research report

Job Access, Agency Cost, and VMT Impacts of Offering Microtransit alongside Fixed-route Transit

Abstract

Public transit ridership has declined in major US cities over the past decade. Integrating traditional fixed-route transit with flexible microtransit has been proposed to enhance ridership, mobility, accessibility, and sustainability. This project surveyed California transit agencies on their microtransit services to identify challenges to integrating them with fixed-route services. An agent-based model combining the two modes of transit was developed to evaluate different operational designs. FleetPy, an open-source simulation tool, modeled microtransit dynamics. The study examined design impacts, such as fixed route headways and microtransit fleet size, in downtown San Diego and Lemon Grove, California. Results showed that while microtransit reduces fixed-route ridership and requires higher subsidies, it significantly boosts job accessibility.

Phd Dissertation

Strategic freight transportation contract procurement

Publication Date

June 30, 2006

Author(s)

Abstract

Auction based market clearing mechanisms are widely accepted for conducting business-to-business transactions. This dissertation focuses on the development of auction mechanism decision tools for freight transportation contract procurement. The dissertation categorizes the problems in freight procurement auctions arising in both spot markets and long term markets. Spot markets are widely employed over the Internet using standard classic auctions. For long-term markets, large shippers (typically manufacturing companies or retailers) have begun to use combinatorial auctions to procure services from trucking companies and logistics services providers. Combinatorial auctions involve very difficult optimization problems both for shippers and carriers. In the US truckload market few carriers have the technical sophistication to develop bids for combinatorial auctions. To address this problem we look at a different auction scheme termed a unit auction, where the shipper can exploit the economies of scope in the network and give the carriers the chance to bid on pre-defined packages similar to ‘lotting’ in supply chain procurement. The problems in developing contract allocations, called the winner determination problem, are computationally complex and large-scale. Hence the development of good heuristics is of utmost importance. Shippers have non-price business constraints, which must be included in the winner determination problems to closely match shipper business objectives. We develop winner determination problem formulations incorporating the non-price business constraints and develop Lagrangian based optimization methods and greedy approximation algorithms for both unit auctions and combinatorial auctions. Extensive empirical results are provided to test the performance of the heuristics against a standard integer-programming solver. Bidding in auctions from the carrier’s perspective is complicated as it involves taking into account the competitive behavior of other carriers and a carrier’s difficult network optimization problems. We develop bidding strategies for carriers in spot markets using concepts from economic auction theory. For long-term market bidding, we study the effects of demand uncertainty, competitive behavior, carrier network synergies and strategic pricing, and shipper’s winner determination problems on carrier bidding using optimization-based simulation analysis.

Phd Dissertation

Stochastic estimation of lane-changing probabilities and its application to incident detection

Publication Date

June 30, 1997

Author(s)

policy brief

New Insights from Satellite Data Show the Impact Trucks are Having on Communities in Southern California

Abstract

The rapid growth in freight transportation, particularly heavy-duty trucks, poses significant environmental and public health challenges for communities near major ports and freeways. In areas such as those near the Port of Los Angeles and the I-710 corridor, communities are exposed to elevated levels of air pollution, noise pollution, and associated health risks. Traditional traffic data collection methods primarily concentrate on gathering traffic volume data for freeway segments or smaller areas, often overlooking heavy-duty vehicles across roadway networks and in local communities.

To better understand the environmental impact and spatial distribution of heavy-duty truck traffic, this research employed a deep learning approach to analyze satellite imagery and publicly accessible spatial data. This approach allowed identification and categorization of heavy-duty trucks and shipping containers along critical freight routes and analysis of impacts on adjacent communities.

Preprint Journal Article

Charging Infrastructure Decisions by Heavy-duty Vehicle Fleet Operators: An Exploratory Analysis

Abstract

Insufficient charging/fueling infrastructure poses a major challenge to achieving U.S. policy goals for transitioning the heavy-duty vehicle (HDV) sector to zero-emission vehicles. Addressing the infrastructure needs of HDV fleet operators, who are key demand-side stakeholders, is crucial for developing effective solutions and strategies. This study investigates these needs through a fleet survey of California’s drayage sector, focusing on battery electric trucks. Key aspects examined include preferences for charging locations, access types, charging duration, time-of-day for charging, and innovative solutions like Truck-as-a-Service. Analyzing responses from 53 companies with varying fleet sizes, annual revenues, and operational characteristics, the study employed a comprehensive exploratory approach, utilizing descriptive analysis, thematic analysis, and hypothesis testing. Findings reveal that while most fleets preferred on-site charging, about a quarter, primarily smaller fleets with five or fewer trucks, preferred both on-site and off-site options. Private access was often favored for on-site facilities, though some respondents recognized the benefits of shared access for expanding operational coverage. The study also identified a need for faster charging solutions at both off-site and on-site locations, particularly for long-haul or mixed operations. Time-of-day preferences varied widely, driven by the need for efficient operations. Furthermore, a small proportion of participating fleets preferred Truck-as-a-Service over traditional procurement, predominantly among smaller fleets or those with lower revenues. The comprehensive research findings contribute to a deeper understanding of charging infrastructure needs and offer practical insights for policy practitioners and industry stakeholders committed to advancing zero-emission infrastructure. ​​

published journal article

Real-Time Truck Characterization System: A Pilot Implementation of the Freight Mobility Living Laboratory (FML2)

Abstract

California possesses multiple major freight gateway and logistics facilities that serve both the state and the entire U.S. But the economic, environmental, and local community impacts of trucks, especially heavy-duty trucks that are currently essential to our supply chains and freight transportation system remain poorly measured due to the lack of comprehensive and detailed truck activity data. This paper describes the pilot implementation of the real-time, scalable, and cost-efficient Freight Mobility Living Laboratory (FML2). This system provides truck characterizations across multiple attributes, such as truck body types, axle-based and Gross Vehicle Weight Rating (GVWR)-based classification and is currently deployed at 30 detection locations in Southern California along major freight corridors to support freight modeling and analysis needs. This paper details the design of the FML2 from edge data processing, predictive model development, communication architecture, and backend data storage to the real-time data dashboard to visualize the classification results. Three case studies have been presented at the end of the paper to demonstrate the potential of FML2 for use by both researchers and practitioners to gain further insights on truck activities.

policy brief

Shifting Future Electric Vehicle Trips to e-Bikes Could Help Reduce Electricity Demand at Critical Times in California

Abstract

California aims to replace gasoline and diesel light-duty vehicles (LDVs) with zero-emission LDVs, many of which will be plug-in battery electric vehicles (BEVs) and achieve 100% zero-carbon electricity by 2045. Large-scale plug-in BEV deployment will substantially increase electricity demand, particularly during peak hours (4:00pm to 9:00pm) when renewable energy is in short supply. Popular strategies for charging BEVs with electricity produced from renewable energy include smart charging and creating more energy storage that soaks up renewable energy during the day and dispenses it later when needed. These strategies, however, may not be enough. Consumer acceptance limits smart charging, and increased energy storage capacity is expensive. Another potential strategy involves lowering the overall demand for electricity by shifting BEV trips to electric-powered bicycles (e-bikes). While e-bikes cannot entirely replace BEV trips, they are ideal for short trips (five miles or less). Currently, 64% of US vehicle trips fall into the short trip category. Using synthetic travel pattern data from the San Diego region, we quantified the electric grid cost savings of shifting future BEV trips to e-bikes. For our analysis, we determined the passenger LDV trips that e-bikes could potentially replace. To provide an upper bound on replaceable trips, we considered trips that met the following criteria: LDV trips within home-based tours (a sequence of trips starting and ending at the home location) made by no more than two household members (between 16 and 70 years old), with less than five stops, under four hours in travel duration, and with individual trip distances up to seven miles long. We also created three scenarios that differ in terms of the tour purposes:
• Scenario 1: All purposes (e.g., work, recreation, eating out, etc.) except escort (i.e., transporting someone else to their activity) and shopping tours
• Scenario 2: All purposes except escort tours
• Scenario 3: All purposes

policy brief

Automated Vehicles and Transportation Network Companies Will Likely Impact the Efficacy of Transportation Pricing Strategies

published journal article

Dynamic Pricing for Maximizing Performance of High-Occupancy Toll Lanes Along a Freeway Corridor

Abstract

Single-occupancy vehicles (SOVs) are charged to use the high-occupancy-toll (HOT) lanes, while high-occupancy-vehicles (HOVs) can drive in them at no cost. The pricing scheme for HOT lanes has been extensively studied at local bottlenecks or at the network level through computationally expensive simulations. However, the HOT lane pricing study on a freeway corridor with multiple origins and destinations as well as multiple interacting bottlenecks is a challenging problem for which no analytical results are available. This paper attempts to fill the gap by proposing to study the traffic dynamics in the corridor based on the relative space paradigm. In this new paradigm, the interaction of multiple bottlenecks and trips can be captured with Vickrey’s bathtub model by a simple ordinary differential equation. The paper considers three types of lane choice behavior and analyze their properties. Then, it proposes a distance-based dynamic pricing scheme based on a linear combination of I-controllers. This closed-loop controller is independent of the model and feeds back the travel time difference between HOT lanes and general-purpose lanes. Given the mathematical tractability of the system model, this study analytically studies the performance of the proposed closed-loop control under constant demand and show the existence and stability of the optimal equilibrium. Finally, the results were verified with numerical simulations considering a typical peak period demand pattern.

published journal article

Fleet Operator Perspectives on Alternative Fuels for Heavy-duty Vehicles

Abstract

Despite the deployment of alternative fuel vehicles (AFVs) being one of the promising measures to reduce air pollutants and greenhouse gas emissions, AFVs still represent a very small share in the heavy-duty vehicle (HDV) sector. Understanding HDV fleet operator perspectives on alternative fuels is critical to developing effective demand-side strategies to facilitate wider and more rapid adoption of heavy-duty AFVs. This study explored California HDV fleet operator perspectives on viable alternative fuel options in the next 10–20 years, along with motivators for, and barriers to, such adoption. Eighteen in-depth qualitative interviews were conducted, after which thematic analysis was employed to analyze the interview data. Electric, hydrogen, compressed natural gas (CNG), and hybrid options were commonly perceived as viable in the 2030s by the participating organizations. Various optimistic aspects were addressed, including advanced technologies and emission reduction benefits (electric/hydrogen), continued fuel commitments due to their fleet or infrastructure investments already made (CNG), and lower complexity in fleet routing along with favorable driver acceptance (hybrid options). However, many concerns and uncertainties were also reported, including functional unsuitability (electric), uncompetitive upfront costs (hydrogen), unready infrastructure, perceived unavailability of vehicles, uncertain return on investment (electric/hydrogen), and unpromising support from state government (CNG). The study findings help fill a key knowledge gap in AFV fleet adoption research regarding HDV fleet operator perspectives, and contribute to developing demand-side strategies to aid the success of AFV diffusion throughout the HDV market.