This paper focuses on the presentation of an integrated framework based on two advanced strategies, aimed at mitigating the effect of traffic congestion in terms of performance and environmental ...impact. In particular, the paper investigates the “operational benefits” that can be derived from the combination of traffic control (TC) and route guidance (RG) strategies. The framework is based on two modules and integrates a within-day traffic control method and a day-to-day behavioral route choice model. The former module consists of an enhanced traffic control model that can be applied to design traffic signal decision variables, suitable for real-time optimization. The latter designs the information consistently with predictive user reactions to the information itself. The proposed framework is implemented to a highly congested sub-network in the city center of Naples (Italy) and different scenarios are tested and compared. The “do nothing” scenario (current; DN) and the “modeled compliance” (MC) scenario, in which travelers’ reaction to the information (i.e., compliance) is explicitly represented. In order to evaluate the effectiveness of the proposed strategy and the modeling framework, the following analyses are carried out: (i) Network performance analysis; (ii) system convergence and stability analysis, as well as the compliance evolution over time; (iii) and emissions and fuel consumption impact analysis.
Background
This paper compares a hybrid traffic flow model with benchmark macroscopic and microscopic models. The proposed hybrid traffic flow model may be applied considering a mixed traffic flow ...and is based on the combination of the macroscopic cell transmission model and the microscopic cellular automata.
Modelled variables
The hybrid model is compared against three microscopic models, namely the Krauß model, the intelligent driver model and the cellular automata, and against two macroscopic models, the Cell Transmission Model and the Cell Transmission Model with dispersion, respectively. To this end, three main applications were considered: (i) a link with a signalised junction at the end, (ii) a signalised artery, and (iii) a grid network with signalised junctions.
Results
The numerical simulations show that the model provides acceptable results. Especially in terms of travel times, it has similar behaviour to the microscopic model. By contrast, it produces lower values of queue propagation than microscopic models (intrinsically dominated by stochastic phenomena), which are closer to the values shown by the enhanced macroscopic cell transmission model and the cell transmission model with dispersion. The validation of the model regards the analysis of the wave propagation at the boundary region.
•The proposed strategy for network traffic control allows for multi-criteria optimisation of green timings at each single junction and for mono-criterion offsets optimisation.•The embedded mesoscopic ...traffic flow model allows to properly simulate queue and spillback phenomena.•Optimal strategy is obtained through metaheuristics: genetic algorithms, hill climbing.
The paper focuses on Network Traffic Control based on aggregate traffic flow variables, aiming at signal settings which are consistent with within-day traffic flow dynamics. The proposed optimisation strategy is based on two successive steps: the first step refers to each single junction optimisation (green timings), the second to network coordination (offsets). Both of the optimisation problems are solved through meta-heuristic algorithms: the optimisation of green timings is carried out through a multi-criteria Genetic Algorithm whereas offset optimisation is achieved with the mono-criterion Hill Climbing algorithm. To guarantee proper queuing and spillback simulation, an advanced mesoscopic traffic flow model is embedded within the network optimisation method. The adopted mesoscopic traffic flow model also includes link horizontal queue modelling. The results attained through the proposed optimisation framework are compared with those obtained through benchmark tools.
•Stage sequence may greatly affect the performance of a network of signalised junctions.•Scheduled synchronisation optimises stage sequence and lengths and offsets for a junction network.•CENEO is ...the first method available in literature for scheduled synchronisation.•CENEO is an efficient and effective method suitable for large scale application.
One of the most straightforward short term policies to mitigate urban traffic congestion is control through traffic lights at a single junction or network level. Existing approaches for single junction Signal Setting Design (SSD) can be grouped into two classes: Stage-based or Phase-based methods. Both these approaches take the lane marking layouts as exogenous inputs, but lane-based optimisation method may be found in literature, even though for isolated signal-controlled junctions only. The Network Signal Setting Design (NSSD) requires that offsets are introduced; a traffic flow model is also needed to compute total delay. All existing methods for NSSD follow a stage-based approach; these methods do not allow for stage matrix optimisation: it is shown that explicit enumeration of stage sequences is only practicable for very small networks.
This paper focuses on Network Signal Setting Design introducing the so-called scheduled synchronisation that includes green scheduling, green timing and coordination into one optimisation problem. The paper proposes a stage-based method to solve such a problem, as an extension of the synchronisation method and the traffic flow model proposed in Cantarella et al. (2015): first a set of candidate stages is defined for each junction, then the stage sequences, the stage lengths and the offsets are optimised all together. To the authors’ knowledge, no other one-step optimisation method is available in literature for scheduled synchronisation. Results of the proposed method to a small network were compared with those from explicit enumeration of all stage sequences; results for a larger network are also discussed.
► We model a new cruise control system for on-board electronic control units. ► The system adapts itself in real-time and on-demand by means of short driving sessions. ► Full details are modelled to ...produce a suitable, behaviourally consistent and safe cruising. ► The modelling framework has shown great capabilities in reproducing observed driving behaviours. ► The modelling framework has been shown to be simple, effective and robust.
Adaptive Cruise Control systems have been developed and introduced into the consumer market for over a decade. Among these systems, fully-adaptive ones are required to adapt their behaviour not only to traffic conditions but also to drivers’ preferences and attitudes, as well as to the way such preferences change for the same driver in different driving sessions. This would ideally lead towards a system where an on-board electronic control unit can be asked by the driver to calibrate its own parameters while he/she manually drives for a few minutes (learning mode). After calibration, the control unit switches to the running mode where the learned driving style is applied. The learning mode can be activated by any driver of the car, for any driving session and each time he/she wishes to change the current driving behaviour of the cruise control system.
The modelling framework which we propose to implement comprises four layers (sampler, profiler, tutor, performer). The sampler is responsible for human likeness and can be calibrated while in learning mode. Then, while in running mode, it works together with the other modelling layers to implement the logic. This paper presents the overall framework, with particular emphasis on the sampler and the profiler that are explained in full mathematical detail. Specification and calibration of the proposed framework are supported by the observed data, collected by means of an instrumented vehicle. The data are also used to assess the proposed framework, confirming human-like and fully-adaptive characteristics.
The paper aims to provide a further development of traffic control strategies, to propose an enhanced version of two traffic flow models and to integrate these models within an urban traffic control ...framework. Concerning the traffic control method, the synchronisation approach is adopted and three objective functions are considered and compared: two are mono-criterion and the third is multi-criteria. Simulated annealing and multi-objective simulated annealing are adopted as a solution algorithm. In terms of traffic flow representation the approaches analysed are macroscopic cell-based and mesoscopic link-based, both able to model path choice behaviours and vehicle dispersion phenomena. Furthermore, traffic flow prediction is pursued through a Kalman filter and a rolling horizon approach is adopted as a forecasting framework for the optimisation procedure. In order to test the framework and to compare two traffic flow models, a 15-node grid network was considered, including different levels of congestion and demand profiles.
The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized method, which can simultaneously compute the ...network decision variables (i.e., the green timings at each junction and the offset of the traffic light plans of the network). Furthermore, the framework is based on a hybrid traffic flow model operating as a prediction model and plant model in the control procedure. The hybrid traffic flow model combines two sub-models: an aggregate model (i.e., the Cell Transmission Model; CTM) and a disaggregate model (i.e., the Cellular Automata model; CA), using a transition cell to connect them. The whole framework is tested on a signalized arterial, performing several analyses to calibrate the MPC strategy and evaluate the traffic control approach using fixed and adaptive control strategies. All analyses are made in terms of total time spent, network total delay, queue lengths and degree of saturation.
The impact of travel information’s accuracy on route-choice Ben-Elia, Eran; Di Pace, Roberta; Bifulco, Gennaro N. ...
Transportation research. Part C, Emerging technologies,
January 2013, 2013, 2013-1-00, 20130101, Letnik:
26
Journal Article
Recenzirano
► Travellers’ choices are sensitive to the accuracy of travel information in addition to travel time uncertainty. ► A route-choice experiment under three different levels of information accuracy was ...conducted. ► Provided information included descriptive, prescriptive and post-choice experiential information. ► Decreasing accuracy shifts choices from riskier to more reliable routes but also to a useless alternative. ► Prescriptive information has the greatest behavioural impact followed by descriptive and experiential feedback information.
Advanced Travel Information Systems (ATISs) are designed to assist travellers in making better travel choices by providing pre-trip and en-route information such as travel times on the relevant alternatives. Travellers’ choices are likely to be sensitive to the accuracy of the provided information in addition to travel time uncertainty. A route-choice experiment with 36 participants, involving 20 repetitions under three different levels of information accuracy was conducted to investigate the impact of information accuracy. In each experiment respondents had to choose one of three routes (risky, useless and reliable). Provided information included descriptive information about the average estimated travel times for each route, prescriptive information regarding the suggested route and experiential feedback information about the actual travel times on all routes. Aggregate analysis using non-parametric statistics and disaggregate analysis using a mixed logit choice model were applied. The results suggest decreasing accuracy shifts choices mainly from the riskier to the reliable route but also to the useless alternative. Prescriptive information has the largest behavioural impact followed by descriptive and experiential feedback information. Risk attitudes also seem to play a role. The implications for ATIS design and future research are further discussed.
This paper proposes a hybrid traffic flow model able to support the implementation of traffic management strategies in the presence of human-driven and connected vehicles. The model is based on the ...combination of two models: an aggregate model (the cell transmission model) and a disaggregate model (the cellular automata model). The model was tested considering three main layouts, namely a ring-shaped arc, a signalised link, and a grid network with four origins and four destinations, and then calibrated on real data. The model was also applied in the presence of connected vehicles. Our results point out the model's local consistency in terms of wave propagation and its suitability with respect to the benchmark models as well as in the presence of connected vehicles.
It is common opinion that traditional approaches used to interpret and model users’ choice behaviour in innovative contexts may lead to neglecting numerous nonquantitative factors that may affect ...users’ perceptions and behaviours. Indeed, psychological factors, such as attitudes, concerns, and perceptions may play a significant role which should be explicitly modelled. By contrast, collecting psychological factors could be a time and cost consuming activity, and furthermore, real-world applications must rely on theoretical paradigms which are able to easily predict choice/market fractions. The present paper aims to investigate the above-mentioned issues with respect to an innovative automotive technology based on the after-market hybridization of internal combustion engine vehicles. In particular, three main research questions are addressed: (i) whether and how users’ characteristics and attitudes may affect users’ behaviour with respect to new technological (automotive) scenarios (e.g., after-market hybridization kit); (ii) how to better “grasp” users’ attitudes/concerns/perceptions and, in particular, which is the most effective surveying approach to observe users’ attitudes; (iii) to what extent the probability of choosing a new automotive technology is sensitive to attitudes/concerns changes. The choice to install/not install the innovative technology was modelled through a hybrid choice model with latent variables (HCMs), starting from a stated preferences survey in which attitudes were investigated using different types of questioning approaches: direct questioning, indirect questioning, or both approaches. Finally, a comparison with a traditional binomial logit model and a sensitivity analysis was carried out with respect to the instrumental attributes and the attitudes. Obtained results indicate that attitudes are significant in interpreting and predicting users’ behaviour towards the investigated technology and the HCM makes it possible to easily embed psychological factors into a random utility model/framework. Moreover, the explicit simulation of the attitudes allows for a better prediction of users’ choice with respect to the Logit formulation and points out that users’ behaviour may be significantly affected by acting on users’ attitudes.
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