Showing papers in "Transportation research procedia in 2015"

Modeling Lane-Changing Behavior in a Connected Environment: A Game Theory Approach

Abstract: Vehicle-to-Vehicle communications provide the opportunity to create an internet of cars through the recent advances in communication technologies, processing power, and sensing technologies. A connected vehicle receives real-time information from surrounding vehicles; such information can improve drivers’ awareness about their surrounding traffic condition and lead to safer and more efficient driving maneuvers. Lane-changing behavior,as one of the most challenging driving maneuvers to understand and to predict, and a major source of congestion and collisions, can benefit from this additional information.This paper presents a lane-changing model based on a game-theoretical approach that endogenously accounts for the flow of information in a connected vehicular environment.A calibration approach based on the method of simulated moments is presented and a simplified version of the proposed framework is calibrated against Next Generation Simulation (NGSIM) data. The prediction capability of the simplified model is validated. It is concluded the presented framework is capable of predicting lane-changing behavior with limitations that still need to be addressed. Finally, a simulation framework based on the fictitious play is proposed. The simulation results revealed that the presented lane-changing model provides a greater level of realism than a basic gap-acceptance model.

Automated Vehicles and the Rethinking of Mobility and Cities

Abstract: The project CityMobil2 has carried out a forward-looking exercise to investigate alternative cybermobility scenarios, including both niche and large-market innovations, and their impacts on European cities and their transport systems. The paper describes the current status of and main trends in automated vehicles, a preliminary vision of the future city with mobility supported mainly by automated vehicles, and freight distribution. The expected positive impacts derive from the development of car sharing, the reduction of space required for parking vehicles, the possibilities for older people or those with disabilities to use cars, the enhancement of safety, and the improvement of efficiency of the transport system.

Spatial and temporal characterization of travel patterns in a traffic network using vehicle trajectories

Abstract: This paper presents a trajectory clustering method to discover spatial and temporal travel patterns in a traffic network The study focuses on identifying spatially distinct traffic flow groups using trajectory clustering and investigating temporal traffic patterns of each spatial group The main contribution of this paper is the development of a systematic framework for clustering and classifying vehicle trajectory data, which does not require a pre-processing step known as map-matching and directly applies to trajectory data without requiring the information on the underlying road network The framework consists of four steps: similarity measurement, trajectory clustering, generation of cluster representative subsequences, and trajectory classification First, we propose the use of the Longest Common Subsequence (LCS) between two vehicle trajectories as their similarity measure, assuming that the extent to which vehicles’ routes overlap indicates the level of closeness and relatedness as well as potential interactions between these vehicles We then extend a density-based clustering algorithm, DBSCAN, to incorporate the LCS-based distance in our trajectory clustering problem The output of the proposed clustering approach is a few spatially distinct traffic stream clusters, which together provide an informative and succinct representation of major network traffic streams Next, we introduce the notion of cluster representative subsequence (CRS), which reflects dense road segments shared by trajectories belonging to a given traffic stream cluster, and present the procedure of generating a set of CRSs by merging the pairwise LCSs via hierarchical agglomerative clustering The CRSs are then used in the trajectory classification step to measure the similarity between a new trajectory and a cluster The proposed framework is demonstrated using actual vehicle trajectory data collected from New York City, USA A simple experiment was performed to illustrate the use of the proposed spatial traffic stream clustering in application areas such as network-level traffic flow pattern analysis and travel time reliability analysis

Railway Infrastructure Maintenance - A Survey of Planning Problems and Conducted Research

Abstract: Railway infrastructure maintenance consumes very large budgets, is complicated to organize and has numerous challenging planning problems. Specifically, the coordination with train traffic operatio ...

On Microscopic Modelling of Adaptive Cruise Control Systems

Abstract: The Adaptive Cruise Control (ACC) system, is one of the emerging vehicle technologies that has already been deployed in the market. Although it was designed mainly to enhance driver comfort and passengers’ safety, it also affects the dynamics of traffic flow. For this reason, a strong research interest in the field of modelling and simulation of ACC-equipped vehicles has been increasingly observed in the last years. In this work, previous modelling efforts reported in the literature are reviewed, and some critical aspects to be considered when designing or simulating such systems are discussed. Moreover, the integration of ACC-equipped vehicle simulation in the commercial traffic simulator Aimsun is described; this is subsequently used to run simulations for different penetration rates of ACC-equipped vehicles, different desired time-gap settings and different networks, to assess their impact on traffic flow characteristics.

Predicting Travel Mode of Individuals by Machine Learning

Abstract: Travel mode choice prediction of individuals is important in planning new transportation projects. In this paper, we present four machine learning methods namely artificial neural net-MLP, artificial neural net-RBF, multinomial logistic regression, and support vector machines, for predicting travel mode of individuals in city of Luxembourg. The presented methods use individuals’ characteristics, transport mode specifications and data related to places of work and residence. The dataset analyzed comes from a national survey. It contains information on the daily mobility (e.g., from home to work) of individuals who either live or work in Luxembourg. We extracted individual characteristics to relate daily movements (journeys between home and work, in particular) to the characteristics of working individuals. We used the information about public transportation and some geographical location of the residential and work places. We compare the rates of successful prediction obtained by neural networks and several alternative approaches for predicting the travel mode choice using cross-validation. The results show that the artificial neural networks perform better compared to other alternatives. Our analysis can be used to support management decision-making and build predictions under uncertainty related to changes in people's behavior, economic context or environment and transportation infrastructure.

The Netherlands Mobility Panel: an innovative design approach for web-based longitudinal travel data collection

Abstract: This paper introduces a new household panel – ‘The Netherlands Mobility Panel’ (in Dutch: MobiliteitsPanel Nederland MPN). To collect trip and trip stage data for the MPN, we developed a state-of-the-art travel diary, the design philosophy of which will be explained in this paper. Further, the initial assessment results based on the first data collected autumn 2013 is presented, providing insights into the benefits of the travel diary design. We explain how differences in data quality relate to differences in diary design, diary layout, and diary content.

Controller Design for Gating Traffic Control in Presence of Time-delay in Urban Road Networks

Abstract: Recent studies demonstrated the efficiency of feedback-based gating control in mitigating congestion in urban networks by exploiting the notion of macroscopic or network fundamental diagram (MFD or NFD). The employed feedback regulator of proportional-integral(PI)-type targets an operating NFD point of maximum throughput to enhance the mobility in the urban road network during the peak period, under saturated traffic conditions. In previous studies, gating was applied directly at the border of the protected network (PN), i.e. the network part to be protected from over-saturation. In this work, the recently developed feedback-based gating concept is applied at junctions located further upstream of the PN. This induces a time-delay, which corresponds to the travel time needed for gated vehicles to approach the PN. The resulting extended feedback control problem can be also tackled by use of a PI-type regulator, albeit with different gain values compared to the case without time-delay. Detailed procedures regarding the appropriate design of related feedback regulators are provided. In addition, the developed concepts are also exploited to test and compare (for the first time in the related technical literature) the impact of increased sample times on the gating performance.A large part of the Chania, Greece, urban network, modelled in a microscopic simulation environment under realistic traffic conditions, is used as test-bed in this study. The reported results demonstrate a stable and efficient behaviour and improved mobility of the overall network in terms of mean speed and travel time.

Comparison of Travel Diaries Generated from Smartphone Data and Dedicated GPS Devices

Abstract: This paper provides further insight into the usefulness of smartphones and dedicated GPS devices for collecting current travel survey data. GPS and accelerometer time series for 33 European research project PEACOX study participants are available for analysis; these were tracked simultaneously with smartphones and dedicated devices for 8 weeks. Meaningful diaries can be extracted from both data sources. However, if high resolution data is needed, results suggest that dedicated GPS devices are still relevant; they have no battery issues, meaning that more data is recorded and that data quality is more stable.

Automatic trip and mode detection with MoveSmarter: first results from the Dutch Mobile Mobility Panel

Abstract: This paper describes the performance of a smartphone app called MoveSmarter to automatically detect departure and arrival times, trip origins and destinations, transport modes, and travel purposes. The app is used in a three-year smartphone-based prompted-recall panel survey in which about 600 smartphone and non-smartphone owners participated and over 18,000 validated trips were collected during two weeks. MoveSmarter is concluded to be a promising alternative or addition to traditional trip diaries, reducing respondent burden and increasing accuracy of measurement, but there is room to improve trip and mode detection rates and the efficiency of battery consumption.

Stochastic Approximations for the Macroscopic Fundamental Diagram of Urban Networks

Abstract: This paper proposes a theory for estimating the Macroscopic Fundamental Diagram (MFD) on inhomogeneous corridors and networks using probabilistic methods. By exploiting a symmetry property of the stochastic MFD, whereby it exhibits identical probability distributions in free-flow and congestion, it is found that the network MFD depends mainly on two dimensionless parameters: the mean block length to green ratio and the mean red to green ratio. The theory is validated with an exact traffic simulation and with the empirical data from the city of Yokohama. It is also shown that the effect of buses can be approximated with the proposed theory by accounting for their effect in the red to green ratio parameter.

A model of bus bunching under reliability-based passenger arrival patterns

Abstract: If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustrate when bus bunching might occur. We show that non-uniform arrival patterns can significantly influence the bus bunching process. With case studies we find that, even without exogenous delay, bunching can arise when the boarding rate is insufficient given the level of overall demand. Further, in case of exogenous delay, non-uniform arrivals can either worsen or improve the bunching conditions, depending on the level of delay. We conclude that therefore such effects should be considered when service control measures are discussed.

Robust Constrained Control of Uncertain Macroscopic Fundamental Diagram Networks

Abstract: This paper considers modeling and control of uncertain Macroscopic Fundamental Diagram (MFD) systems for multiple-region networks. First, the nonlinear vehicle conservation equations based on MFD dynamics, presented in earlier publications, are transformed to linear equations with parameter uncertainties. The parameter uncertainties include the destination decomposition fractions, that are difficult to estimate in reality. Then, the uncertain linear model is utilized to design a robust feedback controller by an interpolation-based approach. This approach (i) guarantees robustness against all parameter uncertainties, (ii) handle control and state constraints, and (iii) present a computationally cheap solution. The main idea is to interpolate between (i) a stabilizing outer controller that respects the control and state constraints, and (ii) an inner robustly stable controller designed by any method. The robust control is further challenged to deal with different relative locations of reference accumulation points on the MFD diagrams. Numerical results for a two-region system show that the uncertain linear model can replace the nonlinear model for modeling and control. Moreover, the robust control law is presented as implicit and explicit solutions, where in the implicit case one linear programming (LP) problem is solved at each time instant, while in the explicit case, the control law is shown as a piecewise affine function of state. Finally, a comparison between the interpolating controller and other controllers in the literature is carried out. The results demonstrate the performance advantages from applying the robust interpolating controller.

Incident Detection Methods Using Probe Vehicles with On-board GPS Equipment

Abstract: Mobile communication instruments have made detecting traffic incidents possible by using floating traffic data This paper studies the properties of traffic flow dynamics during incidents and proposes incident detection methods using floating data collected by probe vehicles equipped with on-board global positioning system (GPS) equipment The proposed algorithms predict the time and location of traffic congestion caused by an incident The detection rate and false rate of the models are examined using a traffic flow simulator, and the performance measures of the proposed methods are compared with those of previous methods

Cost-benefit Analysis (CBA), or Multi-criteria Decision-making (MCDM) or Both: Politicians’ Perspective in Transport Policy Appraisal

Abstract: The scientific literature frequently discusses questions if cost-benefit analysis (CBA) or multi-criteria decision-making (MCDM) is the appropriate appraisal tool in transport policy-making, or a combination of both. Hardly any literature exists on the opinions of real transport policy decision-makers about appraisal tools such as CBA or MCDM (or both) which are actually supposed to help them. The aim of this paper is to discuss from a politicians’ perspective how a useful transport policy appraisal tool might look like. Twenty-one Dutch transport politicians were interviewed on their views on CBA. The results show that they use CBA but in a non-decisive manner and they find the aggregate outcome (the composite result) of CBAs pretentious. They seem especially interested in appraisal tools which show clearly to them the political important trade-offs of a transport policy. This paper proposes a possible approach for such a trade-off information sheet using both CBA and MCDM.

Application of AHP and ELECTRE III/IV methods to multiple level, multiple criteria evaluation of urban transportation projects

Abstract: In this paper the authors carry out a multiple level, multiple criteria evaluation of 18 urban transportation projects. At each level of the hierarchical decision problem different multiple criteria ranking sub-problems have been structured and solved with the application of AHP method, ELECTRE III/IV method and their combination (AHP/ELECTRE III/IV). Thus, the computational phase allowed for testing the above mentioned multiple criteria ranking methods, i. e.: AHP and ELECTRE III/IV and analyzing their suitability for performing a multiple level, multiple criteria evaluation of transportation projects. Due to axiomatic differences between methods alternative aggregation formulas of the generated rankings by ELECTRE III/IV and AHP methods have been proposed. A multi - aspect discussion and comparison of generated results and applied methods have been presented.

Optimal transit service atop ring-radial and grid street networks: A continuum approximation design method and comparisons

Abstract: Two continuum approximation (CA) optimization models are formulated to design city-wide transit systems at minimum cost. Transit routes are assumed to lie atop a city's street network. Model 1 assumes that the city streets are laid out in ring-radial fashion. Model 2 assumes that the city streets form a grid. Both models can furnish hybrid designs, which exhibit intersecting routes in a city's central (downtown) district and only radial branching routes in the periphery. Model 1 allows the service frequency and the route spacing at a location to vary arbitrarily with the location's distance from the center. Model 2 also allows such variation but in the periphery only. The paper shows how to solve these CA optimization problems numerically, and how the numerical results can be used to design actual systems. A wide range of scenarios is analyzed in this way. It is found among other things that in all cases and for both models: (i) the optimal headways and spacings in the periphery increase with the distance from the center; and (ii) at the boundary between the central district and the periphery both, the optimal service frequency and line spacing for radial lines decrease abruptly in the outbound direction. On the other hand Model 1 is distinguished from Model 2 in that the former produces in all cases: (i) a much smaller central district, and (ii) a high frequency circular line on the outer edge of the central district. Parametric tests with all the scenarios further show that Model 1 is consistently more favorable to transit than Model 2. Cost differences between the two designs are typically between 9% and 13%, but can top 21.5%. This is attributed to the manner in which ring-radial networks naturally concentrate passenger's shortest paths, and to the economies of demand concentration that transit exhibits. Thus, it appears that ring-radial street networks are better for transit than grids. In order to illustrate the robustness of the CA design procedure to irregularities in real street networks, the results for all the test problems were then used to design and evaluate transit systems on networks of the “wrong” type – grid networks were outfilled with transit systems designed with Model 1 and ring-radial networks designed with Model 2. Cost increased on average by a little 2.7%. The magnitude of these deviations suggests that the proposed CA procedures can be used to design transit systems over real street networks when they are not too different from the ideal and that the resulting costs should usually be very close to those predicted.

Continuum Theory for Pedestrian Traffic Flow: Local Route Choice Modelling and its Implications

Abstract: This contribution puts forward a novel multi-class continuum model that captures some of the key dynamic features of pedestrian flows. It considers route choice behaviour on both the strategic (pre-trip) and tactical (en-route) level. To achieve this, we put forward a class-specific equilibrium direction relation of the pedestrians, which is governed by two parts: one part describing the global route choice, which is pre-determined based on the expectations of the pedestrians, and one part describing the local route choice, which is a density-gradient dependent term that reflects local adaptations based on prevailing flow conditions. Including the local route choice term in the multi-class model causes first of all dispersion of the flow: pedestrians will move away from high density areas in order to reduce their overall walking costs. Second of all, for the crossing flow and bi-directional flow cases, local route choice causes well known self-organised patterns to emerge (i.e. diagonal stripes and bi-directional lanes). We study under which demand conditions self-organisation occurs and fails, as well as what the impact is of the choices of the different model parameters. In particular, the differences in the weights reflecting the impact of the own and the other classes appear to have a very strong impact on the self-organisation process.

A Systematic Review of Multi-criteria Decision-making Applications in Reverse Logistics

Abstract: Multi-criteria decision-making (MCDM) methods have been applied to various reverse logistics problems. In order to develop a reliable knowledge base through accumulating knowledge from previous studies, we conduct a systematic review of the applications of different MCDM methods to different reverse logistics problems. We found 80 relevant papers published in scientist journals, which are application of different MCDM methods to different reverse logistics problems. We classify the literature based on two dimensions problem context and methodology. The results show that recycling and AHP are the most researched problem and methodology respectively. We finally suggest some future research directions with respect to problem context and methodology.

A Robust, Tactic-Based, Real-Time Framework for Public- Transport Transfer Synchronization

Abstract: Missed transfers affect public transport (PT) operations by increasing passenger's waiting and travel times and frustration. Because of the stochastic and uncertain nature of PT systems, synchronized transfers do not always materialize. This work proposes a new mathematical programming model to minimize total passenger travel time and maximize direct (without waiting) transfers. The model consists of four policies built on a combination of three tactics: holding, skip-stops, and short-turn, the last applied, for the first time, as a real-time control action. The concept is implemented in two steps: optimization and simulation. An agent-based simulation framework is used to represent real-life scenarios, generate random input data, and validate the optimization results. In order to assess the robustness of this framework, a wide range of schedule-deviation scenarios are defined using efficient algorithms for solving the control models within a rolling horizon structure. A case study of the Auckland, New Zealand, PT system is described for assessing the methodology developed. The results show a 4.7% reduction in total passenger travel time and a more than 150% increase in direct transfers. The best impressive results are attained under short headway operations.

Workshop Synthesis: Stated Preference Surveys and Experimental Design, an Audit of the Journey so far and Future Research Perspectives

Abstract: This paper is a synthesis of the discussions and ideas that were generated during the workshop on “Stated preference surveys and experimental design” at the 2014 Travel Survey Methods Conference in Leura (Australia). The workshop addressed the challenges related to the design and implementation of stated preference surveys as a way to capture richer behavioural information on the preferences of individuals and groups. The discussion began by reviewing the current state of stated preference surveys and whether and what we have been doing correctly. We then analysed the areas where improvements are still needed, how we can achieve them, and some pros and cons of each improvement.

Parking space management via dynamic performance-based pricing

Abstract: In congested urban areas, it remains a pressing challenge to reduce unnecessary vehicle circling for parking while at the same time maximize parking space utilization. In observance of new information technologies that have become readily accessible to drivers and parking agencies, we develop a dynamic non-cooperative bi-level model (i.e. Stackelberg leader-follower game) to set parking prices in real-time for effective parking access and space utilization. The model is expected to fit into an integrated parking pricing and management system, where parking reservations and transactions are facilitated by sensing and informatics infrastructures, that ensures the availability of convenient spaces at equilibrium market prices. It is shown with numerical examples that the proposed dynamic parking pricing model has the potential to virtually eliminate vehicle circling for parking, which results in significant reduction in adverse socioeconomic externalities such as traffic congestion and emissions.

An Analysis of Bicycle Travel Speed and Disturbances on Off-street and On-street Facilities☆

Abstract: For transport planners and land use practitioners, many are the qualitative guidelines provided regarding the location and quality of separated bicycle facilities. When separated bicycle facilities are poorly designed or placed in less than optimum locations, their intended use is less than anticipated. An interesting element in the evaluation of bicycle facilities that have received less attention revolve around the disturbance due to the presence of other users on cyclists way. Other users consists in cyclists and pedestrians for off-street bicycle facilities, and motorized vehicles on the roadway. This study focuses on quantifying the role of disturbances encountered on separated cycling facilities, compared to disturbances from cycling mixed with traffic, assuming cyclists speed as a performance measure and analysing the cyclist speed reductions from different types of disturbances. Collecting data on three segments of Bologna's cycling network (Italy), the authors measured the frequency, type, and speed reduction attributed to different types of disturbances. The data collected shows that pedestrian disturbances on the separated facility are highly frequent but associated with moderate speed reductions, while disturbances in the mixed traffic environment can be relatively fewer but have more severe speed reductions. Moreover, the authors results suggest that design elements of separated facilities can play a role in affecting the frequency, type, and severity of disturbances. This work helps lay the foundation for outlining the existing relationship between bicycle travel speeds and non stationary disturbances.

A two-stage approach to modeling vacant taxi movements

Abstract: In this paper, a two-stage modeling approach is proposed to predict vacant taxi movements in searching for customers. The taxi movement problem is formulated into a two-stage model that consists of two sub-models, namely the first and second stage sub-models. The first stage sub-model estimates the zone choice of vacant taxi drivers for customer-search and the second stage sub-model determines the circulation time and distance of vacant taxi drivers in each zone by capturing their local customer-search decisions in a cell-based network within the zone chosen in the first stage sub-model. These two sub-models are designed to influence each other, and hence an iterative solution procedure is introduced to solve for a convergent solution. The modeling concept, advantages, and applications are illustrated by the global positioning system data of 460 Hong Kong urban taxis. The results demonstrate that the proposed model formulation offers a great improvement in terms of root mean square error as compared with the existing taxi customer-search models, and show the model capabilities of predicting the changes in vacant taxi trip distributions with respect to the variations in the fleet size and fare. Potential taxi policies are investigated and discussed according to the findings to provide insights in managing the Hong Kong taxi market.

A Comprehensive Framework for Measuring Performance in a Third-party Logistics Provider

Abstract: Today, Third-Party Logistics Providers (3PL) face a great pressure in order to meet their clients’ needs: customers demand a high level of time and place value for their deliveries, at lower prices, making the last mile activity not only a challenge whilst meeting the clients’ requirements but likewise in managing the profitability and the financial balance of the operation. In order to meet the logistics’ operation efficiency, several 3PL monitor their activity assisted by a variety of ex-post systems of performance indicators that assess the quality and efficiency of the logistic process. However, most of the time 3PL do not fully exploit the potentiality of those performance systems. The objective of this paper is to provide a comprehensive and innovative performance measurement framework for a Third-Party Logistics Provider, transferable for other stakeholders. The framework is supported in a thorough revision of the existing literature regarding performance indicators systems, with particular significance in the field of logistics and freight transport. The rich variety of logistics performance indicators arrays frequently focus on a specific domain or follow a typical framework which includes metrics for cost and asset management, customer service, productivity and quality. In order to meet the specifics of a 3PL, the authors believe that a more detailed framework would be beneficial. The framework the authors propose is organized in three levels: the activities dimension (e.g. transport, warehousing, and customer service), the decision level dimension (operational, tactical and strategic) and the different actors dimension (e.g. carriers, 3PL and consolidation centers). A case study of Urbanos, a Portuguese 3PL firm, was used to validate the proposed framework.

W-SPSA in Practice: Approximation of Weight Matrices and Calibration of Traffic Simulation Models

Abstract: The development and calibration of complex traffic models demands parsimonious techniques, because such models often involve hundreds of thousands of unknown parameters. The Weighted Simultaneous Perturbation Stochastic Approximation (W-SPSA) algorithm has been proven more efficient than its predecessor SPSA (Spall, 1998), particularly in situations where the correlation structure of the variables is not homogeneous. This is crucial in traffic simulation models where effectively some variables (e.g. readings from certain sensors) are strongly correlated, both in time and space, with some other variables (e.g. certain OD flows). In situations with reasonably sized traffic networks, the difference is relevant considering computational constraints. However, W-SPSA relies on determining a proper weight matrix (W) that represents those correlations, and such a process has been so far an open problem, and only heuristic approaches to obtain it have been considered. This paper presents W-SPSA in a formally comprehensive way, where effectively SPSA becomes an instance of W-SPSA, and explores alternative approaches for determining the matrix W. The authors demonstrate that, relying on a few simplifications that marginally affect the final solution, the authors can obtain W matrices that considerably outperform SPSA. The authors analyse the performance of the proposed algorithm in two applications in motorway networks in Singapore and Portugal, using a dynamic traffic assignment model and a microscopic traffic simulator, respectively.

Adaptive Group-based Signal Control by Reinforcement Learning☆

Abstract: Group-based signal control is one of the most prevalent control schemes in the European countries. The major advantage of group-based control is its capability in providing flexible phase structures. The current group-based control systems are usually implemented with rather simple timing logics, e.g. vehicle actuated logic. However, such a timing logic is not sufficient to respond to the traffic environment whose inputs, i.e. traffic demands, dynamically change over time. Therefore, the primary objective of this paper is to formulate the existing group-based signal controller as a multi-agent system. The proposed signal control system is capable of making intelligent timing decisions by utilizing machine learning techniques. In this regard, reinforcement learning is a potential solution because of its self-learning properties in a dynamic environment. This paper, thus, proposes an adaptive signal control system, enabled by a reinforcement learning algorithm, in the context of group-based phasing technique. Two different learning algorithms, Q-learning and SARSA, have been investigated and tested on a four-legged intersection. The experiments are carried out by means of an open-source traffic simulation tool, SUMO. Performances on traffic mobility of the adaptive group- based signal control systems are compared against those of a well-established group-based fixed time control system. In the testbed experiments, simulation results reveal that the learning-based adaptive signal controller outperforms group-based fixed time signal controller with regards to the improvements in traffic mobility efficiency. In addition, SARSA learning is a more suitable implementation for the proposed adaptive group-based signal control system compared to the Q-learning approach.

Modeling of shared space with multi-modal traffic using a multi-layer social force approach

Abstract: In the field of traffic road design, the shared space approach aims to develop roads from mere traffic infrastructures to public spaces, compelling higher interaction between road users. In this paper we develop the fundamentals for a micro-simulation tool based on the Social Force Model, to represent the motion of road users in such layouts. Working with the observed behavior of users in a pedestrian-friendly intersection in the city of Braunschweig (D), a multi-layer structured model is developed, in which each layer is designated to handle different situations, from free-flow movements to user interactions in crowded situations. Visibility graphs and clothoid estimations are used for designing trajectories of road users for the free flow movement. Furthermore, an enhancement of the classical Social Force Model is provided in order to model long-range collision avoidance behavior. Finally, the enhanced simulation framework is validated by two observed scenarios, which include various conflicts between pedestrians and cars.

Stop Detection in Smartphone-based Travel Surveys

Abstract: Future Mobility Sensing (FMS) is a smartphone-based travel survey system that employs a web-based prompted-recall interaction to correct automatically inferred information. A key component of FMS is a stop detection algorithm that derives the users’ activity locations and times based on the raw data collected by their phones. Output of this algorithm is presented in the Activity Diary for the users to validate, and its accuracy has a significant impact on user burden. In this paper, we present FMS’ stop detection algorithm and its performance during testing by volunteers and public users during a large-scale field test.

Short-term Strategies for Stochastic Inventory Routing in Bike Sharing Systems

Abstract: Bike sharing systems (BSS) provide individual and eco-friendly urban mobility and are implemented in a growing number of cities. In BSS, customers can rent and return bikes spontaneously at stations and at every time of the day. To allow a reliable usage, system operators have to enable a sufficient number of bikes and empty bike racks at each station. Therefore, system operators use a set of vehicles to relocates bikes between stations. The according routing can be derived solving an inventory routing problem (IRP). For planning, operators can draw on expected customer trips generally following specific daytime patterns. Nevertheless, a significant amount of rentals and returns occur unpredictably and spontaneously forcing immediate adaptions of the routes. In this paper, we define the stochastic IRP for BSS and present a short-term relocation strategy (STR). A STR defines priority stations regarding their urgency that have to be rebalanced. In a real world case study, we compare STR to a long-term relocation strategy (LTR) using given target fill levels. STR outperforms LTR significantly leading to suitable service levels.