policy brief

Intelligent Intersections Reduce Crashes and Will Support the Safe Introduction of Autonomous Vehicles

Publication Date

August 1, 2018

Author(s)

Alex Kurzhanskiy, Pravin Varaiya

Abstract

Intersections are dangerous. In the U.S., approximately 40% of all crashes, 50% of serious collisions, and 20% of fatalities occur in intersections. Intersections are challenging due to complex interactions among pedestrians, bicycles and vehicles; absence of lane markings; difficulty in determining who has the right of way; blind spots; and illegal movements (e.g., vehicles running red lights). Many cities have developed Vision Zero plans seeking to eliminate traffic injuries and deaths through modifications to road infrastructure, such as adding bike lanes and pedestrian refuge islands. These modifications can be expensive (e.g., the cost of a protected intersection can range between $250,000 to more than a $1 million) and have mixed safety results.It is claimed autonomous vehicles (AVs) will prevent 94% of all crashes involving human error. However, the safety performance of AVs is far below that of human-driven cars. In California, the number of accidents and disengagements per AV mile traveled is 13 to 100 times worse than human-driven cars. The AV fatality rate is equally as bad. AVs find intersections especially challenging; 58 of 66 (88%) AV crashes reported to the California Department of Motor Vehicles (DMV) occurred in intersections.Crashes in intersections occur because vehicles, pedestrians, and bicyclists are missing critical information. Intelligent intersections can provide this information at a relatively low cost of $25,000 to $100,000 per intersection. Intelligent intersections are able to report the traffic signal from all approaches, predict when the signal phase will change, relay information on blind spots, predict red light violations before they occur, and more. This information is broadcast via radio to every traveler in the intersection equipped with a smartphone or Bluetooth device.

policy brief

User Acceptance and Public Perception Regarding Automated Driving Systems

Abstract

Fully Automated Driving System (ADS) is one of the most innovative and fundamentally disruptive changes in transportation. This technology has the potential to resolve or mitigate current transportation problems, including reducing traffic accidents, congestion, energy consumption, and pollution. However, the extent of these impacts will depend heavily on public perception and widespread adoption of ADSs.

policy brief

Meeting SB 1 Transportation Systems Performance Goals

Publication Date

August 1, 2018

Author(s)

Abstract

The Road Repair and Accountability Act (SB 1) invests $5.4 billion annually over the next decade to help fix and repair California’s transportation system. As part of the SB 1 package, the Solutions for Congested Corridors Program was created and will receive $250 million annually to support multimodal corridor plans that make performance improvements along the state’s most congested highways. This funding will be crucial in maintaining and enhancing the State’s Transportation Management Systems (TMS). The State’s TMS, sometimes called Intelligent Transportation Systems (ITS), represents a broad class of technology assets on the state highway system, including field elements (e.g., ramp meters, traffic loops, electronic highway message signs), fiber and wireless communication systems, and central management systems (e.g., computer servers running software). To monitor progress and to assure accountability, SB 1 established a TMS performance outcome of “not less than 90 percent of the transportation management system units in good condition”, which Caltrans must meet by 2027.

research report

User Acceptance and Public Policy Implications for Deployment of Automated Driving Systems

Abstract

The objective of this project is to understand public perception of Automated Driving Systems (ADS) and to develop acceptance models that can help understand users’ intentions to use fully ADS, including both personally owned fully ADS and shared-use fully ADS. This project consisted of three phases, including (1) in-depth interviews with end-users of partially ADS, (2) interviews with experts in the transportation domain regarding policy gaps for deployment of ADS, and (3) focus group and online surveys to understand public perception and acceptance model of fully ADS. Findings from this study show that safety, vehicle control and compatibility, and trust are the three most critical factors that have influence on users’ acceptance of fully automated driving systems.

research report

Estimating Health Benefits, Cost-Effectiveness and Distributional Equity from California's Vehicle Emission Reduction Initiatives: Lessons from the San Joaquin Valley's Tune-In & Tune-Up Program

Abstract

N/A

research report

The Impacts of Infill Rail Transit Stations: Implications for the Shinn Station Proposal

Abstract

Infill rail transit stations are being implemented to improve access to transit as well as to encourage and support urban development and revitalization efforts.  The stations are relatively low-cost because they use existing tracks and equipment, but costs vary substantially depending on the complexity of the station design and its surroundings. Travel time savings can accrue to passengers using the infill station, but the added stop will increase time for some riders and may necessitate changes in equipment, schedule, or both.  Ridership at the infill station depends on the size of the area made more accessible as well as the amount of new development and intensified activity that occurs in its vicinity.  Findings from the literature and US examples are used together with a preliminary site assessment and interviews to identify the issues that would be raised by a proposed infill station linking multiple services in the San Francisco East Bay.   The concluding section summarizes factors that should be considered in evaluating the impacts of proposed infill stations and discusses the broader implications for regional planning.

research report

Meeting SB1 Transportation Systems Performance Goals

Abstract

This research project directly addresses the Caltrans policy question of “How to meet the SB 1 ten-year (2027) mandated preliminary performance outcomes for additional state highway investments?”  More specifically, the study focuses on performance outcome number 4: “Not less than 90 percent of the transportation management system units in good condition”. As part of this project, the research team evaluated the Caltrans performance-based methodology to achieve the 90% performance goal in addition to completing a review of relevant reports from the Federal Highway Administration (FHWA), state departments of transportation, and Caltrans. The research team also conducted multiple meetings, phone calls, and emails with Caltrans management. The research team found that the Caltrans Transportation Asset Management Plan, which governs its SB 1 implementation, follows Federal Highway Administration guidance and published best asset management practices. Further, Caltrans has a solid asset management plan in place to meet the SB 1 target. The research team also provides several recommendations including but not limited to: 1) Caltrans should continue working on defining deterioration rates or models for transportation management systems (TMS), 2) the state of being in “good condition” for transportation management systems must be more clearly defined, 3) Caltrans should continue monitoring innovations in asset management, and 4) Caltrans should consider conducting more pilots of performance-based ITS maintenance.

research report

Introducing an Intelligent Intersection

Publication Date

August 1, 2018

Author(s)

Aditya Medury, Alex Kurzhanskiy, Mengqiao Yu, Offer Grembek, Pravin Varaiya

Abstract

This project seeks to remove one important cause of intersection accidents: drivers, pedestrians, and cyclists make mistakes because they lack sufficient information about the movement of others as they proceed through an intersection. There is spatial and temporal uncertainty. This missing information can be supplied by an ‘intelligent intersection’. It describes the signal from all approaches; predicts when the signal phase will change; uses sensor data to determine which blind spots are occupied; and predicts red light violations before they occur. The intelligent intersection broadcasts this information via radio and can be received by a connected vehicle or indeed anyone in the intersection with a smartphone or Bluetooth device, so most intersection users will get this information. The objective of this research is to design intelligent intersection infrastructure and evaluate its performance in terms of safety and mobility benefits.

research report

Evaluating the Use of Zero-Emission Vehicles in Last Mile Deliveries

Abstract

While trucks may only represent a small share of the traffic in urban areas, they generate more than half of the overall emissions for specific contaminants (Jaller et al., 2016). One of the approaches to contend with such issues is to promote the use of new technologies and alternative fuel pathways. This work conducts an empirical assessment of the economic and driving patterns of trucks used for last-mile delivery given the increase in these vehicles serving even more densely populated areas (compared to the long-haul transport). The work concentrates on parcel deliveries, as they are typically used to transport the goods resulting from the rapidly growing e-commerce demand. The authors evaluate the performance by analyzing real driving data from parcel fleets (Walkowicz et al., 2014; Jaller et al., 2017a), and use the data to conduct life-cycle assessments (LCA) to estimate the various impacts. The contributions of the work are 1) comparison analyses between parcel delivery driving data with other delivery vocations to identify different freight patterns. The analyses show the differences and similarities between the driving patterns when using different drivetrains for a number of parcel delivery vocations. 2) Estimation of delivery tour length distributions (TLDs), and specific fuel consumption (SFC) for different drivetrains and vehicle classes. And, 3) estimate the total cost of ownership (TCO), including externalities, of different truck technologies under numerous scenarios that assume changes in fuel efficiency and incentives of certain drivetrains. Additional sensitivity analyses are conducted to identify the key parameters that affect the TCO. Among these, the analyses show the efficiency of purchases and use incentives for these technologies. The results can be extrapolated to a system-wide scope for similar vocations with common operational variables and the benefits and costs of transitioning to zero-emission technologies can be explored.