Modelling Joint Development of Light Rail Transit Stations and Land Use - The Case of Tel-Aviv

Light Rail Transit (LRT) has been gaining popularity as a means of decreasing private automobile dependency and thus reducing car pollutants, relieving congestion and enhancing community liveability. LRT is also perceived as an important generator of economic growth, mainly in old urban centers. Through the improvement of accessibility to CBDs (Central Business Districts) planners and decision makers expect to revitalize central cities' vis-a-vis the increasing competition from the growing suburban shopping malls. More specifically, the objective of this paper is to explore the complex relationship between transportation and land use by analyzing the optimal composition of land use around the proposed light rail stations. Density and diversity are the two most important characteristics of urban land use development. We examine changes in land use adjacent to the LRT stations in metropolitan Tel-Aviv, and their impact on the demand for total travel in particular. These changes include hypothetical scenarios of alternative land use compositions, densities and intensities of residential, employment, and commercial land uses. In order to measure the impact of these changes on travel, a demand model is calibrated. The traditional four-step transportation model is retrofitted with alternative land use density and diversity variables. Among these are: residential density, job-population balance etc. As such, the re¬structured model is more sensitive to the different hypothetical land use scenarios and is expected to predict ridership demand changes more accurately. The results have shown that some of the land use variables are extremely important for trip generation trends forecasts, especially trip attraction trends. Furthermore, the simulations of the various land use policies are able to display the spatial reaction of trip rates to land use function, density, degree of mix, and household characteristics. The results of this study could serve to better assess urban transportation ridership demands, especially since they serve as input for mode choice analyses. Moreover, by exploring this subject even further, planners and decision makers will be able to attain a clearer and more comprehensive picture of optimal land use patterns surrounding station areas, and in doing so, improving the quality of life of urban dwellers, commuters and visitors.

Modeling adoption of innovations in agriculture using discrete choice models

This paper is concerned with the development of varieties and fertilization techniques of greenhouse tomatoes, and their spatial diffusion in the northwestern region of the Negev in Israel. The main objective of the paper is to identify the factors affecting the farmers’ decision to adopt innovations and the factors inducing the process of knowledge-diffusion in the rural region. The approach adopted is the use of discrete choice models based on random utility theory. Results of the empirical analysis when applying the disaggregate Logit Model indicate that the regional, local and individual attributes have a significant bearing on the farmers’ decision-making process in regard to choosing among alternative tomato varieties and fertilization techniques. The findings indicate that the models constructed for this study may be used as a planning tool for the purpose of evaluating the effect of different factors on the spatial diffusion of innovations in rural regions. The results of the research could also assist decision-makers in formulating development policies for rural regions. Keywords: Spatial diffusion; discrete choice models; greenhouse tomatoes; nested logit

Book Review: Tampère, C.M.J., Viti, F. and Immers, L. H. (eds.): New Developments in Transport Planning: Advances in Dynamic Traffic Assignment

This book contains a selection of contributions from the second Dynamic Traffic Assignment (DTA) Symposium held at the Katholieke Universiteit Leuven, Belgium, in June 2008. The nineteen individual chapters of the book are suitably classified in four distinct parts, providing a coherent state-of-the-art overview of fundamental DTA research and practice. The international experts that contribute to the book are leading researchers in the field, and provide both wide-spread reviews and fresh looks on the various issues related to DTA

A general equilibrium model for multi-passenger ridesharing systems with stable matching

This paper proposes a general equilibrium model for multi-passenger ridesharing systems, in which interactions between ridesharing drivers, passengers, platforms, and transportation networks are endogenously captured. Stable matching is modeled as an equilibrium problem in which no ridesharing driver or passenger can reduce ridesharing disutility by unilaterally switching to another matching sequence. This paper is one of the first studies that explicitly integrates the ridesharing platform multi-passenger matching problem into the model. By integrating matching sequence with hyper-network, ridesharing-passenger transfers are avoided in a multi-passenger ridesharing system. Moreover, the matching stability between the ridesharing drivers and passengers is extended to address the multi-OD multi-passenger case in terms of matching sequence. The paper provides a proof for the existence of the proposed general equilibrium. A sequence-bush algorithm is developed for solving the multi-passenger ridesharing equilibrium problem. This algorithm is capable to handle complex ridesharing constraints implicitly. Results illustrate that the proposed sequence-bush algorithm outperforms general-purpose solver, and provides insights into the equilibrium of the joint stable matching and route choice problem. Numerical experiments indicate that ridesharing trips are typically longer than average trip lengths. Sensitivity analysis suggests that a properly designed ridesharing unit price is necessary to achieve network benefits, and travelers with relatively lower values of time are more likely to participate in ridesharing

Modelling bicycle route choice using data from a GPS-assisted household survey

This paper considers bicycle route choice for commuter trips. Bicycle route preferences are analysed using a dataset from a GPS-assisted household travel survey conducted in the Tel Aviv metropolitan area. Different choice set generation methods were applied to generate alternative routes for each observation, and the matching with the actual route is discussed. Model estimation is performed for different route choice sets to test the sensitivity of the parameter estimates. The results obtained are quite consistent, and indicate an expected tendency to ride in longer routes, but with separated bike lanes. In the absence of such lanes, riders prefer to use local streets and avoid riding on busy arterial streets and highways

A SEMI-COMPENSATORY RESIDENTIAL CHOICE MODEL WITH FLEXIBLE ERROR STRUCTURE

Spatial choices entailing many alternatives (e.g., residence, trip destination) are typically represented by compensatory models based on utility maximization with exogenous choice set generation, which might lead to incorrect choice sets and hence to biased demand elasticity estimates. Semi-compensatory models show promise in increasing the accuracy of choice set specification by integrating choice set formation within discrete choice models. These models represent a two-stage process consisting of an elimination-based choice set formation upon satisfying criteria thresholds followed by utility-based choice. However, they are subject to simplifying assumptions that impede their application in urban planning. This paper proposes a novel semi-compensatory model that alleviates the simplifying assumptions concerning (i) the number of alternatives, (ii) the representation of choice set formation, and (iii) the error structure. The proposed semi-compensatory model represents a sequence of choice set formation based on the conjunctive heuristic with correlated thresholds, and utility-based choice accommodating alternatively nested substitution patterns across the alternatives and random taste variation across the population. The proposed model is applied to off-campus rental apartment choice of students. The population sample for model estimation consists of 1,893 residential choices from 631 students, who participated in a stated-preference web-based survey of rental apartment choice. The survey comprised a two-stage choice experiment supplemented by a questionnaire, which elicited socio-economic characteristics, attitudes and preferences. During the experiment, respondents searched an apartment dataset by a list of thresholds for pre-defined criteria and then ranked their three most preferred apartments from the resulting choice set. The survey website seamlessly recorded the chosen apartments and their respective thresholds. Results show (i) the estimated model for a realistic universal realm of 200 alternatives, (ii) the representation of correlated threshold as a function of individual characteristics, and (iii) the feasibility and importance of introducing a flexible error structure into semi-compensatory models

Modeling adoption of innovations in agriculture using discrete choice models

This paper is concerned with the development of varieties and fertilization techniques of greenhouse tomatoes, and their spatial diffusion in the northwestern region of the Negev in Israel. The main objective of the paper is to identify the factors affecting the farmers’ decision to adopt innovations and the factors inducing the process of knowledge-diffusion in the rural region. The approach adopted is the use of discrete choice models based on random utility theory. Results of the empirical analysis when applying the disaggregate Logit Model indicate that the regional, local and individual attributes have a significant bearing on the farmers’ decision-making process in regard to choosing among alternative tomato varieties and fertilization techniques. The findings indicate that the models constructed for this study may be used as a planning tool for the purpose of evaluating the effect of different factors on the spatial diffusion of innovations in rural regions. The results of the research could also assist decision-makers in formulating development policies for rural regions. Keywords: Spatial diffusion; discrete choice models; greenhouse tomatoes; nested logi