research report

Detecting changes in accident rates using a hierarchical Bayesian approach: An application to the I-710 and the implementation of the PierPASS program

Publication Date

January 1, 2017
Suggested Citation
Ankoor Bhagat, Jean-Daniel Saphores and R Jayakrishnan (2017) Detecting changes in accident rates using a hierarchical Bayesian approach: An application to the I-710 and the implementation of the PierPASS program.

conference paper

Prediction of short-term freeway traffic volume using recursive least squares and lattice filtering

Applications of advanced technologies in transportation

Publication Date

January 1, 1998

Abstract

Estimating and predicting the dynamic variation of traffic variables such as volume and speed is becoming increasingly important for intelligent transportation systems applications. In this paper, we present a linear model for the short-term (30 second) prediction of freeway traffic volumes using a recursive least squares algorithm with a lattice filter. An innovative feature of the model is that all of the parameters, such as the optimal weights and the model order, are time-varying and are automatically updated in real-time so that unexpected traffic variations can be addressed by varying the parameters. Recursive filtering algorithms are applied in order to save computation time and storage space. The results of the performance analysis show that the proposed model works well under different conditions, including multiple locations and recurrent and non-recurrent congestion.

Suggested Citation
SM Kang, SG Ritchie and R Jayakrishnan (1998) “Prediction of short-term freeway traffic volume using recursive least squares and lattice filtering”, in . Hendrickson, CT and Ritchie, SG (ed.) Applications of advanced technologies in transportation. AMER SOC CIVIL ENGINEERS, pp. 255–264.

conference paper

CrowdWiFi. efficient crowdsensing of roadside WiFi networks

Proceedings of the 15th international middleware conference on - middleware '14

Publication Date

January 1, 2014

Author(s)

Di Wu, Qiang Liu, Yanyan Zhang, Julie McCann, Amelia Regan, Nalini Venkatasubramanian

Abstract

In this paper, we present CrowdWiFi, a novel vehicular middleware to identify and localize roadside WiFi APs that are located outside or inside buildings. Our work is motivated by the recent surge in availability of open WiFi access points (APs) that are enabling opportunistic data services to moving vehicles. Two key elements of CrowdWiFi that provide vehicles with opportunistic WiFi access include (a) an online compressive sensing component and (b) an offline crowd-sourcing module. Online compressive sensing (CS) techniques are primarily used to for the coarse-grained estimation of nearby APs along the driving route; here, the received signal strength (RSS) values are recorded at runtime, and the number and locations of APs are recovered immediately based on limited RSS readings. The offline crowdsourcing mechanism assigns the online CS tasks to crowd-vehicles and aggregates answers using a bipartite graphical model. This offline crowdsourcing executes at a crowd-server that iteratively infers the reliability of each crowd-vehicle from the aggregated sensing results and refines the estimation of APs using weighted centroid processing. Extensive simulation results and real testbed experiments confirm that CrowdWiFi can successfully reduce the number of measurements needed for AP recovery, while maintaining satisfactory counting and localization accuracy. In addition, the impact of CrowdWiFi middleware on WiFi handoff and data transmission applications is examined.

Suggested Citation
Di Wu, Qiang Liu, Yuan Zhang, Julie McCann, Amelia Regan and Nalini Venkatasubramanian (2014) “CrowdWiFi. efficient crowdsensing of roadside WiFi networks”, in Proceedings of the 15th international middleware conference on - middleware '14. ACM Press, pp. 229–240. Available at: 10.1145/2663165.2663329.

working paper

User Characteristics and Reponses to a Shared-Use Station Car Program: An Analysis of ZEV•NET in Orange County, CA

Publication Date

September 5, 2008

Author(s)

Abstract

Growing concerns about petroleum dependence, greenhouse gas emissions, and traffic congestion make shared-use vehicle programs look increasingly attractive. They offer an alternative to car ownership that yields benefits to their members by lowering the cost of transportation and to society at-large by reducing per capita VMT and increasing the use of public transportation. While neighborhood carsharing programs have already received a lot of attention, station car programs, the other type of shared-use vehicle program, largely have not. In the station car approach, shared vehicles are based at public transportation terminals to “extend” the public transportation network. This paper analyzes responses to a survey of the users of UC-Irvine’s ZEV•NET research program, which employs battery electric vehicles and is managed using information technologies. We find that ZEV•NET users participate in the program because they like the flexibility, the ease of use, and the reliability of ZEV•NET vehicles. ZEV•NET commuters are also more concerned about travel stress, cost, and environmental impacts than those who drive alone. By contrast, the latter place greater value in flexibility, reliability, and to a lesser degree, time. Moreover, the demographic characteristics of ZEV•NET users are not statistically different from those of non-users. As ZEV•NET users are not much more concerned about environmental issues than non-users, just advertising the environmental impacts of this program would not be sufficient to grow ZEV•NET; instead, potential cost advantages should be emphasized. These findings should be useful for designing more station car programs that rely on zero-emitting vehicles.

Suggested Citation
Matt G. Heling, Jean-Daniel Saphores and G. Scott Samuelsen (2008) User Characteristics and Reponses to a Shared-Use Station Car Program: An Analysis of ZEV•NET in Orange County, CA. Working Paper UCI-ITS-WP-08-1. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/8tw5f21p.

research report

A Systematic Evaluation Of The Impacts Of Real-traffic Condition Information On Traffic Flow

Abstract

The focus of this research effort is the study of driver behavior in the presence of real-time traffic condition information. The methodology adapted for this research involves three parts: development of a theoretical model for driver behavior under Advanced Traveler Information Systems (ATIS), interactive simulation experiments, data analysis and behavioral modeling. FASTCARS, an interactive computer-based simulator that has been developed for in-laboratory experimentation to gather data for estimating and calibrating predictive models of driver behavior under conditions of real-time information, is used in the project.

Suggested Citation
Jeffrey L. Adler, Wilfred W. Recker and Michael G. Mcnally (1993) A Systematic Evaluation Of The Impacts Of Real-traffic Condition Information On Traffic Flow. Final Report UCB-ITS-PRR-93-6. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/96c108s0.

working paper

Simultaneous Model of Household Activity Participation and Trip Chain Generation

Publication Date

March 1, 1999

Associated Project

Author(s)

Working Paper

UCI-ITS-WP-99-9, UCI-ITS-AS-WP-99-3

Areas of Expertise

Abstract

A trip generation model has been developed using a time-use perspective, in which trips are generated in conjunction with out-of-home activities, and time spent traveling is another component of overall time use. The model jointly forecasts three sets of endogenous variables – (1) activity participation and (2) travel time (together making up total out-of-home time use), and (3) trip generation — as a function of household characteristics and accessibility indices. It is estimated with data from the Portland, Oregon 1994 Activity and Travel Survey. Results show that the basic model, which has ten endogenous time use and trip generation variables and thirteen exogenous variables, fits well, and all postulated relationships are upheld. Test show that the basic model, which divides activities into work and nonwork, can be extended to a three-way breakdown of subsistence, discretionary and obligatory activities. The model can also capture the effects of in-home work on trip chaining and activity participation. We use the model to explore the effects on time use and trip chaining of GIS-based and zone-based accessibility indices.

Suggested Citation
Thomas F. Golob (1999) Simultaneous Model of Household Activity Participation and Trip Chain Generation. Working Paper UCI-ITS-WP-99-9, UCI-ITS-AS-WP-99-3. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/18n4h0ff.

research report

Experimental Studies of Traffic Incident Management with Pricing, Private Information, and Diverse Subjects

Abstract

39 subjects each controlled a simulated vehicle through a simple road network: one freeway, one alternate route with two traffic lights. All subjects traveled simultaneously (share the road) and in the same direction to their destination. Each participants started with $14.00 endowment that decreases at $0.15 per second until they reached their destination. Each subject began on the freeway, and were given one opportunity each round to switch to the alternate route. The simulation has a Changeable Message Sign (CMS) within 8 seconds before alternate route off-ramp is reached. The CMS varied based on the each scenario being tested. The sessions presented the subjects with information that used publicly or privately visible vehicle identifiers to target the diversion recommendation at specific individuals. Another session presented standard Caltrans CMS information, and one of the sessions presented a dynamically updated desired diversion rate. Detailed statistical analyses of all treatments were completed, including the estimation of models describing the learning processes and behavioral changes of subjects in response to CMS content and the outcomes of previous route choices.

Suggested Citation
David Brownstone, Michael McBride, AMINE MAHMASSANI and SI-YUAN KONG (2017) Experimental Studies of Traffic Incident Management with Pricing, Private Information, and Diverse Subjects. Research Report. ITS-Irvine. Available at: https://escholarship.org/uc/item/6kx670mv.

conference paper

Impact of VSL location on capacity drop: A case of sag and tunnel bottlenecks

INTERNATIONAL SYMPOSIUM OF TRANSPORT SIMULATION (ISTS'18) AND THE INTERNATIONAL WORKSHOP ON TRAFFIC DATA COLLECTION AND ITS STANDARDIZATION (IWTDCS'18) - EMERGING TRANSPORT TECHNOLOGIES FOR NEXT GENERATION MOBILITY

Publication Date

January 1, 2018

Abstract

When there is upstream congestion the discharging flow-rate of a tunnel or sag bottleneck can drop, which leads to additional traffic jams. Therefore, control strategies such as variable speed limit (VSL) have been developed aiming to prevent or mitigate upstream traffic congestion. Understanding traffic dynamics at bottlenecks, especially the mechanism of capacity drop, is critical for developing such models. Many studies are centered on the control algorithm design of VSL. However, there are few studies that systematically anayze the effect that the VSL application area has on the control effectiveness. This paper extends to sag and tunnel bottlenecks the theoretical framework to analytically solve the optimal location of the speed limit application area (first developed in Martinez and Jin (2018)). Moreover, we prove that the optimization formulation can be simplified. Consequently, it can be applied to further bounded acceleration models than the constant one. Finally, for an open-loop control with a constant speed limit for the Kobotonoke tunnel bottleneck, we validate the analytic definition of optimal location by preventing capacity drop in numerical simulations. (C) 2018 The Authors. Published by Elsevier Ltd.

Suggested Citation
Irene Martinez and Wen-Long Jin (2018) “Impact of VSL location on capacity drop: A case of sag and tunnel bottlenecks”, in . Yoshii, T and Shiomi, Y and Kusakabe, T and Wada, K (ed.) INTERNATIONAL SYMPOSIUM OF TRANSPORT SIMULATION (ISTS'18) AND THE INTERNATIONAL WORKSHOP ON TRAFFIC DATA COLLECTION AND ITS STANDARDIZATION (IWTDCS'18) - EMERGING TRANSPORT TECHNOLOGIES FOR NEXT GENERATION MOBILITY. ELSEVIER SCIENCE BV (Transportation research procedia), pp. 12–19. Available at: 10.1016/j.trpro.2018.11.008.

Phd Dissertation

An Analysis of Carsharing and Battery Electric Vehicles in the United States

Abstract

According to the California Air Resources Board (CARB, 2020), light-duty vehicles are responsible for 13 percent of statewide NOx emissions and 28 percent of statewide greenhouse gas emissions. Scientists, policymakers, and car manufacturers have been striving to reduce the air pollution and greenhouse gas emissions from the transportation sector using various measures, ranging from cleaner engines to alternatives to driving to reduce VMT. In this dissertation, I focus on a subset of these measures: carsharing programs and Battery Electric Vehicles (BEVs). In the first part of this dissertation, I explore the profile of households engaging in carsharing by estimating zero-inflated negative binomial (ZINB) models on data from the 2017 National Household Travel Survey (NHTS). My results show that households who are more likely to carshare are those who participate in other forms of sharing, have more Silent generation members, are less educated (the highest educational achievement is a high school degree), and have fewer vehicles than drivers. Conversely, households with more young adults (18 – 20 years old), with 2 or more adults and no children, take part in carsharing program less often. Moreover, households who took more part in ridesharing and have fewer vehicles than drivers are less likely to never carshare. Furthermore, households whose annual income between $75,000 and $150,000 are more likely to never carshare. In the second part of this dissertation, I concentrate on the adoption of BEVs. More specifically, I focus on two questions: 1) What are the characteristics of households who own battery electric vehicles (BEVs)?; and 2) Does the travel behavior of these households differ from the travel of households who have motor vehicles but not BEVs? To answer those questions, I characterize three groups of households based on their vehicle holdings: BEV-only, BEV+ (i.e., households with both one or more BEV and at least one conventional vehicle), and non-BEV households. I analyze data from the 2017 NHTS using mixed methods. Results show that BEV households are more likely to be Asian, well-educated, with a higher income and to live in higher population and employment density areas. Furthermore, BEV-only households are more likely to be composed of one adult (not retired) with fewer Baby Boomers. Yet, BEV+ households are more likely to be larger households with 2 or more adults. Also, BEV+ households are more likely to have more Generation X (37-52 years old in 2017) and Z members (20 years old or younger in 2017). They are also more likely to own their home. My analysis on gender (at the individual level) concluded that BEV owners are more likely to be men. Furthermore, I find that BEV households travel as much as non-BEV households. Although carsharing and BEVs could substantially decrease the environmental footprint of transportation, they are currently far from mainstream. To promote carsharing programs, their reach could be extended, they could be made more affordable, while increasing the cost of owning and operating private vehicles. Similarly, state and federal governments could continue to provide financial incentives to lower the purchase price difference between conventional and BE vehicles, manufacturers could provide extended warranties on batteries, and the charging infrastructure needs to be developed in order to attract more customers. The Covid-19 crisis is giving governments around the world an opportunity to invest in clean technologies to jumpstart the economy. It is critical to take advantage of this crisis to reduce air pollution and greenhouse gas emissions from transportation for the good of current and future generations.

Suggested Citation
Yunwen Feng (2021) An Analysis of Carsharing and Battery Electric Vehicles in the United States. Ph.D.. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_2555985409 (Accessed: October 12, 2023).