California Partners for Advanced Transportation Technology

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.

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.

In order to improve corridor network operations, the vision of integrated corridor management (ICM) is to identify corridor managers who serve as experts for individual corridors, and to enable these managers to oversee corridor operations, to coordinate with partner agencies, and to improve collaborative, multiagency planning. While it makes sense to manage freeways, arterials, and transit in a coordinated way within a corridor, it is less clear how multiple corridors interact with each other, and how incidents and response plans along one corridor impacts a nearby corridor or multiple corridors. This project formulates recommendations and strategies for large scale traffic management and enabling multiple corridor management efforts and/or ICMs to work together. In addition, it identifies situations where conditions on one corridor influences management decisions on another corridor. To accomplish this, both probe data and traditional sensor data are analyzed to answer questions about aggregate traffic patterns on a multi-corridor scale.

Cybersecurity has become a critical issue in today’s world. In the past, security of our cyberspace was an important issue for some sectors of the economy, especially those dealing with financial information, personal identification related information, corporate systems and trade secrets, government classified information, and other types of data considered valuable targets for hackers. For other sectors, there was much less attention and resources dedicated to protection of our information and control systems. These sectors were often considered less likely to be targeted and a less valuable target.

Complete streets movement is a national effort to return to traditional streets in our cities to enhance livability, safely, accommodate all modes of travel, provide travel choices, ease traffic congestion, and promote healthier communities. The California Department of Transportation (Caltrans) and several local agencies in the State have developed implementation plans for complete streets. In this project, we developed and tested improved strategies and analysis methodologies for complete streets, taking into consideration the emerging advances in technology on control devices and data availability from multiple sources. The proposed improvements to the Highway Capacity Manual (HCM) methodology for bicycle LOS, accounts for protected bicycle lanes, traffic exposure, bicycle delay and pavement quality index. A survey was also used to calibrate the proposed bikeway evaluation models. Signal control strategies for complete streets were developed and tested, including signal optimization for pedestrians, bicycles and Transit Signal Priority (TSP) along major travel corridors in San Francisco.

This document is the final report for Task ID 3710 (65A0759), a project titled “Potential Erroneous Degradation of High Occupancy Vehicle (HOV) Facilities”. This report contains a compilation of three previous technical memorandums titled “Survey of Data-Mining Methods”, “Performance of Methods”, and “Magnitude of HOV Degradation”. HOV lane sensors in Caltrans’ Performance Management System (PeMS), are sometimes misconfigured as general-purpose lanes. In this situation, HOV lane data is mistakenly aggregated with general-purpose lane data and vice versa. The purpose of this project was to understand how widespread this problem might be and the extent to which it impacts performance reporting on the degradation of HOV lanes.

Freeway on-ramp metering (RM) has been extensively used as a traffic control strategy to regulate the entry of the on-ramp vehicles to prevent congestion at the freeway merging areas and preserve the freeway capacity. Benefits of RM include improved freeway travel times, improved travel time reliability, and accident reductions. Fixed-rate ramp metering strategies are based on historical data and implemented by time of day. Traffic responsive RM strategies are based on real time freeway traffic data provided by loop detectors at the vicinity of the on-ramp. Coordinated RM determine the metering rates at the ramps along a freeway corridor to minimize the delays or maximize the freeway throughput. The objective of this research was to evaluate the traffic performance of coordinated traffic responsive systems (CRM) currently implemented by Caltrans based on field data.

Quality data collection, processing, and analysis are foundational to good research, policy making and regulation development. With the rapid development of Connected Automated Vehicles (CAV) technologies, it is urgent for both researchers and policy makers to obtain and evaluate good quality CAV data to better understand CAV impacts. CAV hardware-in-the-loop (HIL) tests can expedite CAV performance evaluation and system implementation. This research aims at equipping an existing HIL test tool with data management functions. To this end, a database instance on MySQL has been integrated with an existing HIL test tool. The improved HIL test tool can greatly streamline CAV data collection and quality so that it is beneficial for performance analysis. A detailed comparison and selection of available database tools, database instance design and implementation have been performed to help other California institutes develop and improve their own systems. A user-friendly test tool setup guide and a specific user guide have been provided to enable potential users to easily get started using the data management functions. In addition, two example CAV tests are presented to demonstrate the detailed data collection and performance evaluation procedure. Those examples can serve as a guide to assist users in applying the HIL test tool in their own CAV tests.

This report investigates how Caltrans may incorporate third-party vendor data into its established system for performance measurement to improve accuracy of vehicle hours of delay (VHD) estimates and to enable smarter deployment of point-based sensors, such as loops. Methods are evaluated to project data from multiple sources, including multiple vendors and internal data feeds, onto the same domain of analysis so as to compute performance metrics with high fidelity. The recommended VHD estimation method depends on the infrastructure type and the data available. Overall a hybrid approach provides the best estimates of performance measures. A roadmap is proposed to begin using hybrid traffic data and to create opportunities to modify existing usage strategies of point-based sensors.

This report is the culmination of a year-long effort to develop a connected and automated vehicle (CAV) Strategic Plan for the California Department of Transportation (Caltrans). The purpose of the CAV Strategic Plan project is to define a vision and tactical strategy for Caltrans in preparation for CAV deployment in California and to begin a policy development process to keep California at the forefront of this emerging industry. This plan recommends actions for Caltrans to carry out within the next five years. Caltrans has a strong interest in planning for the fast-moving evolution in CAVs and intends to accelerate its leadership and outreach in this field.