Publications
List of books, book chapters, journal articles, policy briefs, white papers, and thesis.
2026
- A holistic continuous approximation framework for strategic last-mile distribution planningBlessy Kirubakaran , Anmol Pahwa, Surendra Reddy Kancharla , and 1 more authorTransportation Research Interdisciplinary Perspectives
The conventional approach to modelling last-mile distribution operations involves use of the discrete formulation method which renders a representative mathematical model necessitating use of sophisticated solution techniques. While such an intensive approach is justified when decision-makers require a precise plan to support operational planning, this level of precision is redundant for strategic planning, wherein available information is representative but not necessarily exact. To this end, continuous approximation (CA) method offers a practical alternative with use of continuous density functions that estimate parameters approximately, thus striking a balance between estimation accuracy and computational effort. However, typical CA-based routing frameworks assume a simplified distribution environment that significantly limits the capability of such frameworks to accurately model last-mile operations in real-world distribution environments, such as postal service, e-commerce, q-commerce, waste collection, emergency service etc. Thus, the objective of this work is to develop a holistic CA framework for the Vehicle Routing Problem (VRP) to facilitate strategic last-mile distribution planning within diverse logistic settings. Specifically, this study synthesizes a total of 1080 distribution environments, each with peculiar distribution structure and distinctive customer characteristics. Subsequently, it optimizes last-mile distribution for distribution environment instance using an Adaptive Large Neighborhood Search (ALNS) metaheuristic. Finally, this work develops a robust CA-based functional form through symbolic regression to precisely estimate the total distribution tour length across the various distribution environments. In doing so, this work supports strategic decision-making for a wide scope of logistic operators that may have representative but not necessarily exact information.
- Explicit consideration of human exposure to minimize freight routing impactsSarah Dennis-Bauer , Anmol Pahwa, and Miguel JallerTransportation Research Part D: Transport and Environment
As freight demand grows, so do its negative externalities, such as health and environmental impacts. This study integrates a reduced-complexity air quality model (RCM) with a multimodal traffic assignment model to analyze the scenario in which trucks minimize their public health costs. The study compares the least health-cost path (LHCP) with the shortest, fastest, and least-emissions paths. Two LHCP scenarios with geofences around sensitive populations differed in travel time (TT), health costs, and community impacts. LHCP had 10.9% higher TT and 29% lower costs than the next lowest scenarios. Under the LHCP, within-scenario burdens increased for some communities (e.g., PM2.5 burden) but decreased for others (e.g., ozone burden). The other routing scenarios similarly produced differential effects across communities, highlighting tradeoffs. Geofences increased TT and health costs relative to the LHCP and produced different community impacts. This study provides new, actionable insights into methods to mitigate transportation externalities, particularly in communities.
2025
- Assessing the sustainability of last-mile distribution strategies to manage expedited shipping with dynamic and stochastic demandAnmol Pahwa, and Miguel JallerTransportation Research Part E: Logistics and Transportation Review
As many e-retailers compete through increasingly consumer-focused services, urban freight faces a critical need for sustainable alternate last-mile distribution practices. While previous research has investigated the performance of various distribution strategies under different planning and network design scenarios, their performance under the dynamic and stochastic conditions inherent to consumer-focused services (e.g., expedited deliveries) is not well understood. This study introduces a dynamic-stochastic last-mile network design (DS-LMND) problem, formulated as a multi-echelon capacitated location routing problem with time-windows (ME-C-LRP-TW), to address this gap. Consequently, this work develops a Monte Carlo simulation–optimization framework integrated with an adaptive large neighborhood search (ALNS) metaheuristic to solve the problem. Using this framework, the authors configure the distribution structure and simulate last-mile operations for each distribution strategy. For these configured distribution structures, this work determines economic viability, environmental efficiency, and social equity – the three pillars of sustainability. Further, the authors determine the impact of demand uncertainties on the sustainability of last-mile distribution through the value of information (VI) and coefficient of variance (CV) metrics. In doing so, this work a) estimates the efficacy of conventional distribution strategy; b) confirms the competitiveness of electric delivery vehicles; c) evaluates the effectiveness of crowdsourced delivery services; d) advances the case for consolidation-based multi-echelon distribution strategies; e) establishes the rationale for customer pickups; and f) develops the use case for drone and robots, to cater to dynamic and stochastic demand with expedited shipping.
- Last-Mile Delivery Innovations and Best Practices in the Age of E-commerceMiguel Jaller , and Anmol PahwaNational Center for Sustainable Trasnsportation
2024
- Evaluating private and system-wide impacts of freight eco-routingAnmol Pahwa, and Miguel JallerTransportation Research Part D: Transport and Environment
Freight is crucial for economic development, but the trucks hauling this freight significantly contribute towards greenhouse gas emissions, advancing global climate change and criteria pollutant emissions that affect local community health. Hence, this work explores the opportunities and challenges associated with freight eco-routing to mitigate these freight-related externalities in Southern California. To this end, the authors establish the private impacts of a single carrier eco-routing its fleet of freight vehicles with a point-to-point routing tool. Further, the authors investigate network-wide freight eco- routing’s system effects with the novel origin-based algorithm for multi-class Traffic Assignment by Paired Alternative Segments (mTAPAS). Overall, the study showcases the potential opportunities with freight eco-routing in reducing transportation-related externalities. However, it also highlights implementation challenges due to a lack of monetary incentives for carriers and regulators to account for these externalities in their decision-making.
- Benefits, Challenges, and Opportunities of Different Last-Mile Delivery StrategiesMiguel Jaller , Anmol Pahwa, Jean-Daniel Saphores , and 1 more authorUniversity of California Institute of Transportation Studies
As online shopping nears its third decade, it is clear that itsimpacts on urban goods flow are profound. Increased freight traffic and related negative externalities such as greenhouse gas emissions and local air pollution can impede sustainabilitygoals. In response, e-retailers are exploring innovative distributionstrategies to enhance last-mile delivery sustainability and efficiency. They use urban consolidation centers with light-duty vehicles like electric vans and cargo bikes, establish alternative customer pickup points, and deploy crowdsourced delivery networks. Advanced technologies that may streamline deliveries, such as autonomous delivery robots and unmanned aerial vehicles, are being tested. University of California Davis and Irvine researchers have investigated these strategies under economic viability, environmental efficiency, and social equity frameworks. Different modeling approaches were implemented to evaluate last-mile network designs and the potential for decarbonizing delivery fleets by switching to electric vehicles. Key findings suggest that while these innovative strategies offer substantial environmental benefits and reduce operational costs, they also present challenges like higher initial investments and operational hurdles. The study emphasizes the need for ongoing innovation and careful strategy implementation to balance sustainability with urban delivery systems’ economic and service reliability demands.
2023
- Estimating last-mile deliveries and shopping travel emissions by 2050Miguel Jaller , Runhua Ivan Xiao , Sarah Dennis-Bauer , and 2 more authorsTransportation Research Part D: Transport and Environment
This study investigates the potential ramifications of e-commerce on shopping behaviors, travel, and residential deliveries by the year 2050. A comprehensive modeling framework has been devised to predict alterations in shopping behavior, generate future synthesized populations for major metropolitan statistical areas (MSAs), and estimate parameters associated with shopping travel and last-mile delivery alternatives. This framework relies on an integrated simulation that produces shopping and delivery travel, incorporating techniques such as Weighted Multinomial Logit and Monte Carlo simulation. The findings reveal that population growth and socio-demographic factors will differentially impact shopping behaviors across various MSAs. Furthermore, shopping travel and delivery patterns are subject to the influence of the spatial distribution of trips and transportation mode selection. The study underscores the significance of contemplating the implementation of clean energy fleets and effective transportation strategies to mitigate the negative externalities related to shopping activities.
- Assessing last-mile distribution resilience under demand disruptionsAnmol Pahwa, and Miguel JallerTransportation Research Part E: Logistics and Transportation Review
The COVID-19 pandemic led to a significant breakdown of the traditional retail sector resulting in an unprecedented surge in e-commerce demand for the delivery of essential goods. Consequently, the pandemic raised concerns pertaining to e-retailers’ ability to maintain and efficiently restore level of service in the event of such low-probability high-severity market disruptions. Thus, considering e-retailers’ role in the supply of essential goods, this study assesses the resilience of last-mile distribution operations under disruptions by integrating a Continuous Approximation (CA) based last-mile distribution model, the resilience triangle concept, and the Robustness, Redundancy, Resourcefulness, and Rapidity (R4) resilience framework. The proposed R4 Last Mile Distribution Resilience Triangle Framework is a novel performance-based qualitative-cum-quantitative domain-agnostic framework. Through a set of empirical analyses, this study highlights the opportunities and challenges of different distribution/outsourcing strategies to cope with disruption. In particular, the authors analyzed the use of an independent crowdsourced fleet (flexible service contingent on driver availability); the use of collection-point pickup (unconstrained downstream capacity contingent on customer willingness to self-collect); and integration with a logistics service provider (reliable service with high distribution costs). Overall, this work recommends the e-retailers to create a suitable platform to ensure reliable crowdsourced deliveries, position sufficient collection-points to ensure customer willingness to self-collect, and negotiate contracts with several logistics service providers to ensure adequate backup distribution.
- Assessing Sustainability of E-Commerce Goods DistributionAnmol PahwaUniveristy of California, Davis
The growth of e-commerce, spurred by the internet, has transformed urban goods flow. What would previously have been a trip to a store is now a hassle-free delivery to the home. With consolidated and optimized delivery tours, e-commerce has the potential to make urban goods flow economically viable, environmentally efficient, and socially equitable. However, as e-retailers compete with increasingly consumer-focused service, urban freight witnesses a significant increase in associated distribution costs and negative externalities including greenhouse gas emissions advancing global climate change, as well as criteria pollutant emissions worsening local air quality and thus affecting those living close to logistics clusters. Thus, considering the potential of e-commerce to render economically viable, environmentally efficient, and socially equitable urban goods flow, it is pertinent to understand the opportunities and challenges associated with urban freight in light of the increasingly consumer-focused e-commerce distribution. To this end, the author develops A) the impact of e-commerce on urban goods distribution, with a simulation framework founded on consumer shopping behavior simulating urban goods flow, B) the impact of key delivery environment parameters on e-commerce goods distribution, with a continuous approximation (CA) framework modeling last-mile distribution operation for an e-retailer, and C) the impact of demand uncertainty on e-commerce goods distribution, with a discrete optimization framework formulating a last-mile network design (LMND) problem as a dynamic-stochastic two-echelon capacitated location routing problem with time-windows (DS-2E-C-LRP-TW), addressed using an adaptive large neighborhood search (ALNS) metaheuristic algorithm.
- Overview of innovations in urban freightMiguel Jaller , Anmol Pahwa, Carlos Otero-Palencia , and 1 more authorIn Handbook on City Logistics and Urban Freight
This chapter discusses innovations in urban freight, concentrating on changes in consumer behavior and retail distribution by the advent of omni-channel retailing and the rapid growth of e-commerce. The chapter provides an overview of the relevant impacts on the system, such as changes in logistics structures; information and data management; considerations of passenger and freight travel substitution, complementarity, and induced demand effects; last-mile delivery practices and services (e.g., expedited deliveries, cargo bikes, micro-hubs, zero-emission vehicles); and other innovations that have the potential to fundamentally change how logistics systems are planned and operated in the form of hyperconnected systems. In addition, this chapter discusses a few new, automated technologies (e.g., aerial unmanned delivery vehicles and autonomous delivery robots), and delivery practices brought about by developments in information and communication technologies and the shared economy (e.g., app-based crowdsourced delivery services). Throughout the discussion, the authors provide insights about the sustainability of the new behaviors and innovations, and ultimately put forward some research recommendations.
- Sketch Planning Tool for Sustainable and Resilient Urban Goods Distribution: User ManualMiguel Jaller , and Anmol PahwaMETRANS Transportation Center
The urban goods distribution system is a critical component of modern society. However, the COVID-19 pandemic exposed significant vulnerabilities in this system as it struggled to cope with an unforeseen surge in demand. This crisis highlighted the urgent necessity of developing a resilient and sustainable urban goods distribution system capable of efficiently recovering from high-severity disruptions. Our research team previously developed a novel analytical model, the Robustness, Redundancy, Resourcefulness, and Rapidity - Last-Mile Distribution - Resilience Triangle (R4-LMD-RT) framework to address this challenge. In line with the previous work, this work aims to create a sketch-planning tool tailored for local jurisdictions based on the R4-LMD-RT model. This tool assists in strategically planning urban goods distribution systems, identifying land use requirements, and proposing sustainable and resilient strategies, such as urban consolidation, micro-hubs, alternative delivery points, and zero-emission vehicles. As part of a case study, the authors validate the effectiveness of this planning tool by applying it to the city of Los Angeles for a COVID-19-like disruption. This research outcome paves the way for more sustainable and resilient urban goods distribution systems in the post-pandemic world.
- Coping with the Rise of E-commerce Generated Home Deliveries through Innovative Last-mile Technologies and StrategiesMiguel Jaller , and Anmol PahwaNational Center for Sustainable Trasnsportation
E-commerce can potentially make urban goods flow economically viable, environmentally efficient, and socially equitable. However, as e-retailers compete with increasingly consumer-focused services, urban freight witnesses a significant increase in associated distribution costs and negative externalities, particularly affecting those living close to logistics clusters. Hence, to remain competitive, e-retailers deploy alternate last-mile distribution strategies. These alternate strategies, such as those that include the use of electric delivery trucks for last-mile operations, a fleet of crowdsourced drivers for last-mile delivery, consolidation facilities coupled with light-duty delivery vehicles for a multi-echelon distribution, or collection-points for customer pickup, can restore sustainable urban goods flow. Thus, in this study, the authors investigate the opportunities and challenges associated with alternate last-mile distribution strategies for an e-retailer offering expedited service with rush delivery within strict timeframes. To this end, the authors formulate a last-mile network design (LMND) problem as a dynamic-stochastic two-echelon capacitated location routing problem with time-windows (DS-2E-C-LRP-TW) addressed with an adaptive large neighborhood search (ALNS) metaheuristic.
2022
- A cost-based comparative analysis of different last-mile strategies for e-commerce deliveryAnmol Pahwa, and Miguel JallerTransportation Research Part E: Logistics and Transportation Review
The growth of e-commerce has bridged the gap between the consumer and the retailer, bringing prosperity for both. However, in a quest to achieve even larger profits and market share, e-retailers compete to offer consumers cheaper shipping, expedited deliveries, free returns, and other lucrative deals. To keep pace with these growing needs of e-commerce, e-retailers have piloted various alternative distribution strategies. To aid a fuller understanding of the costs and benefits of these distribution strategies in diverse delivery environments, this work develops a multi-echelon last-mile distribution model using Continuous Approximation (CA) techniques. The model results suggest that traditional last-mile delivery with diesel trucks is a good fit for e-retailers delivering in dense environments with lenient temporal constraints (parcel service), a strategy that allows for demand consolidation and thus low-cost low-emission distribution. For e-retailers delivering in sparsely populated environments with stringent temporal constraints (grocery delivery), this work finds outsourcing alternatives (crowdsourced delivery, customer self-collection) to render low-cost distribution albeit with high emissions. As a result, the authors suggest the use of low-volume low-pollution vehicles from smaller consolidation facilities close to the market to provide expedited deliveries at fairly low costs and emissions. The analysis bolsters the case for the use of electric trucks for last-mile deliveries, as the study finds an electric truck fleet to not only eliminate tailpipe emissions but also to lower distribution costs compared to a diesel truck fleet. Thus, with this work the authors discuss the opportunities and challenges associated with different last-mile strategies for e-commerce delivery.
- National Impacts of E-commerce Growth: Development of a Spatial Demand Based ToolMiguel Jaller , Runhua Xiao , Sarah Dennis , and 2 more authorsNational Center for Sustainable Trasnsportation
This project aims to study the impacts of e-commerce on shopping behaviors and related externalities. The objectives are divided into five major tasks in this project. Methods used include Weighted Multinomial Logit (WMNL) models, time series forecasting, and Monte Carlo (MC) simulations. The American Time Use Survey (ATUS) and the National Household Travel Survey (NHTS) databases are used for identifying the independent and dependent variables for behavioral modeling. At the same time, the researchers collected all MSA population data from the U.S. Census Bureau and combined the shares of each variable from ATUS to generate a synthesized population, which serves as input into the MC simulation framework together with the behavioral model. This simulation framework includes the generation of shopping travel parameters and the calculation of negative externalities. The authors do this to estimate e-commerce demand and impacts every decade until 2050. The results and analyses provide information that supports the generation of shopping travel and the estimations of a series of negative externalities using MC simulation, which includes shopping travel parameters, last-mile delivery parameters, and emission rate per person. For different parameters, a unique probability distribution or a regression relation is obtained for different MSAs, and this distribution is fed into the subsequent MC simulation. Finally, the researchers simulated shopping behaviors for synthesized populations (until 2050) and to estimate the expected negative externalities. The MC simulation generates aggregate average vehicle miles traveled (VMT) and emissions (negative externalities) for different shopping activities in the planning years and different MSAs.
- Improving Environmental Justice and Mobility in Southeast Los AngelesGenevieve Giuliano , Marlon Boarnet , Miguel Jaller , and 8 more authorsPacific Southwest Region Univeristy Transportation Center
This case study is part of the Climate Smart Transportation and Communities Consortium (CSTACC), case studies that were conducted in various locations throughout the state to analyze environmental justice issues in low income, communities of color. This study took place in southeast Los Angeles County in partnership with the Southeast Los Angeles Collaborative (SELAC), a non-profit community-based umbrella organization representing 8 cities and several unincorporated areas. The case study has two parts. The first part examines impacts of heavy duty trucks and finds the main problems to be traffic safety and particulate emissions. An analysis of regional freight traffic reveals that current and planned regulations to achieve zero emission truck targets will significantly reduce truck-related emissions. A local analysis showed higher than average truck involved crashes and safety hot spots. Local traffic management strategies are recommended to increase safety. The second part examines public transit job accessibility. Transit accessibility depends on both service level and access to bus stops. We recommend that bike share and car share options be explored to reduce travel times to and from bus stops.
- Assessing E-retailer’s Resilience During the COVID-19 PandemicMiguel Jaller , and Anmol PahwaUniveristy of California, Davis
The COVID-19 pandemic led to a significant breakdown of the traditional retail sector, resulting in a substantial surge in ecommerce demand for the delivery of essential goods. The e-retailers coped with this surge in demand, albeit while operating at a much lower level of service than usual, by outsourcing part of their operations through: crowdsourced delivery fleets, alternative pickup/delivery locations, 3rd party logistics service providers, etc. Given e-retailers’ role in the supply of essential goods, the pandemic raised concerns pertaining to e-retailers’ ability to maintain and efficiently restore level of service in similar market disruptions. This study assesses the resilience of last-mile distribution operations under disruptions, by integrating a continuous approximation–based last-mile distribution model; the resilience triangle concept; and the Robustness, Redundancy, Resourcefulness, and Rapidity (R4) resilience framework. The resulting integrated tool, the R4 Resilience Triangle Framework, is a novel performance-based qualitative-cum-quantitative domain-agnostic framework (where “domain” means “discipline,” such as engineering, economics, etc.). Through a set of empirical analyses, this study highlights the opportunities and challenges of different distribution/outsourcing strategies to cope with disruption. For example, the study analyzed the use of an independent crowdsourced fleet (flexible service contingent on driver availability); the use of collection-point pickup (unconstrained downstream capacity contingent on customer willingness to self-collect); and integration with a logistics service provider (reliable service with high distribution costs). Overall, the e-retailers must create a suitable platform to ensure reliable crowdsourced deliveries, position sufficient collection-points to ensure customer willingness to self-collect, and negotiate contracts with several logistics service providers to ensure adequate backup distribution.
2021
- Cargo routing and disadvantaged communitiesMiguel Jaller , Anmol Pahwa, and Michael ZhangPacific Southwest Region Univeristy Transportation Center
Freight is fundamental to economic growth, however, the trucks that haul this freight are pollution intensive, emitting criteria pollutants and greenhouse gases at high rates. The increasing volume and time-sensitivity of freight demand over the past decade has encouraged carriers to take the fastest route, which is often not an eco-friendly route. The increase in urban freight movement has thus brought along negative externalities such as congestion, emissions, and noise into cities. Alternative fuel technologies, such as electric trucks and hydrogen-fuel trucks can significantly reduce freight-related emissions. However, despite their lower operational costs, the high purchase cost and consequent longer payback periods compared to traditional vehicles, have resulted in slow adoption rates. Since the need to reduce global greenhouse gas emissions and local criteria pollutants is immediate, accounting for externalities in carriers’ tactical and operational decision-making in the form of eco-routing can bring about desired reductions in emissions. The objectives of this work are to explore the possibilities and potential of eco-routing from the perspective of the carrier, in terms of cost-benefits and trade-offs, and from the perspective of the regulator, in terms of network-wide effects and policy initiatives that could encourage carriers to eco-route. This study evaluates reduction in global greenhouse emissions and local criteria pollutants, with a particular focus on direct impacts on disadvantaged communities in the Southern California Association of Governments (SCAG) region.
- The sustainability of alternative last-mile delivery strategiesMiguel Jaller , and Anmol PahwaNational Center for Sustainable Trasnsportation
- Minimizing the Impact of Freight Traffic on Disadvantaged CommunitiesMiguel Jaller , and Anmol PahwaPacific Southwest Region Univeristy Transportation Center
2020
- Evaluating the environmental impacts of online shopping: A behavioral and transportation approachMiguel Jaller , and Anmol PahwaTransportation Research Part D: Transport and Environment
Various fields and commercial sectors have witnessed a transformation with the advent of the internet. In the last decade, the retail sector in particular has witnessed the massive growth of e-commerce. This has also significantly altered our shopping experiences, influencing a range of decisions, from where, how, and how much to shop. With the consistent growth of e-commerce transactions, more trucks than ever before are entering cities today, bringing with them the negative externalities of increased congestion and pollution. This study first unravels underlying shopping behaviors–both in-store and online–using the 2016 American Time Use Survey (ATUS) data. The authors also develop an econometric behavioral model to understand the factors that affect shopping decisions. At a macro level, the disaggregate individual shopping behaviors are studied by implementing the model to synthetic populations to estimate potential vehicle miles traveled and environmental emissions in two metropolitan areas, Dallas and San Francisco (SF). Finally, the study estimates the impacts of rush deliveries, basket size, and consolidation levels by developing a breakeven analysis between in-store and online shopping. These results confirm the importance of managing the urban freight system, including delivery services and operations, to foster a more sustainable urban environment.
- Automation, electrification, and shared mobility in urban freight: opportunities and challengesMiguel Jaller , Carlos Otero-Palencia , and Anmol PahwaTransportation Research Procedia
Automation, electrification, and shared mobility are 3 the Revolutions (3Rs) in the passenger transport sector that have resulted in efficiency improvements, cost reductions, and low carbon emissions. Although there is interest about their implementation in freight transportation, the development of multiple 3Rs initiatives in freight represent a challenge for academics and practitioners, especially to anticipate potential obstacles in last mile operations. Consequently, this paper discusses the challenges and opportunities for the introduction of the 3Rs in the last mile. Specifically, the paper provides an overview of different technologies, at different levels of market readiness, and explores their benefits and/or unintended consequences. The main contribution of this exploratory research is informing the current state of the 3Rs and providing insights to develop policies, plans or initiatives that promote these revolutions in the urban freight system.
- Analytical modeling framework to assess the economic and environmental impacts of residential deliveries, and evaluate sustainable last-mile strategiesMiguel Jaller , and Anmol PahwaNational Center for Sustainable Trasnsportation
In the last decade, e‐commerce has grown substantially, increasing business‐to‐business, business‐to‐consumer, and consumer‐to‐consumer transactions. While this has brought prosperity for the e-retailers, the ever-increasing consumer demand has brought more trucks to the residential areas, bringing along externalities such as congestion, air and noise pollution, and energy consumption. To cope with this, different logistics strategies such as the introduction of micro-hubs, alternative delivery points, and use of cargo bikes and zero emission vehicles for the last mile have been introduced and, in some cases, implemented as well. This project, hence, aims to develop an analytical framework to model urban last mile delivery. In particular, this study will build upon the previously developed econometric behavior models that capture e-commerce demand. Then, based on continuous approximation techniques, the authors will model the last-mile delivery operations. And finally, using the cost-based sustainability assessment model (developed in this study), the authors will estimate the economic and environmental impacts of residential deliveries under different city logistics strategies.
- Automated Vehicles are Expected to Increase Driving and Emissions Without Policy InterventionCaroline Rodier , Miguel Jaller , Elham Pourrahmani , and 3 more authorsNational Center for Sustainable Trasnsportation
2018
- Automated vehicle scenarios: Simulation of system-level travel effects using agent-based demand and supply models in the San Francisco Bay areaCaroline Rodier , Miguel Jaller , Elham Pourrahmani , and 3 more authorsNational Center for Sustainable Trasnsportation
In much in the same way that the automobile disrupted horse and cart transportation in the 20th century, automated vehicles hold the potential to disrupt our current system of transportation in the 21st century. Experts predict that vehicles could be fully automated by as early as 2025 or as late as 2035. Methods are needed to help the public and private sector understand automated vehicle technologies and their system-level effects. First, we explore the effects of automated vehicles using the San Francisco Bay Area Metropolitan Transportation Commission’s activity-based travel demand model (MTC-ABM). The simulation is unique in that it articulates the size and direction of change on travel for a wide range of automated vehicles scenarios. Second, we simulate the effects of the introduction of an automated taxi service on conventional personal vehicle and transit travel in the San Francisco Bay Area region and use new research on the costs of automated vehicles to represent plausible per mile automated taxi fares. We use an integrated model for the San Francisco Bay Area that includes the MTC-ABM combined with the agent-based MATSim model customized for the region. This model set uses baseline travel demand data from the region’s official activity-based travel model and dynamically assigns vehicles on road and transit networks by the time of day. Third, we use the MTC-ABM and the MATSim dynamic assignment model to simulate different “first” mile transit access services, including ride-hailing (Uber and Lyft) and ridesharing (Uber Pool/Lyft Line and Via) with and without automated vehicles. The results provide insight into the relative benefits of each service and automated vehicle technology and the potential market for these services.
2017
- Methodology for using GPS data from buses to assess link-based travel time variationAnmol Pahwa, Sneha Lakhotia , and Geetam TiwariJournal of the Eastern Asia Society for Transportation Studies
As cities are growing, both in size and complexity, it has become increasingly important for transportation systems to integrate intelligent systems to improve their service quality. Transit systems are progressively using global positioning system (GPS) to extract real-time data of the transit units. These data can be used to extract multiple traffic stream characteristics. However, the primary step in using the GPS data is to process it and make it suitable for analyses. In this paper, we have discussed various issues which need to be resolved from the raw GPS data, which we obtained for a period of one month for 25 bus routes in Delhi. Subsequently, we have outlined a sequential approach to select the ideal method for processing the GPS data, so as to estimate travel time and speed on these routes. These measures can then be used further for assessing other traffic stream characteristics.