JTLU Volume 13, No. 1 (2020)

Persistent link for this collection

https://hdl.handle.net/11299/213961

Note: Starting in 2017, the Journal of Transport and Land Use will release articles as they are published. They will no longer be published in three separate issues.

Table of Contents:

How is public transit in the megacity peripheral relocatees' area in China? Captive transit rider and dynamic modal accessibility gap analytics in a peripheral large-scale residential area in Shanghai, China, pp. 1-21

Vehicle miles traveled and the built environment: New evidence from panel data, pp. 23-48

A new method using medians to calibrate single-parameter spatial interaction models, pp. 49-70

Does urban form influence automobile trip frequency in Accra, Ghana?, pp. 71-92

Testing microsimulation uncertainty of the parcel-based space development module of the Baltimore PECAS Demo Model, pp. 93-112

Residential accessibility's relationships with crash rates per capita, pp. 113-128

Towards a general theory of access, pp. 129-158

Commuting inequality, role of urban structure, and identification of disadvantaged groups in the Mexico City metropolitan area, pp. 159-183

Anticipating land-use impacts of self-driving vehicles in the Austin, Texas, region, pp. 185-205

Where and why do firms choose to move? Empirical evidence from Norway, pp. 207-225

Integrated land use and transportation modelling and planning: A South African journey, pp. 227-254

Affecting commute mode choice in Southern California: Which employer-based strategies work?, pp. 255-272

Identifying the combined effect of shared autonomous vehicles and congestion pricing on regional job accessibility, pp. 273-297

Impact of land use on bicycle usage: A big data-based spatial approach to inform transport planning, pp. 299-316

Multilevel spatial impact analysis of high-speed rail and station placement: A short-term empirical study of the Taiwan HSR, pp. 317-341

Do people walk more in transit-accessible places? pp. 343-365

The influence of urban form and socio-demographics on active transport: A 40-neighborhoods study in Chengdu, China, pp. 367-388

Analysis of the effect of multi-level urban form on bikeshare demand: Evidence from seven large metropolitan areas in the United States, pp. 389-408

Introduction to special issue: Innovations for transport planning in China, pp. 409-412 (Special Issue)

Sunsetting skim matrices: A trajectory-mining approach to derive travel time skim matrix in dynamic traffic assignment for activity-base model integration, pp. 413-428 (Special Issue)

Trip mode inference from mobile phone signaling data using Logarithm Gaussian Mixture Model, pp. 429-445 (Special Issue)

Exploring multi-scale spatial relationship between built environment and public bicycle ridership: A case study in Nanjing, pp. 447-467 (Special Issue)

The impact of street characteristics on older pedestrians’ perceived safety in Shanghai, China, pp. 469-490 (Special Issue)

Dockless bike-sharing system: Solving the problem of faulty bikes with simultaneous rebalancing operation, pp. 491-515 (Special Issue)

Real-time urban regional route planning model for connected vehicles based on V2X communication, pp. 517-538 (Special Issue)

A multiple-path gradient projection method for solving the logit-based stochastic user equilibrium model, pp. 539-558 (Special Issue)

Dynamic interactions between spatial change and travel behavior variation in old town fringe, pp. 559-584 (Special Issue)

Fear follows form: A study of the relationship between neighborhood type, income and fear of crime at train stations, pp. 585-603

Social-cultural impacts of China-Pakistan Economic Corridor on the well-being of local community, pp. 605-624

How does the built environment affect transit use by train, tram and bus?, pp. 625-650

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Measuring road space consumption by transport modes: Toward a standard spatial efficiency assessment method and an application to the development scenarios of Rajkot City, India
(Journal of Transport and Land Use, 2020) Will, Marie-Eve; Cornet, Yannick; Munshi, Talat
The space "consumed" by various urban passenger transport modes varies greatly depending on the size and the speed of vehicles. Past studies have shown that public transport (PT) and non-motorized transport (NMT) can be up to 20 times more space-efficient compared to a typical car. This optimal use of space is of relevance in an urban context where space is often a constrained resource. Yet space used by vehicles is rarely assessed in the practice of transport planning. There exists no standard method for quantifying the use of space in complex urban settings. This study proposes an approach based on the space-time concept for quantifying and comparing the dynamic (on-road) and still (parking) space used by different transport modes for a specific road network. Transport planning scenarios developed in the Low-carbon Comprehensive Mobility Plan (LCMP) prepared for the city of Rajkot are used to demonstrate the method. The indicators show that significantly less space is used by transport in a scenario that promotes higher use of PT and NMT in comparison to a business-as-usual scenario based on traffic projections for private motorized vehicles. These results provide evidence that could contribute to alleviating chronic congestion expected from car- and motorcycle-based transport development only. Overall, this research describes an assessment framework for low-carbon transport development that would include spatial efficiency concerns.
Dynamic interactions between spatial change and travel behavior variation in old town fringe
(Journal of Transport and Land Use, 2020) Zhou, Wenzhu; Li, Qiao; Li, Zhibin; Wang, Nan; Wang, Qi
Old town fringe area is changing in its spatial features, and these changes correspondingly result in variations in travel behaviors. Taking the spatial characteristics and travel behavior data of the Nanjing Old Town Fringe (OTF) area in 2010 and 2015 as an example, we conducted a comparative study for two years. First, based on the identification of the spatial range of OTF in these two years by using travel data mutation points and the Point of Information (POI) kernel analysis method, the significant change in the OTF area, from marginal areas in 2010 to non-marginal areas in 2015, was identified. Second, multiple logit models were used to evaluate the impact of the built environment and economic and social attributes of residents on the choice of travel modes, as well as the different impact factors. From the perspective of overall performance, with reference to the behavior of choosing motor vehicle travel, from 2010 to 2015, the significant correlation of factors in promoting residents to choose walking, cycling or public transit changed. Moreover, there were three different dynamic characteristics of this correlation change: (1) the correlation of factors was significant and stable from 2010 to 2015; (2) the correlation of factors was significant in 2010 but not significant in 2015; (3) the correlation of factors was not significant in 2010 but was significant in 2015. It was found that the correlated factors of fluctuation were mainly social attribute factors, for example, education, gender, age, whether having a driver’s license, etc. Therefore, in future research and practice, we need to focus on the impact of stable correlated factors (such as shortest distance to downtown, plot ratio, occupation, etc.) and factors with increasing correlations (such as bus coverage, gender, age, etc.). And the land-mix factor needs to be considered from both vertical and horizontal perspectives. This will have certain significance and help future development of OTF areas.
A multiple-path gradient projection method for solving the logit-based stochastic user equilibrium model
(Journal of Transport and Land Use, 2020) Tan, Heqing; Du, Muqing; Yu, Chun-bin
This paper proposes a path-based algorithm for solving the well-known logit-based stochastic user equilibrium (SUE) problem in transportation planning and management. Based on the gradient projection (GP) method, the new algorithm incorporates a novel multiple-path gradient approach to generate the descent direction in consideration of many paths existing in every single origin-destination (O-D) pair. To apply the path-based algorithm, the SUE problem is reformulated as a variational inequality (VI), and a working path set is predetermined. The numerical experiments are conducted on the Winnipeg network where a large number of paths are provided. The results show the multiple-path gradient projection algorithm outperforms the original GP method. Three different step size strategies, including the fixed step size, self-regulated averaging and self-adaptive Armijo’s strategies, are involved to draw a more general conclusion. Also, the effects of the path number on computational performance are analyzed. The multiple-path gradient projection (MGP) method converges much faster than the GP method when the path set size gets large.
Real-time urban regional route planning model for connected vehicles based on V2X communication
(Journal of Transport and Land Use, 2020) Wang, Pangwei; Deng, Hui; Zhang, Juan; Zhang, Mingfang
Advancement in the novel technology of connected vehicles has presented opportunities and challenges for smart urban transport and land use. To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper. First, considering the traffic signal timing and phase information collected by V2X, road section resistance values are calculated dynamically based on real-time vehicular driving data. Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. Finally, we design the test scenario with different traffic saturation levels and collect 150 sets of data to analyze the feasibility of the proposed method. The numerical results have shown that the average travel times calculated by the proposed optimal route are 8.97 seconds, 12.54 seconds, and 21.85 seconds, which are much shorter than the results of traditional navigation routes. This proposed model can be further applied to the whole urban traffic network and contribute to a greater transport and land-use efficiency in the future.
Dockless bike-sharing system: Solving the problem of faulty bikes with simultaneous rebalancing operation
(Journal of Transport and Land Use, 2020) Usama, Muhammad; Zahoor, Onaira; Shen, Yongjun; Bao, Qiong
The Free-Floating Bike-Sharing System (FFBS) enables commuters to pick up and drop off a shared bike without going to a docking station before and after the trip. However, the specific sharing features of the FFBS can also be a problem for users because randomly scattered and faulty bikes within the system can result in bike unavailability and maintenance difficulties. This not only negatively impacts the company’s service quality but also causes user safety issues. In this study, a mechanism for the rebalancing of useable bikes and faulty bikes is presented in two steps: 1) gathering each faulty bike at a station determined by the model traversing the shortest path by light service vehicles; and 2) enabling the rebalancing operation to obtain optimal bike inventory levels at all stations and collect faulty bikes at a depot. The destination station from which each faulty bike is taken is considered a decision variable rather than shifting them to a closer station. The mechanism is based on minimizing the total cost of the rebalancing operation by optimizing the formulated problem, supported by time and capacity constraints. Using CPLEX solver, the validity of the model is tested through different numerical experiments.
The impact of street characteristics on older pedestrians’ perceived safety in Shanghai, China
(Journal of Transport and Land Use, 2020) Wu, Hao; Zhang, Zhaoxi; Chen, Yong; Jiao, Junfeng
Land-use patterns and rapid urban sprawl greatly influence older adults’ mobility in China. Older pedestrians’ safety issues are crucial because these people are more frequently injured in traffic accidents. This research aims to investigate what street characteristics influence perceived safety among older pedestrians in Shanghai, China. A mix of research methods containing both quantitative and qualitative analyses were employed. The researchers recruited 68 elderly urban dwellers who each agreed to take a perceived safety survey using 39 simulated streetscape images that contained 12 street characteristics extracted from four sectional zones of streets. Ordinal logit regression was performed to investigate the impact of street characteristics on older pedestrians’ perceived safety. A semi-structured, in-depth interview was conducted with 8 out of the 68 participants. It was found that the street interface type, elevation differences, footpath width, paver directions, isolation facility type, and vehicle traffic all affected pedestrians’ perceived safety after adjusting for individual demographic attributes and the physical limitations of the participants. Understanding the street characteristics related to perceived safety will contribute to making more inclusive and walkable cities.
Exploring multi-scale spatial relationship between built environment and public bicycle ridership: A case study in Nanjing
(Journal of Transport and Land Use, 2020) Lyu, Cheng; Wu, Xinhua; Liu, Yang; Yang, Xun; Liu, Zhiyuan
A public bicycle system (PBS) is a promising countermeasure for the traffic issues induced by rapid urbanization, and it is widely acknowledged that the built environment has a significant impact on the use of a PBS. However, as the urban built-up area expands, different regions within a city can exhibit diverse characteristics. The spatial effects and differences among regions have been neglected by existing studies. To better understand how the urban built environment affects PBS ridership, this study conducts a quantitative analysis of the spatial relationship. It introduces a multi-scale geographically weighted regression (MGWR) to accomplish this task and conducts and evaluates a case study of the PBS in Nanjing, China. Six types of “D” variables (density, diversity, design, destination accessibility, distance to transit, and demand management) are involved in the analysis. The proposed method outperforms linear regression and standard geographically weighted regression (GWR) in terms of explanatory power. The modeling results demonstrate different influencing patterns between traditional downtown areas and newly built-up areas, especially for the density of population, road network, parking space, and various points of interest.
Trip mode inference from mobile phone signaling data using Logarithm Gaussian Mixture Model
(Journal of Transport and Land Use, 2020) Chen, Xiaoxu; Yang, Chao; Xu, Xiangdong
Trip mode inference plays an important role in transportation planning and management. Most studies in the field have focused on the methods based on GPS data collected from mobile devices. While these methods can achieve relatively high accuracy, they also have drawbacks in data quantity, coverage, and computational complexity. This paper develops a trip mode inference method based on mobile phone signaling data. The method mainly consists of three parts: activity-nodes recognition, travel-time computation, and clustering using the Logarithm Gaussian Mixed Model. Moreover, we compare two other methods (i.e., Gaussian Mixed Model and K-Means) with the Logarithm Gaussian Mixed Model. We conduct experiments using real mobile phone signaling data in Shanghai and the results show that the proposed method can obtain acceptable accuracy overall. This study provides an important opportunity to infer trip mode from the aspect of probability using mobile phone signaling data.
Sunsetting skim matrices: A trajectory-mining approach to derive travel time skim matrix in dynamic traffic assignment for activity-base model integration
(Journal of Transport and Land Use, 2020) Tian, Ye; Chiu, Yi-Chang; Sun, Jian; Chai, Chen
The travel impedance skim matrix is one of the most essential intermediate products within transportation forecasting models and is a fundamental input for activity-based transportation forecasting models. It reflects interzonal travel time, travel time reliability, travel costs, etc. by time of day. The traditional method to obtain skim matrices is to execute multiple times of time-dependent, shortest-path calculations. However, the computational and memory use burden can easily increase to an intractable level when dealing with mega-scale networks, such as those with thousands of traffic-analysis zones. This research proposes two new approaches to extract the interzonal travel impedance information from the already existing vehicle trajectory data. Vehicle trajectories store travel impedance information in a more compact format when compared to time-dependent link performance profiles. The numerical experiments highlight huge potential advantages of the proposed approaches in terms of saving both memory and CPU time.
Introduction to special issue: Innovations for transport planning in China
(Journal of Transport and Land Use, 2020) Li, Zhibin; Jiao, Junfeng; Ding, Chuan
We planned this special issue in response to the new opportunities and innovations for urban transport planning in China all of which can help build the smart transportation systems of the future. In preparation for the special issue, we organized the 19th COTA International Conference of Transportation Professionals (CICTP2019) with the theme of “Transportation in China 2025” in July 2017 and recommended high-quality submissions to this special issue. In the end, we received a total of 24 valid papers. After the standard peer-review process, we accepted eight papers for the special issue, with three focusing on built environment and travel activity, three focusing on road network distribution, and two focusing on data-driven traffic modeling. The special issue also has a well-balanced research focus on different types of transport modes, with two papers on multi-modal transport, three on personal cars, two on public bikes, and one on pedestrians.
How does the built environment affect transit use by train, tram and bus?
(Journal of Transport and Land Use, 2020) De Gruyter, Chris; Saghapour, Tayebeh; Ma, Liang; Dodson, Jago
While much research has explored the influence of the built environment on public transport use, little focus has been given to how this influence varies by public transport mode. Using a case study of Melbourne, this study assesses the influence of the built environment and other characteristics (transit service quality, demand management and socio-demographics) on commuting by train, tram and bus. Key findings indicate that the built environment has a significant influence, but with notable differences between individual public transport modes. Commuting by tram was found to have the strongest association with the explanatory variables, while bus had the weakest explanatory power. Differences in the geographical coverage of public transport services in Melbourne play a key role in explaining the influence of the built environment. Population density is positively associated with tram use, which operates in older, higher density environments, but is negatively associated with train and bus use. Furthermore, the association with land-use mix is only significant for train and tram use, as buses tend to operate in areas with greater land-use homogeneity. When focused on inner Melbourne only, the influence of the built environment is diluted, while distance to public transport becomes more significant. The findings have important implications for practice, not only in terms of improving transit demand forecasting but also in targeting changes to the built environment to leverage higher transit ridership by mode.
Social-cultural impacts of China-Pakistan Economic Corridor on the well-being of local community
(Journal of Transport and Land Use, 2020) Sun, Yunpeng; Ghani, Usman; Hameed Pitafi, Abdul; Islam, Tahir
In this research, the impact of infrastructure improvement as a result of the China-Pakistan Economic Corridor (CPEC) initiative on the well-being and quality of life (QOL) of residents has been studied. Using the primary data collected from the local population of the Baluchistan province of Pakistan, a link between the socio-cultural effects of CPEC development and the subjective well-being of local citizens has been established. A total of 495 relevant responses were used to assess the well-being of the population through structural equation modeling. Results have shown that the social, cultural, and educational benefits of local communities are significant predictors of the well-being of citizens, and QOL issues have shown to have a major impact on the well-being of citizens. However, findings have also shown that the community resource has an important link with the subjective well-being of citizens. Furthermore, the results also give the local community perceptions of the CPEC initiative; hence the officials of the province can use the findings of this study to create prospective approaches based on the local community perceptions toward better exploitation of CPEC as an opportunity.
Fear follows form: A study of the relationship between neighborhood type, income and fear of crime at train stations
(Journal of Transport and Land Use, 2020) Strandbygaard, Sofie Kirt; Nielsen, Otto Anker; Jones, Alan Keith Spence; Grönlund, Bo; Jensen, Lotte M. B.
In pursuing fear-reduction strategies in public transport, the total experience of accessing rail stations should be taken into account. This article correlates passengers’ fear of crime at train stations with neighborhood types and income data within the pedestrian catchment area. The research is based on urban form and income around 84 S-train stations in the Copenhagen metropolitan area and nine years of passenger surveys on fear of crime at these stations. The study reveals a significant positive correlation between low income and fear of crime; the lower the income in an urban area, the more unsafe passengers feel at the station. However, when controlling for the relationship between income, safety and neighborhood type, stations in neighborhoods with urban form associated with low incomes have the lowest ratings of safety. The research indicates that train passengers’ sense of security is connected to neighborhood type and the city’s planning characteristics. This is an important finding for urban designers and planners working on the integration of public transport and station design in urban areas.
Analysis of the effect of multi-level urban form on bikeshare demand: Evidence from seven large metropolitan areas in the United States
(Journal of Transport and Land Use, 2020) Nasri, Arefeh; Younes, Hannah; Zhang, Lei
Bikeshare programs in their current form have been in place for several years in many cities across the United States. Encouraging people to use bikeshare for their daily routine travel has numerous social, economic, environmental, and health benefits. Therefore, it is important to understand factors influencing bikeshare use in different urban areas to improve the system and encourage more use. This paper investigates how the built environment at both local and regional scales influences bikeshare use in seven large metropolitan areas in the U.S. The study areas include Boston, Chicago, Philadelphia, Minneapolis, San Francisco, San Jose, and Washington, D.C., and the data consists of about 12 million bike trips from approximately 2,000 stations over a one-year period. In addition to linear regression models built for each individual city for comparison purposes, a multi-level mixed effect regression model is built to predict the number of trips originated from each station with respect to the local and regional built environment pattern. The results are consistent with previous research on the effect of land use at the local level on bikeshare demand and show that residential density, regional diversity, pedestrian-oriented road network density, and job accessibility via transit all have a significant positive effect on bikeshare demand. At the regional level, results suggest that the overall level of mixed-use development and overall bike-friendliness in the region (i.e., exclusive bike routes, right-of-way, and bike facilities) and higher congestion level in the region are significant factors influencing bikeshare activities and demand. Models developed in this study could be applied to other communities that are seeking to improve and/or expand their bikeshare systems, as well as cities planning to launch new bikeshare programs.
The influence of urban form and socio-demographics on active transport: A 40-neighborhoods study in Chengdu, China
(Journal of Transport and Land Use, 2020) Guan, ChengHe; Forsyth, Ann
In China, a centralized planning culture has created similar neighborhoods across the country. Using a survey of 1,048 individuals conducted in 2016 in Chengdu—located in a carefully conceptualized typology of neighborhood forms—we analyzed the associations between individual and neighborhood characteristics and active or nonmotorized transport behavior. Using several multiple logistic and multilevel models, we show how neighborhoods were categorized and how the number of categories or neighborhood types affected the magnitude of the associations with active transport but not the direction. People taking non-work trips were more likely to use active compared with motorized modes in all neighborhood types. Neighborhood type was significant in models but so too were many other individual-level variables and infrastructural and locational features such as bike lanes and location near the river. Of the 3-D physical environment variables, floor area ratio (a proxy for density) was only significant in one model for non-work trips. Intersection density and dissimilarity (land-use diversity) were only significant in a model for work trips. This study shows that to develop strong theories about the connections between active transport and environments, it is important to examine different physical and cultural contexts and perform sensitivity analyses. Research in different parts of China can help provide a more substantial base for evidence-informed policymaking. Planning and design recommendations were made related to active transport need to consider how neighborhoods, built environments, and personal characteristics interact in different kinds of urban environments.
Do people walk more in transit-accessible places?
(Journal of Transport and Land Use, 2020) Choi, Yunkyung; Guhathakurta, Subhrajit
While transit-oriented developments (TODs) are generally believed to promote the use of sustainable travel modes, the degree to which various components of TODs influence travel behavior is still debatable. This paper revisits Chatman’s (2013) question: “Does TOD need the T?” by addressing the effect of rail transit access in influencing walking behavior in TOD areas. In particular, we compare TODs to other similar areas, with rail transit access being the key variable, and examine whether people are more likely to walk in TODs for purposes other than transit use. This hypothesis is tested using traffic analysis zones (TAZs) in the Atlanta Metropolitan Region. First, we identify TAZs within rail catchment areas and use propensity scores to match them with other TAZs with similar built environmental characteristics except for rail transit access. We then conduct a statistical analysis comparing walking trips for both commuting and non-commuting trips in these two TAZ groups. Our results confirm that the likelihood of walking trips increases in transit-accessible TAZs compared to other similar areas without transit. Therefore, states and localities can maximize the benefits of pedestrian-friendly built environments by making rail transit access an important part of their planning and design.
Multilevel spatial impact analysis of high-speed rail and station placement: A short-term empirical study of the Taiwan HSR
(Journal of Transport and Land Use, 2020) Tsai, Yu-Hsin; Guan, Jhong-yun; Chung, Yi-hsin
Understanding the impact of high-speed rail (HSR) services on spatial distributions of population and employment is important for planning and policy concerning HSR station location as well as a wide range of complementary spatial, transportation, and urban planning initiatives. Previous research, however, has yielded mixed results into the extent of this impact and a number of influential factors rarely have been controlled for during assessment. This study aims to address this gap by controlling for socioeconomic and transportation characteristics in evaluating the spatial impacts of HSR (including station placement) at multiple spatial levels to assess overall impact across metropolitan areas. The Taiwan HSR is used for this empirical study. Research methods include descriptive statistics, multilevel analysis, and multiple regression analysis. Findings conclude that HSR-based towns, on average, may experience growing population and employment, but HSR-based counties are likely to experience relatively less growth of employment in the tertiary sector. HSR stations located in urban or suburban settings may have a more significant spatial impact. This differential in spatial change may be attributed to a high concentration of some subsectors and transportation services in the study area. Policy implications include adopting policies that encourage higher density at the local level, considering rural areas as a last choice for the installation of new HSR stations, and the use of HSR station placement to initiate brownfield urban regeneration in the urban core.
Impact of land use on bicycle usage: A big data-based spatial approach to inform transport planning
(Journal of Transport and Land Use, 2020) Zhao, Yi; Lin, Qiaowen; Ke, Shangan; Yu, Yanghang
Bicycling is an alternative of urban transport mode, which is significantly influenced by land use. This paper makes an effort to quantify the magnitude and direction of the impact. We first develop a theoretical framework to establish links between land use and bicycle usage. Then, trip data is crawled from Mobike, one of the largest newly emerging, free-floating bike sharing operators in Shenzhen (China), for a total of more than 7.8 million records over 191 consecutive days. And bicycling frequency, travel duration, and riding distance are obtained to be proxies of bicycle usage. Land-use characteristics regarding bicycling are comprehensively indicated by a set of standardized variables including three dimensions, land-use type, land-use mix, land-use connections, and 12 concrete indices. Panel spatial model is applied to quantify the associations at the district level with socioeconomics controlled. Results show that the percentage of green land has a remarkable impact on bicycle usage outcomes and land-use mix is positively associated with bicycling frequency. Density of intersections contributes to longer trip duration. Bicycle lane is a positive facilitator on workdays, while the number of stations is positively related to bicycle usage, especially frequency and distance. These findings provide insight into land use-transport interaction and could be of value to policymakers, planers and practitioners for transport planning while incorporating bicycling-friendly principles.
Identifying the combined effect of shared autonomous vehicles and congestion pricing on regional job accessibility
(Journal of Transport and Land Use, 2020) Zhong, Shaopeng; Cheng, Rong; Li, Xufeng; Wang, Zhong; Jiang, Yu
Most of the existing research on shared autonomous vehicles (SAVs) and road congestion pricing have studied the short-term impact on traffic flow. These types of studies focused on the influences on mobility and ignored the long-term impacts on regional job accessibility. Given this, from the perspective of land use and transportation integration, this study explored the long-term effects of SAVs and cordon-based congestion pricing on regional land use, transportation, and job accessibility. The contributions of this study have been summarized by the following three purposes. First, to the best of the authors' knowledge, this study was the first attempt to identify the long-term impact of the combination of these two technologies on regional job accessibility. Second, compared to the previous research methodology, this study adopted the land use and transportation integrated model (TRANUS model) and scenario planning to ensure the comprehensiveness and validity of the results. Third, this study analyzed the spatial heterogeneity of the impact of the combination of the two technologies on regional job accessibility in different areas with different built-environment attributes. To realize this purpose, this study quantitatively classified traffic analysis zones (TAZs) using data mining technology, i.e., factor analysis and clustering analysis. Results showed that the introduction of SAVs will contribute to job and population development in the charging zone and reduce the negative effect of road congestion pricing. From the perspective of reducing the average travel time between TAZs, the best strategy will be to implement SAVs alone, followed by integrated use of SAVs and road congestion pricing, while the worst strategy will be to implement the cordon-based congestion pricing policy alone. By comparison, from the perspective of improving regional job accessibility, the effect of introducing SAVs was better than that of road congestion pricing, while the combination of these two technologies was not superior to implementing SAVs alone.
Affecting commute mode choice in Southern California: Which employer-based strategies work?
(Journal of Transport and Land Use, 2020) Kane, Kevin; Hsu, Jenneille; Cryer, Joseph; Anderson, Marco
Interest in mandatory employer-based trip reduction (EBTR) programs has been renewed due to increased emphasis on reducing transportation-related greenhouse gas emissions. This paper analyzes survey data from 2004 to 2016 from an EBTR program in Southern California, known as Rule 2202, which allows employers with more than 250 workers to choose among implementing commute reduction strategies to meet performance standards, show evidence of obtaining omissions credits, or pay a fee-in-lieu. We report program statistics and conduct bivariate and regression analyses to determine which land-use and location characteristics, employer characteristics, and mitigation strategies explain cross-sectional differences in average vehicle ridership (AVR) and AVR improvement to understand where future AVR increases might be realized. Decreasing program participation suggests that alternatives to commute-reduction strategies make financial sense to regulated employers, but Rule 2202 employers report higher alternative transportation shares than the region as a whole. AVR is found to be highest at smaller worksites, in transit-supported and pedestrian-friendly neighborhoods, and where employers support vanpool programs. Multivariate analyses indicate that AVR gains were also highest in commercially dense neighborhoods, for retail businesses, and where guaranteed ride home programs were offered, showing promise for future AVR gains.