2020

Fariba Siddiq, University of California, Los Angeles
Amanda Dillon, University of Utah
Reid Ewing, University of Utah

As many cities continue to grow, they face housing shortages, witness increased automobile congestion, and subsequent air pollution. Promoting transit-oriented development and multifamily housing is one way municipalities are combating these challenges. As this kind of development has expanded, so has the research investigating the link between real estate values and transit proximity. However, the results of those inquires have been mixed and no general conclusion has been drawn about the effect size and impact areas of transit station on multifamily property values. This research aims to fill a gap in literature by conducting a meta-analysis of transit premiums for multifamily housing. The results indicate that rail transit stations had a bigger effect on multifamily property values (up to 3200 meter) than bus rapid transit (BRT) stations (up to 1500 meter). The average transit premium for multifamily properties can be up to 15% when it is within 200 to 300 meter of rail transit stations. For BRT and light rail, the premiums are lower initially in the distance bands closest to the stations and then increase in the successive distance bands. This may be because of the nuisance of being close to stations, which is offset by accessibility benefits in proximity of stations. On the contrary, for heavy rail, the premium decreases linearly with distance from stations because the nuisance effect is smaller compared to the accessibility benefit. The findings can help local governments consider how and where they may get the highest economic yields on investments near transit stations.

Christian Sprague, Cornell University
H. Gao, Cornell University

Integrating land use and transportation policy is widely understood as an efficient approach to meet sustainable transport objectives, yet impacts on residential location preference may limit policy effectiveness. Incorporating the effects on residential location preference is especially important for aligning policy decisions with policy goals. Using travel survey data, matched to block group characteristics, this study uncovers an important constraint: an integrated consumer-driven policy mix can influence households to either a more compact and accessible city or a more sprawled, revenue-generating city. We further estimate the effect of policy decisions on household exposure to road-traffic fatality and noise pollution, greenspace accessibility, and walkability and find significant differences in outcomes depending on the policy decision.

Shishir Mathur, San Jose State University

This study estimates households’ willingness to pay for single-family houses and condominiums/townhouses located within 2 miles of Warm Springs (WS) BART Station in Fremont, CA. The study finds that, compared to the houses sold in the control distance band (2 to 5 miles away), an average-priced single-family house within two miles of the WS BART Station was higher in price by 9% to 15%. The total property value increment for the single-family houses is large enough to fund the $802 million Warm Springs BART Extension Project cost five times over.

Baichuan Mo, Massachusetts Institute of Technology (MIT)
Qingyi Wang, Massachusetts Institute of Technology (MIT)
Yu Shen, Tongji University
Jinhua Zhao, Massachusetts Institute of Technology (MIT)

With the quick advance of autonomous vehicle (AV) technology, understanding the potential demand of AV and its user characteristics has increasingly become a popular area of research. In consumer choice and technology adoption literature, whenever the demand of a new product is forecasted, the attitudes towards existing choices are found important in addition to new product attributes and consumer characteristics. While there is an abundance of literature from stated preference (SP) surveys identifying attitudes are just as important as demographics in forming a purchase or usage decision of AVs, past studies have seldom looked at how attitudes towards existing travel modes affect the new mode adoption. We conduct a dynamic online SP survey in Singapore on 2,003 individuals, with indicator questions about impressions on existing modes. We focus on how these attitudes affect AV adoption based on confirmatory factor analysis and discrete choice models with latent variables. The results show that having positive attitudes towards public transit casts a negative effect on AV adoption, while having positive attitudes towards ridesharing is positive on AV adoption. And, positive attitudes towards walking and driving do not have any significant effects. In addition, the model identifies that highly educated, wealthy, and/or younger people as the population to have more positive attitudes towards new technologies and more likely to adopt AVs. The research provides insights on potential relationship between AVs and existing modes, as well as the characteristics of potential audience, which may be of help in planning future AV services.

Jaehyung Lee, Yonsei University
Euntak Lee, Yonsei University
Jaewoong Yun, Yonsei University
Jin-Hyuk Chung, Yonsei University
Jinhee Kim, Yonsei University

Autonomous driving technologies (ADTs) are expected to relieve the burden of driving and thus transform travel behavior. Since travel distance is closely related to the burden on driving, it is expected to affect preference of ADTs. However, the effects of travel distance on people’s preference for ADTs have been largely ignored in the transportation literature. Therefore, the present study is designed to investigate preference of ADT and its variation by travel distance. In particular, the study aims to estimate the value of travel time savings (VTTS) during autonomous driving and the nonlinearity in the VTTS reduction by increasing travel distance. Hypothetical choice situations were designed to investigate people’s preference for ADT compared with human driving with varying travel distance. Four sets of choice profile per distance were given to respondents, and each choice profile consists of four hypothetical choice situations with different travel time and cost. The experiments were designed using Bayesian D-efficient method for each choice profile per distance. Using the stated preference data collected via the experiment, a mixed logit model was estimated to account for random taste variation with respect to travel time and panel effect over multiple hypothetical choice situations and multiple choice profiles with varying travel distance. The results show that ADT is a more attractive mode in long-distance trip than short-distance trip, and that the VTTS for using ADT tends to be nonlinearly decreased. In addition, the effects of socio-demographics on the preference for ADT tend to vary with increasing travel distance.

Lu Ling, Purdue University
Xinwu Qian, University of Alabama, Tuscaloosa
Satish Ukkusuri, Purdue University

The rapid growth of Transportation Network Companies (TNCs) substantially affects the traditional taxi industry, resulting in significant losses in market share,  ridership,  labor supply,  and asset values of the traditional taxi industry. This study aims to examine the impact of TNCs on the labor supply of yellow taxi market. We adopt the wage decomposition method by partial least squares to quantify how taxi drivers' labor supply behavior is affected by the rise of TNCs over time. The taxi GPS trajectory data and TNCs trip record from 2013 to 2018 in New York City (NYC) are further introduced to gain insights from real-world scenarios. Based on the analyses of market-level and individual-level yellow taxi driver's performance, we find that the market-level labor supply decreases with 1% more TNCs trips resulting in 0.0123% yellow taxi drivers quit from the market. Besides, individual-level revenue has been affected with 1% more TNCs trips resulting in 0.0044% reduction of yellow taxi monthly income. The insights imply that even the individual-level labor supply is barely affected, the yellow taxi drivers' work motivations decrease by shifting their work behavior from widely accepted neoclassical standard (NS) behavior to reference-dependent preference (RDP), which provide potential contributions to reconsider the taxi industry regulations and policy.

Muhammad Tahmidul Haq, University of Wyoming
Milan Zlatkovic, University of Wyoming
Khaled Ksaibati, University of Wyoming

Wyoming is encountering an extensive increase in truck movement along Interstate 80 (I-80). The increased interactions between trucks and other vehicles have raised many operational and safety concerns. This paper presents an operational analysis of freeway climbing lanes under heavy truck traffic, which extends to a benefit-cost analysis from both operational and safety perspective. Seven corridors with proposed new climbing lanes along I-80 were analyzed, and performance measures associated with these segments were collected to evaluate the operational and safety effectiveness. To understand the efficiency of climbing lanes, a benefit-cost analysis (BCA) was conducted based on the guideline provided by the U.S. Department of Transportation (USDOT). It was found that the installation of climbing lanes has the potential to improve operational performances for a 20-year planning horizon. The results from the BCA indicated that 20-year aggregated benefits significantly outperformed the corresponding project costs. Among the investigated segments, the most cost-effective new climbing lane location was found WB (MP 20.38 – 19.88) with a benefit-cost ratio (BCR) of 10.9 and 11.1 for 46% and 70% truck proportion respectively. Based on the results of simulation analyses, recommendations can be made to enhance truck operations. Findings from this study are expected to help WYDOT managers and policymakers to take necessary actions and decide on management strategies.

Yang Jiang, China Sustainable Transportation Center
Peiqin Gu, Beijing CityDNA Technology Co., Ltd.
Jie Qi, Beijing CityDNA Technology Co., Ltd.
Zhejing Cao, Tsinghua University
Yulin Chen, Tsinghua University

Few previous studies have linked transit-oriented development (TOD) patterns and property values at the station level in the Chinese context. Using Shanghai as a case study , we obtained 21,094 transaction records within the 800 m radius catchment areas of 280 urban rail stations from a local property agency. A performance-based TOD indicator framework was established to capture built environment features in terms of density, diversity and design dimensions. Using open-source geospatial data, we generated a series of TOD indicators for each station catchment area and further developed a composite TOD index with information entropy weighting. The results of multilevel regression models showed that within urban rail station catchment areas, residential properties with higher TOD levels were positively associated with higher value. Increasing pedestrian and bike accessibility and integrating diversified urban functions around stations could create more value for nearby residential properties.

Athena Roumboutsos, University of the Aegean
Danai Bolorizou, University of the Aegean

The introduction of new rail-based transportation systems in metropolitan urban areas is considered important by planners wishing to provide sustainable transit options despite the lack in public funds.  In this context, the present study addresses three research questions in the Athens-Piraeus Metropolitan Area: (i) Is there land value uplift in metropolitan areas due to urban rail transit?(ii) Do Tram or Metro stop/stations have a greater impact on land value uplift?(iii) Can this land value be captured or is there too much variability limiting the possibility of capture measures requiring standardisation (e.g. forms of taxation)? A hedonic model based on differences of differences is built in response. Despite existing transit options, properties near tram and metro stop/stations enjoy higher real estate values. The Tram could be more attractive. However, considerable variability undermines findings. Given this remark, larger samples are needed, while the need to normalize and, therefore, compare studies is hampered by the variability of locations and availability of data. Land value capture becomes limited with ad hoc applications which cannot be transferred and repeated.

Dimitrios Kourtesis, Ideas Forward SA
Michail Makridis, IVT ETHZ
Stefanos Tsiakmakis, Ideas Forward SA
Nikolaos Tsoniotis, Florence University
Georgios Fontaras, European Commission

This paper focuses on the potential of transport assets sharing, a field where decentralization can enable new solutions and market potential. Distributed ledger (also refered to as blockchain) technology can significantly contribute in this direction. The goal of this work is to investigate the applicability of blockchain in the creation of future technology platforms which enable improved peer-to-peer (P2P) car-sharing between car rental operators and, more importantly, to provide a preliminary evaluation of the market potential of such solutions by looking at the challenges and priorities of businesses in this sector. The results suggest that P2P car-sharing seems to be a well-established practice among businesses that operate small and medium-sized car rental fleets in Greece and Italy and potentially in other EU countries. The findings from this study reinforce the view that decentralized car-sharing business models and application solutions in the car rental space must address three key requirements: (i) trust building, (ii) coordination support, and (iii) interoperable information exchange.

Fabiene Cristina de Carvalho da Costa, Federal University of Rio de Janeiro
Carlos Nassi, Universidade Federal do Rio de Janeiro

Urban mobility is achieved through transport policies aimed to improve the movement of people in an urban space, through the prioritization of collective and non-motorized modes of transport in an effective, socially inclusive and ecologically sustainable way. Trying to analyze one of the main factors that influence urban mobility in an area, this paper aims to elaborate a methodology to obtain personal expenses with urban transportation in a given area, to apply it in a study area belonging to the State of Rio de Janeiro, Brazil. The result obtained is that 12.15% of the average monthly income of the individual is spent with urban transport, considering those that present non-zero displacements and the value of 7.74% for the entire Rio de Janeiro Metropolitan Region (RMRJ) population. From the determination of the average individual expenditure with urban transportation in the area where the procedure is applied, it is expected to change and encourage new urban planning policies, interconnecting the territory planning areas (with more decentralized definitions of workplaces) and the existing and future transport infrastructure contributing to improve the population life quality.

Rami Chkaiban, University of Nevada, Reno
Elie Hajj, University of Nevada, Reno
Muluneh Sime, Nevada Automotive Test Center
Gary Bailey, Nevada Automotive Test Center
Peter Sebaaly, University of Nevada, Reno

This paper describes an approach for the development of prediction models for the estimation of mileage-related vehicle depreciation that can be used in the estimation of the benefits derived from transportation network improvements. The approach takes advantage of published online data for vehicle valuations. A new asymmetric logistic prediction model for total vehicle depreciation, including initial and mileage-related depreciations, is proposed and fitted to collected valuations data. The added benefit of this prediction model is that it takes into consideration both, vehicle age (i.e., years since manufacturing) and vehicle usage (i.e., miles of travel). Six small light duty vehicles (SLDVs), five large light duty vehicles (LLDVs), three two-axle trucks, one single-unit truck, and two combination trucks were considered in this study. Vehicle fuel sources included gasoline, diesel, gasoline-ethanol blend of up to 85% ethanol (E85), and hybrid-electric (HE); resulting in 26 combinations of vehicle type and fuel source. Additionally, the developed models were adjusted to account for vehicle average speed and roadway characteristics (e.g., grade, curvature) effects on vehicle depreciation. The practicality of the developed models for large SUV and midsize car was illustrated using select examples highlighting the models’ sensitivity to vehicle average speed and roadway characteristics.

Ioannis Tsapakis, Texas A&M Transportation Institute
Sushant Sharma, Texas A&M Transportation Institute
William Holik, Texas A&M Transportation Institute

The Highway Safety Improvement Program (HSIP) aims to reduce the number and severity of fatalities and serious injury crashes by implementing safety improvement projects. The Traffic Operations Division (TRF) of the Texas Department of Transportation (TxDOT) currently administers TxDOT’s HSIP. TRF requests HSIP projects from TxDOT districts every year. All proposed projects are subjected to a benefit-cost ratio (BCR), called Safety Improvement Index (SII). After projects are submitted to the program, the TRF prioritizes them based on the SII. Although the structure and main components of TxDOT’s HSIP comply with relevant requirements, a review of modern safety assessment methods and tools revealed that there are several areas for improvement, including economic analysis and prioritization of HSIP projects. The objectives of this study are to a) compare TxDOT’s BCR-based project prioritization approach against an improved incremental benefit-cost ratio (IBCR) method, recommended by the Highway Safety Manual (HSM), and b) minimize the amount of time and resources required to prioritize HSIP projects. To address the first objective, the researchers applied both methods using data from the 2016 TxDOT HSIP and compared the results. The comparison showed that the projects selected using the IBCR method were more cost-effective than the projects funded by the BCR method. Further, the IBCR method awarded high-cost projects where more crashes had been observed. To address the second objective, the authors developed a prioritization tool that automatically ranks candidate projects using the IBCR method. The average runtime to prioritize 1,000 projects is less than 0.5 seconds.

Amin Mohamadi Hezaveh, North Carolina Department of Transportation
Christopher Cherry, University of Tennessee, Knoxville

The current practice of road safety economic assessment attributes traffic crash costs to the location of traffic crashes. Therefore, it is challenging to estimate the economic cost of traffic crashes of individuals who live in a specific geographic area. To address this limitation, we used home-address of individuals who were involved in traffic crashes in East Tennessee between 2015-16. After geocoding the home-addresses, we assigned 110,312 individuals to the Traffic Analysis Zone (TAZ) corresponding to their home address and calculated the economic cost of traffic crashes per capita (ECCPC). The average ECCPC in the study area was $1,399. The Knoxville regional Travel demand model output was used for extracting travel behavior data elements for modeling ECCPC at zonal level. We also established an index to measure exposure individuals’ activity in the transportation system –i.e., average zonal activity– for residents of each TAZ. Analysis indicates that the burden of traffic crashes (ECCPC per income) was more tangible in the TAZs with lower income and higher zonal activities. The spatial autoregressive (SAR) model was more suitable compared to spatial error model and ordinary least squares regression. SAR model implies that ECCPC in one TAZ is affected by traffic safety of the adjacent TAZs. Findings indicate that average zonal activity and traffic exposure have a significant positive association with ECCPC. The ECCPC could be used as an index for allocating proper countermeasures and interventions to groups and areas where the burden of traffic crashes is more tangible.

Junfang Li, Shanghai University
Jie Yu, University of Wisconsin, Milwaukee
Hua Hu, Shanghai University
Zhi-gang LIU, Shanghai University

There already exist a few rail transit lines linking the new towns to the center business district (LTC) in megacities. However, few of lines among the new towns (LTT) exist. The paper examines the feasibility of capturing land value uplift to augment or provide funding for new LTT, with LTC as the benchmark. Evaluate the value uplift in catchment and control area over time. Then when and how much LTT raise the land value is analyzed by difference-in-difference model (DID). Case study of Tokyo shows LTT could add to the land value, however, lower than LTC. DID estimators show firstly , the implementation phases, time-saving do result in a substantial land value uplift; Secondly , the implicit land value of LTT is all lower than LTC except that related to time-saving to CBD in the announcement period, implying LTT are expected extremely to link to CBD in the announcement period;  Thirdly , the implicit land value goes down over time at a higher degree for LTT than LTC, implying the impact of LTT on land value uplift is less sustainable than that of LTC; Fourthly , sustainability of the implicit land value as to time-saving to the capital of the new town is more than that to CBD for LTT. For LTC, it is reversed. Lastly , the implicit value in the announcement period presents significantly distance-decay performance for both lines. These results provide an evidence base for policy-maker to quantify the potential to raise financial funding for LTT.

Richard Driscoll, Cambridge Systematics
Kurt Lehmann, Cambridge Systematics

Since Transportation Network Companies (TNCs) entered the market around 2010, their impact on vehicle miles of travel has been difficult to quantify. TNCs greatly expanded the role of ride hailing services in mobility, and continue to be a topic of interest in various transportation industries. The purpose of this paper is to utilize the National Household Travel Survey, containing expanded data on ride-hailing services, in order to explore the impact of TNCs on VMT as defined by the NHTS. The analysis utilizes a survey detailing TNC mode substitution for 7 major metropolitan areas in the U.S. to determine the magnitude of TNC use and its effect on the transportation market.. The mode substitution profile paired with usage estimates were used to compare real measured VMT levels with a hypothetical VMT in the absence of TNCs.

Edem Dzakwasi, Economic Decisions Group, Inc

Baloka Belezamo, Arizona Department of Transportation

Amirhossein Baghestani, City College of New York
Mahdieh Allahviranloo, City College of New York
Carla Tejada, City College of New York

Ishant Sharma, University of Memphis
Sabya Mishra, University of Memphis
Mihalis Golias, University of Memphis

Roozbeh Rahmani, University of Florida

Rydell Walthall, University of Texas, Austin

Sania E. Seilabi, Purdue University

Anup Tapase, Metropolitan Transportation Commission (MTC)