The effectiveness of congestion charges and parking prices as monetary disincentives to reduce car traffic and alleviate congestion in highly demanded urban areas is investigated, focusing on Jerusalem's diverse and congested city center. A tailored MATSim agent-based simulation model was used to examine various payment scenarios and assess the congestion level impacts of entry charges to the city center. Entry charges directly influence the number of vehicles entering the area; parking prices mostly the dwell time. Implementing a moderate daily payment of €10, either as a combined charge or separately, resulted in a substantial 25% reduction in congestion and potentially a reduction of 7.5% to 30% of emissions in the city center. Parking pricing advantages are augmented as the charged area expands. Strategic implementation of these monetary tools can effectively allow cities to manage traffic congestion, reduce pollution, and encourage a shift to sustainable transportation modes.

Public transport network design is the goal of numerous projects, and the models and algorithms that facilitate this design are the focus of transportation science research. Yet this great variety of tools is hardly employed in planning practice. We claim that the reason for this gap is the inability of the formal approaches to make the planner a part of the sustainable mobility design. To bridge between the analytical methods and planners we propose a novel Transit Planning Support System (TPSS). The TPSS is based on heuristic optimization algorithms for establishing and canceling transit lines, and agent-based models for assessing travelers' adoption of the proposed changes. TPSS remains open for the planner's intervention at every stage, bringing the sustainable mobility mindset into the design process.

Based on the anonymized dataset of one million shared scooter rides collected by the Tel Aviv municipality, we investigate the behavior of the shared e-scooter users in Tel Aviv and the resulting dynamics of the scooters’ spatio-temporal patterns. The users’ choice of the shared e-scooters as a transportation mode follows fast and frugal heuristics: the user who activated the shared scooter’s application continues with the ride when the closest available scooter is close enough, at up to 50-100 meters from her. Riders strongly prefer bike paths for riding and essentially deviate from the shortest path between the origin and destination and choose the routes with the higher percentage of bike paths. The longer the route, the higher the fraction of the bike paths in the rider’s route and the difference between the shortest and chosen paths. We also demonstrate that the operators fail to match the supply to the demand and the scooters are oversupplied in the central part of the city, where the demand is high, and undersupplied in the rest of the city, where the demand is essentially lower. Based on the analysis we propose a new policy of spatial adjustment between the demand and supply.

This research explores the impact of urbanization on familial spatial codes within informal settings and sheds light on their adaptation to contemporary processes. Through comparing residential patterns between traditionally clan-based neighbourhoods alongside urbanized mixed-familial ones in the Palestinian-Israeli town of Sakhnin, the study seeks to scrutinize the socio-economic and political influences on the conduct of traditional code-based systems. Employing GIS analysis, the study examines a two-decade development period of residential patterns in both types of neighbourhoods and uncovers distinct spatial configurations. However, comprehensive interviews with residents reveal that despite urbanization constraints, the familial code continues to guide bottom-up development.

Cities are so complex that we constantly build models to represent them, understand them and attempt to plan them. Models represent a middle ground between the singular configurations of cities and universal theories. This is what makes them valuable and prone to circulate (between places, institutions and languages) and evolve to adapt to new ideas, local conditions and/or other models. When it comes to analytical urban models (i.e. analytical representations of cities developed to study or simulate part of their structure or dynamics), there is a lack of academic understanding regarding how context and circulation affect their content, use and interpretation. What happens to analytical urban models and their reception during their circulation across geographical and disciplinary boundaries? How have different academic disciplines interacted with, contributed to and been influenced by analytical urban models? What are the consequences of urban models' mobility for our understanding of cities? In this article, we employ the policy mobilities framework to analyse the circulation of analytical urban models. We use six canonical models as case studies to determine how their assumptions came about and how these models have circulated across different domains of policy and application by using biographical information and model analysis. The first contribution of the article is to demonstrate by example that our hypothesis regarding the influence of context is consistent. We also show that highly transferable/mobile models share common characteristics relating to contingent factors such as their creators' biographies, institutional context and the traditional markers of power relations.

Analyzing urban pattern dynamics based on construction projects, we classify them into three types - infilling, fringe, and leapfrogging, and focus on the role of leapfrogging projects as seeds for new developments, leading to uncontrolled urban sprawl. To study the leapfrogging phenomenon, we investigate the sprawl of three Israeli cities - Netanya, Haifa, and Safed over 54 years from 1964 to 2018 and conduct a country-wide analysis of the urban sprawl of all 66 Israeli municipalities between 2013 and 2018. Our analysis is based on a country-wide GIS database of roads, buildings, other infrastructure elements, and development plans, as well as high-resolution aerial photos covering the investigated areas and periods. We uncover and characterize a positive feedback mechanism of rapid leapfrogging developments that attract further developments in their proximity and emphasize the potential of leapfrogging development to force divergence from statutory development plans.

Abstract. Public transportation (PT) studies often overlook non-routine trips, focusing on commuting trips. However, recent research reveals that occasional trips comprise a significant portion of public transportation trips. Furthermore, traveler preferences for non-routine trips essentially differ from their preferences for regular commuting. We investigate non-routine trips based on a database of 63 million records of PT boardings made in Israel during June 2019. The behavioral patterns of PT users are revealed by clustering their boarding records based on the location of the boarding stops and time of day, applying an extended DBSCAN algorithm. Our major findings are that (1) conventional home-work-home commuters are a minority and constitute less than 15% of Israeli riders; (2) at least 30% of the PT trips do not belong to any cluster and can be classified occasional; (3) The vast majority of users make both recurrent and occasional trips. A linear regression model provides a good estimate (R2 = 0.85) of the number of occasional boardings at a stop as a function of the total number of boardings, time of a day, and land use composition around the trip origin.

We present a new approach to categorizing different types of urban development, namely infilling, fringe, and leapfrogging, based on construction projects as the fundamental unit of analysis. We focus on the role of the leapfrogging projects as seeds for new developments, leading to urban sprawl extending beyond statutory plans. To examine this phenomenon, we analyze the 50-year growth of three major Israeli cities: Netanya, Haifa, and Safed and the 5-year dynamics of 66 cities in Israel that account for 68% of the country’s population. Our investigation utilizes extensive databases of Israeli development plans, along with high-resolution aerial photographs covering the investigated areas and time periods. These datasets were supplemented by detailed Israeli databases encompassing roads, buildings, and other infrastructure elements, compiled by the Israeli Mapping Centre for the year 2018. Our analysis reveals that although most construction projects in Israel adhere to land-use plans, urban sprawl in Israel remains highly unpredictable. Leapfrogging is specific in terms of both place and time, attracts additional development nearby, and forces the divergence from development plans. We conclude that urban modelers’ view of urban dynamics being driven by common and systematic forces, is unrealistic. Instead, every city has its specific and self-enforcing development drivers that define its land-use dynamics. This explains the limited success of the Cellular Automata (CA) models in explaining and predicting urban dynamics. 2012 ACM

Public transportation (PT) studies often neglect non-routine trips focusing predominantly on commuting. However, recent research revealed that occasional trips make up a substantial portion of public transport journeys, and traveler preferences for non-routine trips diverge from their preferences for regular commuting. We study non-routine trips based on a database of 63 million smartcard (SC) records of PT boardings made in Israel during June 2019. The characteristics of these trips are revealed by clustering PT users' boarding records based on the location of the boarding stops and time of day, applying an extended DBSCAN algorithm. Our major findings are that (1) conventional home-work-home commuters are a minority in Israel and constitute less than 15% of the riders; (2) at least 30% of the PT trips do not belong to any cluster and can be classified as occasional; (3) The vast majority of users make both recurrent and occasional trips. A linear regression model provides a good estimate (R2 = 0.85) of the number of occasional boardings at a stop as a function of the total number of boardings, time of day, and land use composition around the location of trip origin. We discuss the potential applications of our approach in the landscape of diverse flexible PT.

We employ calibrated and validated MATSim multi-modal model of the Jerusalem Metropolitan Area traffic for assessing the effectiveness of Demand-Responsive-Transport (DRT) with ridesharing as a possible game-changer of the existing equilibrium between public transport and private cars. We investigate the combined effect of congestion charges, parking prices, and shared DRT services on the modal split and demonstrate that the DRT is effective when introduced together with congestion charges or parking prices. The policy effectiveness depends on the choice of the deterrence mechanism – given the overall payment for entering the controlled area, the effect of congestion charges depends on the size of the area. At the same time, parking prices are equally effective for an area of any size and, thus, seem advantageous.

Motion planning in an uncertain dynamic environment is a complex task, especially when obstacles move in a non-linear fashion. In this paper obstacles refer to other vehicles, pedestrians, bicycles, riders etc. In such cases, predicting the obstacles' kinematics requires a forecast of the obstacles' trajectories. The choice of the forecast time horizon is critical, especially in conflict scenarios where an accident can be avoided only by adjusting the maneuvers of one of the vehicles. In this paper, we present an approach for establishing optimal forecast time based on Maneuverability Maps that determine a vehicle's possible maneuvers. The approach can be used as guidance for human drivers and can also be implemented in the control system of autonomous vehicles. Simulation results indicate that optimizing the forecast time in a conflict scenario can reduce the probability for an accident.

Urbanization tends to increase runoff volumes, which might cause flooding and reduce groundwater recharge.Since the design of impermeable urban elements is based on the water flow volume before their construction, once they are erected the induced change to the local drainage pattern might generate flooding of the newly developed and previously developed areas.As such, precise modeling is essential to allow municipal watershed-sensitive hydrological design, which may prevent impervious urban surface expansion negative impacts.The digital elevation model that represents the watershed relief at any given location is the hydrological modeling base layer, which is necessary for describing urban landscapes and watersheds.The common notion is that the finer the elevation model resolution is, the more precise the hydrological model will be.Nevertheless, it is suggested that over-accuracy might be redundant.In the same manner, the land use classification resolution should be aligned with the modeling requirements.Such careful evaluation of the modeling resolution will reduce the computing resources needed for the modeling procedure and may be utilized as a sensitivity filter for insignificant tributaries of the hydrological network.This paper demonstrates a nominal procedure for urban watershed sub-basin analysis, which is the initial stage for detailed urban runoff modeling.It was found that the scale-optimized model performed very well and was found suitable for the prediction of runoff volume and discharge from a mainly urban, mountainous karstic watershed. Hosted fileessoar.10512202.1.docxavailable at https:

The future of Demand-Responsive Transport (DRT) is investigated in respect to the potential travelers’ demand. The potential demand for the DRT service is studied based on a database of 63 million records of the public transportation (PT) trips made in Israel using a smartcard in June, 2019. Our major assumption is that travelers may prefer a DRT service over conventional PT for making a non-routine trip that occurs only once a month. The behavioral patterns of PT users were revealed by clustering their boarding records based on the location of the boarding stops and the boarding time of day using an extended DBSCAN algorithm. We make three major discoveries: (1) at least 30% of the PT trips do not belong to any cluster of monthly user activity; (2) conventional home-work-home commuters are a minority and constitute less than 15% of the drivers (3) The vast majority of the users make, during the month, both recurrent and occasional trips. The share of occasional trips is 25% for frequent users who make over 40 trips a month, and as high as 60% for those who board PT up to 10 times a month. We uncover the dependencies of trip regularity on population group, time of day and land use composition around the location of trip origin. We conclude that in high-density urban areas, conventional PT may lose substantial ridership to DRT. The spillover to DRT may be prevented by improving the level of service and incentivizing conventional PT users. We discuss using our approach to identify city areas and PT lines where occasional ridership is common, and user groups that are more likely to switch from conventional PT to DRT.

By definition, the Mobility-as-a-Service (MaaS) system integrates transportation modes of very different flexibility - taxis, buses, light rail, ride-hailing. MaaS major unknown is the effectiveness of the ride-sharing modes. We employ a calibrated and validated MATSim multi-modal traffic model of the Jerusalem Metropolitan Area (JMA) to assess the introduction of Shared Autonomous Vehicles (SAV), as a possible game-changer of the existing equilibrium between the Public Transport (PT) and private cars. First, we confirm the recent empirical observations that ride-sharing modes mostly attract PT users, while their attractiveness for private car users is relatively low. Second, we investigate the problem of preserving travelers' flows to the Jerusalem center while reducing personal car use. For this purpose, we investigate the effect of parking prices and congestion charges in the system with the additional SAV fleet that serves trips to-and-from the center of the city. We propose a balanced set of carrot-and-stick measures to enforce a sustainable modal shift in JMA towards the use of PT and SAV service.

Parking occupancy in the area is defined by three major parameters - the rate of cars arrivals, the dwell time of already parked cars, and the willingness of drivers who are searching but yet did not find a vacant parking spot, to continue their search. We investigate a series of theoretical and numeric models, deterministic and stochastic, that describe parking dynamics in the area as dependent on these parameters, over the entire spectrum of the demand to supply ratio, focusing on the case when the demand is close to or above the supply. We demonstrate that a simple deterministic model provides a good analytical approximation for the major characteristics of the parking system - the average fraction of cars among the arriving that will find parking in the area, the average number of cars that cruise for parking, and average cruising time. Stochastic models make it possible to estimate the distributions of these characteristics as well as the parameters that are related to the variance of these distributions, like the fraction of the arriving cars that find parking in less than t minutes.

The partition of the Mobile Phone Network (MPN) service area into the cell towers' Voronoi polygons (VP) may serve as a coordinate system for representing the location of the mobile phone devices. This view is shared by numerous papers that exploit mobile phone data for studying human spatial mobility. We investigate the credibility of this view by comparing volunteers' locational data of two kinds: (1) Cell towers' that served volunteers' connections and (2) The GPS tracks of the users at the time of connection. In more than 60% of connections, user's mobile device was found outside the VP of the cell tower that served for the connection. We demonstrate that the area of possible device's location is many times larger than the area of the cell tower's VP. To comprise 90% of the possible locations of the devices that may be connected to the cell tower one has to consider the tower's VP together with the two rings of the VPs adjacent to the tower's VPs. An additional, third, ring of the adjacent VPs is necessary to comprise 95% of possible locations of the devices that can be connected to a cell tower. The revealed location uncertainty is in the nature of the MPN structure and service and entail essential overlap between the cell towers' service areas. We discuss the far-reaching consequences of this uncertainty in regards to the estimating of locational privacy and urban mobility. Our results undermine today's dominant opinion that an adversary, who obtains the access to the database of the Call Detail Records maintained by the MPN operator, can identify a mobile device without knowing its number based on a very short sequence of time-stamped field observations of the user's connection.

Abstract. Transportation Network Companies (TNC), like Uber, Lyft, and VIA, started their activities a decade ago with a far-reaching hope that Mobility-On-Demand (MOD) transportation services would decelerate or even stop the ever-growing congestion. However, it didn't happen; the negative incentives, like congestion charges and higher parking prices, seem to be the only policy tools for influencing congestion and associated negative externalities like pollution and noise. The question is whether we can establish socially acceptable congestion charges and parking prices that will effectively reduce the arrivals and traffic in highly congested areas and become the background for the future MOD arrangement? We employ the MATSim agent-based simulation model (Horni et al., 2016) of multi-modal traffic in Jerusalem Metropolitan Area (JMA) to address this problem. We investigate whether the combination of congestion and parking prices can force drivers to use Public Transport (PT), thus reducing arrivals with the private cars into the center of the city. The model study demonstrates that a reasonable charge of 7–12€ for entering the city center could decrease arrivals by 25%. From the transport policy point of view, the effects of congestion charges and parking prices are different – the increase in the congestion charges decreases arrivals. In contrast, the increase in parking prices decreases the dwell time. We discuss the policy consequences of employing each of the two mechanisms.

During the last few decades, the complex systems theory has successfully disclosed the basic features of urban and regional dynamics. The time has come to make the next step, and apply our knowledge of urban complexity to forecasting and controlling particular urban phenomena. The latter requires deep understanding of the selected subject, including the necessary components of urban infrastructure, factors that govern the phenomenon and verifiable models of human behavior and finally, extensive and representative data on all these components. Until very recently, the lack of data restrained complex system theory from becoming operational. We claim that this barrier has been rapidly dissolving during the last decade. We apply complex system theory to studying the problem of urban parking dynamics – a critical component of urban traffic in every big city. Urban parking is only loosely connected to the general traffic and can be thus considered as a relatively simple phenomenon. At the same time, parking dynamics exhibit all major attributes of a complex system – non-linearity, emergence and path dependence. We aim at deep understanding of parking dynamics for establishing urban parking policy, the two major goals of which are inherently conflicting: to reduce parking search time for car drivers on the one hand, while enforcing urban resident and visitors to abandon private cars in favor of public transport on the other. Urban parking dynamics are an outcome of the interplay between parking supply and prices that are controlled by the city and parking demand created by residents and visitors. We represent these dynamics with a hierarchy of models, starting from an aggregate and non-spatial model, proceeding with a model of parking search in an abstract homogeneous space and concluding with an agent-based spatially-explicit model of parking search. Modeling drivers' parking search demands comprehensive depiction of their decision-making and we disclose this behavioral component with serious parking games. The proposed set of models fully captures urban parking dynamics and adequately forecasts the consequences of parking policy decisions in real cities.