published journal article

Strategic hydrogen refueling station locations with scheduling and routing considerations of individual vehicles

Transportation Science

Abstract

A hydrogen refueling station siting model that considers scheduling and routing decisions of individual vehicles is presented. By coupling a location strategy of the set covering problem (SCP) and a routing and scheduling strategy of the household activity pattern problem, this problem falls into the category of location routing problems. It introduces a tour-based approach to refueling station siting, with tour-construction capability within the model. There are multiple decision makers in this problem: the public sector as the service provider and the collection of individual households that make their own routing decisions to perform a given set of out-of-home activities together with a visit to a refueling location. A solution method that does not require the full information of the coverage matrix is developed to reduce the computational burden. Compared to the point-based SCP the results indicate that the minimum infrastructure requirement may be overestimated when vehicle (refueling demand)-infrastructure (refueling supply) interactions with daily out-of-home activities are excluded.

Suggested Citation
Jee Eun Kang and Will Recker (2015) “Strategic hydrogen refueling station locations with scheduling and routing considerations of individual vehicles”, Transportation Science, 49(4), pp. 767–783. Available at: 10.1287/trsc.2014.0519.

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

Suggested Citation
Ritun Saha, Kotaro Yamada, Brian Tarroja, Michael Hyland and Kate Forrest (2024) Shifting Future Electric Vehicle Trips to e-Bikes Could Help Reduce Electricity Demand at Critical Times in California. Policy Brief. UC ITS. Available at: https://doi.org/10.7922/g22z13wv.

conference paper

Improving Infrastructure and Community Resilience with Shared Autonomous Electric Vehicles (SAEV-R)

2023 IEEE Intelligent Vehicles Symposium (IV)

Abstract

We propose using surface and aerial shared autonomous electric vehicles (SAEVs) to improve the resilience of infrastructure and communities, or SAEV-R. In disruptive events, SAEVs can be temporarily deployed to evacuate and rescue at-risk populations, provide essential supplies and services to vulnerable households, and transport repair crews and equipment. We present a modeling framework for feasibility analysis and strategic planning associated with deploying SAEVs for disaster relief. The framework guides our examination of three scenarios: a hurricane-induced power outage, a pandemic-affected vulnerable population, and earthquake-damaged infrastructure. The results demonstrate the flexibility of the proposed framework and showcase the potential and versatility of SAEV-R systems to improve resilience.

Suggested Citation
Jiangbo Gabe Yu, Michael F. Hyland and Anthony Chen (2023) “Improving Infrastructure and Community Resilience with Shared Autonomous Electric Vehicles (SAEV-R)”, in 2023 IEEE Intelligent Vehicles Symposium (IV). 2023 IEEE Intelligent Vehicles Symposium (IV), pp. 1–6. Available at: 10.1109/IV55152.2023.10186785.

published journal article

Characterization of taxi fleet operational networks and vehicle efficiency: Chicago case study

Transportation Research Record

Publication Date

October 1, 2018

Author(s)

Ying Chen, Michael Hyland, Michael Patrick Wilbur, Hani Mahmassani

Abstract

Taxi fleets serve a significant and important subset of travel demand in major cities around the world. This paper characterizes the Chicago taxi fleet operational network using complex network metrics and analyzes the operational efficiency of individual taxis over the past four years using an extensive taxi-trip dataset. The dataset, recently released by the city of Chicago, includes the pickup and drop-off census tracts and time stamps for over 100 million taxi trips. The paper explores year-over-year changes in the spatial distribution of Chicago taxi travel demand. The taxi pickup and drop-off census tract locations are modeled as nodes, and links are generated between unique pickup and drop-off node pairs. The analysis shows that high-demand pickup and drop-off location pairs in 2013 generated similar trip volumes in 2016; however, the low-demand pairs in 2013 generated significantly fewer trips in 2016. Additionally, this paper presents temporal efficiency and spatial efficiency metrics. The temporal efficiency metric determines the percentage of in-service time taxis are productive (i.e., transporting travelers), rather than empty. The spatial efficiency metric measures the percentage of taxi miles that are productive (i.e., loaded), rather than empty. The efficiency analysis of the Chicago taxi fleet shows that, for most taxis, around 50% of their in-service time and travel distance are unproductive. This inefficiency negatively affects the profitability of individual drivers and the fleet, traffic congestion, vehicle emissions, the service quality provided to customers, and the ability of taxi services to compete with emerging mobility services.

Suggested Citation
Ying Chen, Michael Hyland, Michael Patrick Wilbur and Hani S. Mahmassani (2018) “Characterization of taxi fleet operational networks and vehicle efficiency: Chicago case study”, Transportation Research Record, 2672(48), pp. 127–138. Available at: 10.1177/0361198118799165.

published journal article

Environment, land use and urban policy.

Transportation Research Part A: Policy and Practice

Publication Date

February 1, 2003
Suggested Citation
Jean-Daniel Saphores (2003) “Environment, land use and urban policy.”, Transportation Research Part A: Policy and Practice, 37(2), pp. 183–186. Available at: 10.1016/s0965-8564(02)00037-x.

Phd Dissertation

Macroscopic modeling and analysis of urban vehicular traffic

Publication Date

January 1, 2014

Author(s)

Abstract

A macroscopic relation between the network-level average flow-rate and density, which is known as the macroscopic fundamental diagram (MFD), has been shown to exist in urban networks in stationary states. In the literature, however, most existing studies have considered the MFD as a phenomenon of urban networks, and few have tried to derive it analytically from signal settings, route choice behaviors, or demand patterns. Furthermore, it is still not clear about the definition or existence of stationary traffic states in urban networks and their stability properties. This dissertation research aims to fill this gap. I start to study the stationary traffic states in a signalized double-ring network. A kinematic wave approach is used to formulate the traffic dynamics, and periodic traffic patterns are found using simulations and defined as stationary states. Furthermore, traffic dynamics are aggregated at the link level using the link queue model, and a Poincare map approach is introduced to analytically define and solve possible stationary states. Further results show that a stationary state can be Lyapunov stable, asymptotically stable, or unstable. Moreover, MFDs are explicitly derived such that the network flow-rate is a function of the network density, signal settings, and route choice behaviors. Also the time for the network to be gridlocked is analytically derived. Even with the link queue model, traffic dynamics are still difficult to solve due to the discrete control at signalized junctions. Therefore, efforts are also devoted to deriving invariant continuous approximate models for a signalized road link and analyzing their properties under different capacity constraints, traffic conditions, traffic flow fundamental diagrams, signal settings, and traffic flow models. Analytical and simulation results show that the derived invariant continuous approximate model can fully capture the capacity constraints at the signalized junction and is a good approximation to the discrete signal control under different traffic conditions and traffic flow fundamental diagrams. Further analysis shows that non-invariant continuous approximate models cannot be used in the link transmission model since they can yield no solution to the traffic statics problem under certain traffic conditions. For a signalized grid network, simulations with the link queue model confirm that important insights obtained for double-ring networks indeed apply to more general networks.

Suggested Citation
Qijian Gan (2014) Macroscopic modeling and analysis of urban vehicular traffic. UC Irvine. Available at: https://escholarship.org/uc/item/9sh5m4h9 (Accessed: October 12, 2023).

published journal article

Load-following active power filter for a solid oxide fuel cell supported load

Journal of Power Sources

Publication Date

April 1, 2010

Author(s)

Allie E. Auld, Keyue M. Smedley, Fabian Mueller, Jack Brouwer, Scott Samuelsen
Suggested Citation
Allie E. Auld, Keyue M. Smedley, Fabian Mueller, Jack Brouwer and G. Scott Samuelsen (2010) “Load-following active power filter for a solid oxide fuel cell supported load”, Journal of Power Sources, 195(7), pp. 1905–1913. Available at: 10.1016/j.jpowsour.2009.10.005.

book/book chapter

Using social media to inform and engage urban dwellers in la paz, Mexico

Publication Date

January 1, 2020

Author(s)

Victoria Basolo, Anaid Yerena
Suggested Citation
Victoria Basolo and Anaid Yerena (2020) “Using social media to inform and engage urban dwellers in la paz, Mexico”, in Open government. IGI Global, pp. 1373–1391. Available at: https://doi.org/10.4018/978-1-5225-9860-2.ch064.

conference paper

Design and initial implementation of an inductive signature-based real-time traffic performance measurement system

2008 11th international IEEE conference on intelligent transportation systems

Suggested Citation
Andre Tok, Shin-Ting Jeng, Hang Liu and Stephen G. Ritchie (2008) “Design and initial implementation of an inductive signature-based real-time traffic performance measurement system”, in 2008 11th international IEEE conference on intelligent transportation systems. IEEE / IEEE, pp. 216–221. Available at: 10.1109/itsc.2008.4732703.

conference paper

QoE inference and improvement without end-host control

2018 IEEE/ACM symposium on edge computing (SEC)

Publication Date

October 1, 2018

Author(s)

Ashkan Nikravesh, Qi Alfred Chen, Scott Haseley, Xiao Zhu, Geoffrey Challen, Z. Morley Mao

Abstract

Network quality-of-service (QoS) does not always translate to user quality-of-experience (QoE). Consequently, knowledge of user QoE is desirable in several scenarios that have traditionally operated on QoS information. Examples include traffic management by ISPs and resource allocation by the operating system. But today these systems lack ways to measure user QoE. To help address problem, we propose offline generation of per-app models mapping app-independent QoS metrics to app-specific QoE metrics. This enables any entity that can observe an app’s network traffic-including ISPs and access points-to infer the app’s QoE. We describe how to generate such models for many diverse apps with significantly different QoE metrics. We generate models for common user interactions of 60 popular apps. We then demonstrate the utility of these models by implementing a QoE-aware traffic management framework and evaluate it on a WiFi access point. Our approach successfully improves QoE metrics that reflect user-perceived performance. First, we demonstrate that prioritizing traffic for latency-sensitive apps can improve responsiveness and video frame rate, by 46% and 115%, respectively. Second, we show that a novel QoE-aware bandwidth allocation scheme for bandwidth-intensive apps can improve average video bitrate for multiple users by up to 23%.

Suggested Citation
Ashkan Nikravesh, Qi Alfred Chen, Scott Haseley, Xiao Zhu, Geoffrey Challen and Z. Morley Mao (2018) “QoE inference and improvement without end-host control”, in 2018 IEEE/ACM symposium on edge computing (SEC). IEEE, pp. 43–57. Available at: 10.1109/sec.2018.00011.