisons between DAC and non-DAC areas. It also supports early screening of sites for Level-3 fast chargers by identifying locations that appear feasible from the grid standpoint. The result is a practical planning tool that allows agencies to monitor conditions continuously without field surveys and to target investments toward areas of greatest need.

Onboard eco-driving systems provide drivers with real-time information about their driving behavior and road conditions, encouraging them to optimize their driving speed and consequently reduce fuel consumption and emissions. However, there are barriers to making eco-driving a habit. To determine the elements that influence drivers’ intentions to practice eco-driving and their acceptance of eco-driving technology, we developed a theoretical model based on established theories on planned behavior, technology acceptance, and personal goals. The findings showed that drivers’ intention to practice eco-driving has an indirect effect on their intention to use the system via the factor of perceived ease of use. We also explored how cognitive distraction while using an eco-driving system can be a potential barrier to acceptance. The intent is to put forward a solution to improve drivers’ usage eco-driving by turning off guidance when the system detects that the driver is experience from serious distraction. To investigate how to detect a driver’s cognitive distraction status when they are interacting with an eco-driving system, we used a driving simulator and leveraged machine learning algorithms to classify drivers’ attentional states. The findings showed that the glance features played a more important role than the driving features in cognitive distraction.

Transportation data standards are an increasingly important and complex topic, as well as a key enabler of Intelligent Transportation Systems (ITS). New data sources, private data providers, and uses for transportation data are exploding. The ability to harness data is at the core of modern efforts to improve the safety of our transportation system and advance mobility for the benefit of all. There is an increasing need for automated data exchange between public agencies and private organizations to improve existing operations and enable new products and services. In addition, the provision of public safety is another overlapping area where first responders require up-to-date and reliable information to succeed in theirmissions.

This report evaluates the impacts associated with the following pilot changes that were made on and around the Richmond-San Rafael Bridge: (1) opening to traffic of the eastbound shoulder on the bridge’s lower deck between 2 PM and 7 PM every day (April 2018); (2) conversion of the westbound shoulder on the upper deck into a barrier-separated bike/pedestrian path (November 2019); and (3) conversion of an existing one-way bicycle path on the I-580 West Sir Francis Drake off-ramp overcrossing into a barrier-separated two-way path. Specific evaluations include the level of use by cyclists and pedestrians, impacts on traffic conditions and vehicle emissions, traffic compliance with the eastbound shoulder open/close periods, impacts on incident frequency, types, severity, and clearance times, and impacts on maintenance activities. These elements are to be used by Caltrans to determine whether the changes should be kept, in whole or in part. Evaluations show that the opening of the eastbound shoulder to traffic has significantly reduced travel times and incidents in Marin County through the elimination of the congestion that used to affect the I-580 East approach. While the addition of the path on the upper deck has slightly decreased peak bridge capacity and increased travel time variability on the Richmond approach, congestion on the approach remains close to historical averages. Bicycle traffic on the bridge path is highest on weekends, with an average of 483 cyclists entering the bridge on Saturdays and 355 on Sundays. Weekday traffic is much lower, at around 90 trips per day. Pedestrian traffic is usually very low, at less than 25 individuals per day. Some slight impacts from the addition of the path were also found on incident response and maintenance activities, but no significant impacts on incidents. A user survey further shows a positive perception of the path by cyclists, but a more negative view from motorists. The use of the modified path on the Sir Francis Drake overcrossing seems to mirror the use of the bridge path.

This report explores opportunities for employing autonomous driving technology to dampen stop-and-go waves on freeways. If successful, it could reduce fuel consumption and emissions. This technology was tested in an on-road experiment with 100 vehicles over one week. Public stakeholders were engaged to assess the planning effort and feasibility of taking the technology to the next level: a pilot involving 1000+ vehicles over several months. Considerations included the possible geographical boundaries, target fleets of vehicles, and suitable facilities such as bridges or managed lanes. Flow smoothing technology may improve the user experience and operations of managed lanes or bridges, however it may require external incentives such as reduced tolls to entice the traveling public to use it. This must be matched with other goals such as verifying vehicle occupancy. It might be possible for some hybrid solution that addresses both challenges to provide a way forward. A concept of operations needs to be developed specifically for a target road geometry and a California partner. This concept should benefit from lessons learned from previous pilot projects and will need to be defined so as to achieve both (1) a penetration rate sufficient to achieve measurable effects; and (2) sufficient quality and quantity of data to confirm benefits.

The California Department of Transportation (Caltrans) collects megabytes of data every day using a dedicated traffic sensing infrastructure. The collected data provide support for traffic management and system performance monitoring activities that are crucial for supporting the agency’s mission, vision, and strategic goals to strengthen stewardship and drive efficiency. Operating this vast detection system requires extensive resources in the form of engineering and maintenance support, along with millions in capital funds to keep the system running. Within the above context, alternate hybrid data collection models utilizing purchased or third-party data to augment existing data collection system capabilities may enable a reduction in the number of physical detection stations required while maintaining suitable accuracy for Caltrans’ purposes. In addition to the potential for cost savings, the reliance on fewer physical sensors also offers the potential to reduce the exposure of Caltrans employees to the occupational hazard of maintaining roadside detection stations, in alignment with the agency’s “safety first” strategic goal.

This report describes how current methods of estimating truck traffic volumes from existing fixed roadway sensors could be improved by using tracking data collected from commercial truck fleets and other connected technology sources (e.g., onboard GPS-enabled navigation systems and smartphones supplied by third-party vendors). Using Caltrans District 1 in Northern California as an example, the study first reviews existing fixed-location data collection capabilities and highlights gaps in the ability to monitor truck movements. It then reviews emerging data sources and analyzes the analytical capabilities of StreetLight 2021, a commercial software package. The study then looks at the Sample Trip Count and uncalibrated Index values obtained from three weigh-in-motion (WIM) and twelve Traffic Census stations operated by Caltrans in District 1. The study suggests improvements to StreetLight’s “single-factor” calibration process which limits its ability to convert raw truck count data into accurate traffic volume estimates across an area, and suggests how improved truck-related calibration data can be extracted from the truck classification counts obtained from Caltrans’ WIM and Traffic Census stations. The report compares uncalibrated StreetLight Index values to observed truck counts to assess data quality and evaluates the impacts of considering alternate calibration data sets and analysis periods. Two test cases are presented to highlight issues with the single-factor calibration process. The report concludes that probe data analytical platforms such as StreetLight can be used to obtain rough estimates of truck volumes on roadway segments or to analyze routing patterns. The results further indicate that the accuracy of volume estimates depends heavily on the availability of sufficiently large samples of tracking data and stable and representative month-by-month calibration data across multiple reference locations.

Dynamic toll pricing based on demand can increase transportation revenue while also incentivizing travelers to avoid peak traffic periods. However, given the unpredictable nature of traffic, travelers lack the information necessary to accurately predict congestion, so dynamic pricing has minimal effect on demand. Dynamic toll pricing also poses equity concerns for those who lack other travel options. This research explores a potential remedy to these concerns by using a simple “futures market” pricing mechanism in which travelers can lock in a toll price for expected trips by prepaying for future tolls, with the future price increasing as more travelers book an overlapping time slot. This approach encourages travelers to avoid driving during the peak periods when pricing increases toward capacity or to purchase trips in advance when the price remains low or discounted, thus using infrastructure capacity more efficiently. Travelers that do not prepurchase their trip are subject to the real-time market price, which is determined by dynamic congestion pricing. This futures-market mechanism can augment existing toll collection technologies and provide travelers with sufficient pricing information and purchasing options to preplan their travel and avoid excessive prices.

Most studies of the economic benefits of Advanced Traveler Information Systems (ATIS) have focused on the passenger transportation market. Few analyses have addressed the applications of ATIS to freight operations even though using ATIS to route or divert commercial vehicles can make a significant improvement in overall traffic flow and system performance. In this study, multivariate demand models were estimated based on large-scale surveys of commercial vehicle operators in California to determine the current use and perceptions of advanced information technologies, especially advanced traveler information systems (ATIS), among these firms. Data were used to identify organizational and operational characteristics that made these technologies more or less attractive, and to predict potential adoption of the technologies by carrier type. Many characteristics proved influential including company size, type and location of operation, length of load moves, provision of intermodal service and private versus for-hire status. A secondary goal was to explore the extent to which new logistics intermediaries,especially "infomediaries" are likely to develop advanced information technologies for the freight industry. Private sector providers of ATIS have not lived up to earlier expectations. While there still may be a significant future role for private sector involvement in providing this type of information, for now the burden appears to fall primarily on state and local transportation agencies.