The paper aims at introducing an advanced delivery tour planner to support operators in urban delivery operations through a combined approach which chooses delivery bays and delivery time windows while optimizing the delivery routes. After a literature review on tools for the management and the control of the delivery system implemented for optimizing the usage of on-street delivery bays, a prototypical tour delivery planner is described. The tool allows transport and logistics operators to book the delivery bays and to have real-time suggestions on the delivery tour to follow, through the minimization of the total delivery time. Currently, at development phase, the tool has been tested in a target zone, considering the road network and time/city delivering constraints and real-time data about vehicles location, traffic and delivery bay availability. The tool identifies the possible tours based on the delivery preferences, ranks the possible solutions according to the total route time based on information on the road network (i.e. travel time forecasts), performs a further optimization to reduce the total travel times and presents the user the best alternative along with the indications of which delivery bay to use in each delivery stop. The developed prototype is composed by two main parts: a web application that manages communication between the database and the road network simulation, and, an Android mobile App that supports transport and logistic operators in managing their delivering, pre trip and en route, showing and updating routing based on real-time information.
This paper deals with a first attempt to evaluate the technical and economic feasibility of a sharing mobility scenario for the central area of Rome in the year 2035. The main aspects of the proposed scenario focus on the use of electric automated vehicles, on car sharing, on limitations of the use of private cars and on road pricing in the central area of the city. The results indicate a technical and financial feasibility of the scenario.
This paper analyses the current structure of taxi service use in Rome, processing taxi Floating Car Data (FCD). The methodology used to pass from the original data to data useful for the demand analyses is described. Further, the patterns of within-day and day-to-day service demand are reported, considering the origin, the destination and other characteristics of the trips (e.g. travel time). The analyses reported in the paper can help the definition of space-temporal characteristics of future Shared Autonomous Electrical Vehicles (SAEVs) demand in mobility scenarios.
Exploring Temporal and Spatial Structure of Urban Road Accidents: Some Empirical Evidences from RomePublished: 12 December 2018 by Springer Nature in Molluscs
One of the measures that can reduce the negative effects of road accidents is the quick arrive of emergency vehicles to the accident area. This measure requires an effective location in space and on time of these vehicles. This location can be decided after an analysis of the available data in order to find the spatial and temporal characteristics of road accidents. The study presented in this paper uses time series accident data of the 15 districts of Rome Municipality, collected in four months in 2016. Results show that such analyses can be a powerful tool for identifying the temporal and spatial structure of road accidents in urban areas and that relevant differences exist in temporal patterns among different districts and types of road users. Further, such outcomes can be used as inputs to decide the optimal location on the urban area of mobile emergency units.
Delivery bay availability for loading and unloading operations is critical to reduce times and costs of logistics operations, as well as for improving city sustainability and liveability. Beyond defining the appropriate number and location of such bays, urban sustainability and liveability can be improved with telematics tools which enable real-time bay reservation and monitoring, integrating such information within freight routing solutions. This paper presents an architecture for such tools along with methodology integrating delivery bay planning with transportation demand modelling through simulation, allowing computation of performance indicators to be used for ex-ante assessment in planning delivery scenarios. The results were validated through a simulation-based approach on Rome's limited traffic zone.
A behavioural modelling framework with a dynamic travel strategy path choice approach is presented for unreliable multiservice transit networks. The modelling framework is especially suitable for dynamic run-oriented simulation models that use subjective strategy-based path choice models. After an analysis of the travel strategy approach in unreliable transit networks with the related hyperpaths, the search for the optimal strategy as a Markov decision problem solution is considered. The new modelling framework is then presented and applied to a real network. The paper concludes with an overview of the benefits of the new behavioural framework and outlines scope for further research.
This chapter analyzes the process that should guide the definition of a city logistics plan according to the indications provided by the large literature on this topic. Moving from several literature findings that push to define city logistics theories, the process to follow for designing city logistics plans has been investigated focusing on a real test case. The chapter thinks back over the implementation of the city logistics plan in the Calabria region (Italy), a region with some experience in city logistics. According to the literature overview and the sustainability goals pursued by the regional government, a set of city logistics measures were selected to address such goals. The chapter summarizes the methods, models and indications coming from the application field and focuses on the interconnected processes to study and implement city logistics. Finally, the implementation process of a city logistics plan is specified and the real case of the Calabria region is discussed.
The paper compares the characteristics of urban freight transport in some European cities, implementing a methodology which uses similar interviews with retailers and transport operators. The main objective of this study is to evaluate the similarities and differences in terms of socio-economic characteristics and commercial structures, and current distribution patterns followed by different transport and logistics operators. The study shows the flexibility of the methodology used in different applicative contexts and points out that there are some different patterns of urban distribution that need to be taken into account when implementing city logistics measures.
The search of optimal travel strategy on unreliable transit network is analyzed as solution of a Markov decision problem and two uses of this approach, recently presented by the authors, are recalled and compared. The first application is relative to normative strategy search, such as for path recommendation in innovative transit trip planners. The second use concerns subjective optimal strategy search in a dynamic strategy-based path choice modelling, especially suitable for real-time run-oriented simulation-based mesoscopic assignment models. The paper concludes with an overview of the benefits of the approach and outlines scopes for further research.
Service reliability is one of the most important determinants for shifting people to public transport. In low-frequency services, the reliability is considered in terms of punctuality, which becomes significant also from the standpoint of operators, given that punctuality indicators are generally included in business models. As a support for further improvement in bus punctuality in the urban area of Rome, analyses were carried out using automatic vehicle location (AVL) data of a bus line with services mixed with other traffic components and therefore subject to high degrees of travel time variability. The analyses allowed the systematic components of bus dispatching irregularity to be revealed and to investigate to what extent these components are influenced by road congestion, and hence by delayed arrival times at terminals.
From the analysis of European accident data to safety assessment for planning: the role of good vehicles in urban areaPublished: 02 February 2017 by Springer Nature in European Transport Research Review
The paper focuses on unreliable dynamic transit service networks, on which, even if predictive info is available, trip planners should give dynamic strategy-based path suggestions, rather than provide a complete path up to destination. In the paper, the search for a travel strategy to be used as a path recommendation in innovative transit trip planners is analysed as a Markov decision problem, together with the relative solution approaches. Applicative examples of the procedure on a simple test network are then reported. Finally, some concluding remarks are made and future research perspectives outlined.
Bus travel time analysis is essential for transit operation planning. Then, this topic obtained large attention in transport engineering literature and several methods have been proposed for investigating its variability. Nowadays, the availability of large data quantities through automated monitoring allows more in-depth this phenomenon to be pointed out with new experimental evidence. The paper presents the results of some analyses carried out using automatic vehicle location (AVL) data of bus lines and automated vehicle counter (AVC) data on some corridors in the urban area of Rome where the bus services are mixed with other traffic and travel times are subject to high degrees of variability. The results show the effect of temporal dimension and similarity between travel time and traffic temporal patterns, and could open the road for the improvement of the short-term forecasting methods, too.
The paper focuses on unreliable dynamic transit service networks, on which trip planners should give strategy-based path suggestions, rather than a set of single paths from origin up to destination. Different types of optimal strategies, with their related hyperpaths and diversion rules, are defined and analyzed. A search method of a normative optimal strategy, which considers short and long term path attribute predictions, is presented and applied to a test network.
The opportunities offered by telematics development and the features required by travellers moving on more complex multimodal transit networks push to investigate new methods for generating path advice in transit trip planners. First, the study focuses on characteristics and limits of the methods used by current trip planners for path generation and then analyses the new methods applied by a new generation of trip planners (most at the prototypical developing stage). These methods use a group or, better, an individual traveller utility function, which allows personal preferences to be pointed out. As the individual utility functions in the transport modelling literature has been largely neglected, the second part of the study reports the state-of-the-art and some theoretical considerations on individual path utility function modelling, and recalls the approaches developed for including individual utility in new trip planners. Further, the results of individual utility function estimations, using surveys relative to the city of Rome, are presented and some aspects of the utility function calibration, including the info provider learning process of traveller preferences, are explored. The analyses show a significant improvement in using individual functions for path advice and a substantial influence of network complexity on the learning process.
Transit system ‘big data’ collecting and processing, and bidirectional communication between transit travellers and information centres are emerging as two factors that enhance the tools supporting short-term forecasting of network status for transit operations control and for traveller information. However, the current methodologies applied in these tools do not seem to have reached the level of research in the field of transit network modelling. Therefore, several methodological issues connected to the development of such tools are analysed in this paper. These issues concern application and development of real-time on-board load short-term forecasting methods, real-time best path advice, real-time transit assignment modelling, individual path choice modelling, and real-time updating and upgrading of demand and supply model parameters.
Urban Freight Transport Planning towards Green Goals: Synthetic Environmental Evidence from Tested ResultsPublished: 19 April 2016 by MDPI in Sustainability
This paper reviews the ex-post assessment of city logistics measures implemented in some European cities and, in a “what if” framework, proposes an analysis of tested environmental effects which may be useful in defining city logistics scenarios to be evaluated ex ante by simulation models. The analysis is performed in relation to the goals of environmental sustainability to pursue and the main characteristics of the cities in question (i.e., population and density). The paper aims to provide a tool that could be used in an ex-ante assessment methodology to identify a priori which measures (or set of measures) could best work in a specific city with respect to the environmental sustainability goals to pursue. Future scenarios can, thus, be readily defined and subsequently assessed by simulation tools in order to verify whether they meet the planned objectives. Although all measures can produce considerable environmental effects, the study shows that the choice of their implementation should be driven by the type of pollutant to detect.
This article presents a mesoscopic transit assignment model suitable for real-time prediction of on-board passenger numbers in transit networks with real-time individual predictive information on travel time components and also including on-board crowding. The path choice modeling framework is based on the reproduction of a travel strategy using random utility models that simulate both choices of departure time at origin and first access stop, and en-route choices of vehicle to board at stops. Such choices are based on attributes anticipated through a learning mechanism, which considers previous experiences and provides real-time predictive information. Within-day dynamic network loading considers vehicle capacity constraints, which allows the explicit modeling of fail-to-board events. Finally, results of an application on a real-size test network show the ability of the model to capture effects of providing individual predicted information on vehicle crowding.
Restocking in Touristic and CBD Areas: Deterministic and Stochastic Behaviour in the Decision-making ProcessPublished: 01 January 2016 by Elsevier BV in Transportation Research Procedia
The paper examines urban activity restocking process. The proposed models aim at examining how city logistics measures could modify the restocking process of retailers and ho.re.ca. managers located within the urban area. The process is considered in terms of distribution channel: pull or push movements to bring freight to the economic activities. The analysis has been based on surveys carried out in the inner area of Rome. The study points out that deterministic behaviour exists in relation to goods types and that the choices for acquisition (i.e. distribution channel and restocking area) are generally joint choices. For this scope, different behavioural models were tested according to different hypothesis on random residual distributions.
Although the store shopping remains the predominant way to buy, internet is modifying the end consumer's behaviour. In fact, the advance of information and communication technologies have pushed more and more people to choose to shop on-line. This can have significant impacts on freight traffic in urban areas because purchases have to be delivered to customers (e.g. at homes) through delivery tours that cannot always be optimised. Besides, additional costs for repeated deliveries can occur. The paper begins focusing on demographic and socio-economic factors that mainly influence end-consumer purchase production and subsequent trips. Then, a new system of models for simulating shopping choices, including e-shopping, is presented. The models were obtained by using surveys carried out in Rome where about 800 households were interviewed. The system of models were used to assess the effects on shopping and goods delivering under future demographic and socio-economic changes in an urban area. The results indicate these effects can be significant and specific solutions have to be pointed out for improving city sustainability.
Aiming at solving the problem of predicting in real-time the dynamic evolution of a transit system, this paper presents DYBUS2, a modeling framework proposed to overcome some limits of existing models by considering: (i) dynamic real-time simulation, (ii) modeling of travel behavior in the sphere of real-time information, by using a travel strategy approach, (iii) real-time prediction of on-board crowding, the information system should give to travelers, (iv) mesoscopic approach also on the demand side, by grouping travelers in packets. The first part of the paper gives an overview both of general transit network modeling and of DYBUS2 architecture, the latter presents the main modeling components, focusing on the new proposal for the real-time dynamic path choice modeling.
In order to improve the effectiveness of information provided to travelers of a transit network, the new generation of trip planners should give recommendations taking into account several factors, such as network unreliability and presence of diversion nodes where path decision can be made according to the occurrences of random events. In this context, travelers have not to rely on a single selected path, but they have to use a strategy, i.e. set of rules that allow travelers to reach the destination maximizing their expected utility. The availability of real-time predictive information requires the traditional optimal hyper-path approaches to be overcame and new ones to be developed. Further, as the values of path attributes forecasted are random variables and therefore, also with an information system, the uncertainty is not completely overcome. This paper explores some aspects of providing path recommendations in unreliable network, proposing a methodology for defining real-time optimal strategies, that combine predictive and expected values of path attributes.
The paper compares the characteristics of urban freight transport in Rome, Barcelona and Santander and the logistics measures being implemented in the three cities. The analysis is based on three similar surveys carried out in recent years involving interviews with retailers and transport operators. The main objective of this study is to evaluate the similarities and differences in terms of spatial patterns and current regulations, socio-economic characteristics and commercial structures, freight demand characteristics and current distribution patterns followed by different transport and logistics operators. The study shows that there are some different patterns of urban distribution that need to be taken into account when implementing city logistics measures in order to meet desired sustainability goals.
This paper focuses on an Advanced Traveler Advisory Tool (ATAT) aiming at supporting users travelling on multimodal networks and at suggesting the best path set according to user personal preferences. In order to find the best personal paths, the presented ATAT uses the Random Utility Theory framework to assign an estimation of the path utility perceived by the user for each path alternative. The first part of this paper illustrates the user needs and the ATAT logical architecture, and presents the modeling framework able to provide personalized pre-trip and en-route information. The second part reports the results of some test applications and the results of a benefit assessment of the ATAT use for transit travelers. Author(s) Nuzzolo, A. Dept. of Enterprise Eng., “Tor Vergata” Univ. of Rome, Rome, Italy Comi, A. ; Crisalli, U. ; Rosati, L.
Bi-directional communication among travelers and info center and transport network “big data” collecting and processing seem to be two new factors that can improve the tools that support network short-term forecasting for transit operations control and traveler advising. Some of these tools, with several methodological issues connected to their development, are analyzed over the paper.
City logistics long-term planning: simulation of shopping mobility and goods restocking and related support systemsPublished: 04 May 2014 by Informa UK Limited in International Journal of Urban Sciences
The growing necessity to improve city sustainability and liveability has pushed local administrators to look also at medium/long-term city logistics measures, such as land-use governance policies. In order to assess long-term scenarios, it is necessary to have models and methods able to take into account the effects on shopping mobility and goods restocking, generated by these classes of measures (e.g. relocation of shopping zones). Besides, we have to consider that modifications of shopping attitudes, deriving from changes of demographic and socio-economic characteristics of end consumers, can impact on purchasing behaviour and hence on restocking mobility. This paper discusses a number of issues related to the simulation of medium/long-term scenarios and presents a system of models that consider shopping mobility and restocking jointly. The presented shopping demand models, in combination with urban restocking models, are implemented within a simulation support system named City Logistics Analysis and Simulation Support System and are used to assess the effects on the freight restocking due to demographic and socio-economic variations including some hypotheses on new land-use development governance measures in a medium-size urban area. The main results confirm the modelling goodness and, at the same time, demonstrate that changes in demographic and socio-economic characteristics could cause relevant effects, in particular increasing car use in shopping mobility. The growing e-shopping could limit the negative effects of these changes, but the impacts of home deliveries have to be considered. The relocation of commercial and logistics centres, closer to the residential distribution, could drive a different restocking pattern with a consequent reduction in freight vehicle mobility. Anyway, this reduction is not very relevant and therefore further city logistics measures have to be implemented.
Advanced Trip Planners for Transit Networks: Some Theoretical and Experimental Aspects of Pre-Trip Path Choice ModelingPublished: 21 February 2014 by Springer Nature in Advances in Computer and Computational Sciences
The chapter reports the first results of a research project for the definition of an advanced trip planner for transit networks. The project at the current stage has developed the module to support the user with personalized pre-trip information based on his/her preferences. The first part of the chapter describes the user needs and the logical architecture of the trip planner. The second part deals with the theoretical aspects of the path choice model used to support the path choice set individuation, the path utility calculation and the user preference learning procedure. In order to apply the theoretical framework and to show the benefits of the proposed approach, some experimental results of a test case on the transit system of the metropolitan area of Rome are presented.
Given that few studies have investigated the effects of implementing city logistics measures, this paper focuses on actions implemented in the inner area of Rome in the last 10 years in order to improve both livability and freight distribution, providing insights into the effectiveness of such measures. The analysis covers the famous inner area of the city where the main tourist monuments are located and includes several pedestrianized shopping streets. Evaluation is based on data collected in 1999 and 2008 consisting of traffic counts and interviews with retailers and truck drivers. The implemented measures provided effective in abating through-traffic, in reducing the share of transport on own-account and in increasing the use of less polluting vehicles. Further, the increase in the number of stops per tour, in the average quantity delivered and hence in the average loading factor was revealed. Although all these changes improved the freight transport within the city, some critical issues remain and further measures have to be implemented.
This paper presents a system of models for the estimation of international (import/export) freight flows through a partial share approach. It allows us to simulate attraction, production, distribution and modal split for the estimation of modal Origin-Destination matrices in quantities. Aiming at predicting long term effects for strategic planning, the modelling system has been specified through easy-to-capture variables represented by level-of-service attributes and aggregate socio-economic variables. The calibration was carried out by using a set of available data in Italy that allowed us to consider import/export flows for different freight types given by the aggregation of classes provided by European NST/R classifications.
The paper presents the first results of a research aiming to develop a transit trip planner to support the user with personalized pre-trip information. The first part describes the user needs and the architecture of the system. The second part deals with the modeling framework implemented to provide the best path alternatives from the traveler's utility point of view according to real-time data and personal user preferences. Finally, considerations on operative aspects based on some experimental evidences are presented.
This chapter proposes a general integrated demand modeling system developed within a simulation system to forecast both internal (transportation cost variations) and external (variations of pollution, noise and road accidents) direct effects of city logistics measures. In the first part, the paper considers the shopping and restocking components of urban freight mobility and the relative actor’s choices that can be influenced by city logistics measures. The road simulation system is then considered with its various components, and the demand models are analyzed with particular attention to shopping demand models.
A Model For Simulating Urban Goods Transport and Logistics: The integrated Choice of ho.re.ca. Activity Decision-Making ...Published: 01 June 2013 by Elsevier BV in Procedia - Social and Behavioral Sciences
This paper proposes the advancements of a general model developed by the authors in multi-year research in order to simulate the urban freight transport and logistics. The advancements mainly concern: the modeling framework and calibration. In fact, the previous studies mainly investigated the pull movements of retailers and end consumers, while now both push and pull movements of goods are analyzed and modeled. The proposed analysis refers to choices made by ho.re.ca. (hotel, restaurant, catering) activity decision-making (manager, chief) and final business consumers. Although they are end consumers due to final freight destination or their freight consumption, they have a decisional choice process that can be assumed similar to retailer's one. The new calibration advancements were made on the basis of surveys carried out in the inner zone of Rome where more than 500 truck-drivers were interviewed. Models were specified in order to test new model forms (e.g. nested logit) respect the currently consolidated and commonly used.