Evaluating the effectiveness of signal timing optimization based on microscopic simulation evaluation

The optimization of the timing parameters of traffic signals provides for efficient operation of traffic along a signalized transportation system. Optimization tools with macroscopic simulation models have been used to determine optimal timing plans. These plans have been, in some cases, evaluated and fine tuned using microscopic simulation tools. A number of studies show inconsistencies between optimization tool results based on macroscopic simulation and the results obtained from microscopic simulation. No attempts have been made to determine the reason behind these inconsistencies. This research investigates whether adjusting the parameters of macroscopic simulation models to correspond to the calibrated microscopic simulation model parameters can reduce said inconsistencies. The adjusted parameters include platoon dispersion model parameters, saturation flow rates, and cruise speeds. The results from this work show that adjusting cruise speeds and saturation flow rates can have significant impacts on improving the optimization/macroscopic simulation results as assessed by microscopic simulation models

Effect of Pulse‐and‐Glide Strategy on Traffic Flow for a Platoon of Mixed Automated and Manually Driven Vehicles

The fuel consumption of ground vehicles is significantly affected by how they are driven. The fuel‐optimized vehicular automation technique can improve fuel economy for the host vehicle, but their effectiveness on a platoon of vehicles is still unknown. This article studies the performance of a well‐known fuel‐optimized vehicle automation strategy, i.e., Pulse‐and‐Glide (PnG) operation, on traffic smoothness and fuel economy in a mixed traffic flow. The mixed traffic flow is assumed to be a single‐lane highway on flat road consisting of both driverless and manually driven vehicles. The driverless vehicles are equipped with fuel economy‐oriented automated controller using the PnG strategy. The manually driven vehicles are simulated using the Intelligent Driver Models (IDM) to mimic the average car‐following behavior of human drivers in naturalistic traffics. A series of simulations are conducted with three scenarios, i.e., a single car, a car section, and a car platoon. The simulation results show that the PnG strategy can significantly improve the fuel economy of individual vehicles. For traffic flows, the fuel economy and traffic smoothness vary significantly under the PnG strategy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115907/1/mice12168.pd

A simulator of intelligent transportation systems

This paper presents the most recent developments of the Simulator of Intelligent Transportation Systems (SITS). The SITS is based on a microscopic simulation approach to reproduce real traffic conditions in an urban or non-urban network. The program provides a detailed modelling of the traffic network, distinguishing between different types of vehicles and drivers and considering a wide range of net-work geometries. In order to analyse the quality of the microscopic traffic simulator SITS a benchmark test is per-formed.N/

Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamic

Accounting for midblock pedestrian activity in the HCM 2010 urban street segment analysis

The Urban Street segment analysis Chapter of the 2010 Highway Capacity Manual (HCM 2010) provides a methodology for analyzing automobile performance on signalized roadway segments within an urban roadway network. The methodology involves applying a platoon dispersion model to: a) predict the vehicle arrival flow profiles at a downstream signalized intersection; b) use the predicted arrivals to compute the proportion of vehicle arrivals on green; and c) subsequently estimate the delay, travel speed and Level of Service (LOS) under which the segment operates. Vehicles arriving during the red interval at a signalized intersection generally accumulate and form a platoon. When the signal turns green, the platoon of vehicles is discharged from the upstream intersection to the downstream intersection. As vehicle speeds fluctuate, the platoon will disperse before it arrives at the downstream intersection. This is called Platoon dispersion. Notwithstanding its importance and application in evaluating the performance of urban roadway segments, the predictive ability of the HCM 2010 platoon dispersion model under friction and non-friction traffic conditions has not been evaluated. Friction traffic conditions include midblock pedestrian activity, on-street parking activity, and medium to high truck volume. Furthermore, one key limitation of the methodology for evaluating automobile performance on urban street segment is that it does not account for the delay incurred by platoon vehicles due to pedestrian activity at midblock (or mid-segment) crosswalks Therefore, the first objective of this research is to evaluate the predictive performance of the HCM 2010 platoon dispersion model under friction and non-friction traffic conditions using field data collected at four urban street segments. The second and primary objective is to develop an integrated deterministic-probabilistic (stochastic) model that estimates the delay incurred by platoon vehicles due to midblock pedestrian activity on urban street segments. Results of the statistical model evaluation show statistically significant difference between the observed and predicted proportion of arrivals on green under traffic. The results, however, show no statistically significant difference between the observed and predicted proportion of vehicle arrivals on under no traffic friction condition. In addition, the developed delay model was validated using field measured data. Results of the statistical validation show the developed midblock delay model performs well when compared to delays measured in the field. Sensitivity analysis is also performed to study the relationship between midblock delay and certain model parameters and variables. The model parameters are increased and decreased by 50% of their baseline values

A mesoscopic whole link continuous vehicle bunch model for multiclass traffic flow simulation on motorway networks

Modeling of heterogeneous driver behaviour is vital to understanding of dynamic traffic phenomenon taking place on motorway networks. In this research, we present a mesoscopic whole link continuous vehicle bunch model for multiclass traffic flow simulation on motorway networks. Two main attributes of traffic flow classification have been used are: (i) vehicle type, specifying in turn a vehicle length and, together with type of a preceding vehicle, time headway; and, (ii) desired speed, defining together with the speeds of the neighbouring vehicles, the vehicle acceleration/deceleration mode. It is assumed that vehicles in uncongested to moderate congested flow move in bunches dividing the drivers into the two main groups: (i) independent “free” drivers which usually manifest themselves as leaders of bunches; and, (ii) followers, or drivers which adapt their speed to the leader’s speed and follow each other at constrained headways specified by predecessor/successor pairs. The model proposes a solution to arbitrary traffic queries involving a motion in bunches having various speed and size by assuming the rate of driver arrivals follows semi-Poisson distribution and proportion of free drivers is predefined. The solution, assuming limited overtaking possibilities for all drivers, involves formation of longer queue behind bunches moving with slower speed and transformation of some of the “leaders” into “followers” because of adjustment their speed to the speed of the preceding slow-moving bunches. The present solution considers both stochastic and deterministic features of traffic flow and, therefore, may be easily extended to a specific uncertainty level

A review of traffic simulation software

Computer simulation of tra c is a widely used method in research of tra c modelling, planning and development of tra c networks and systems. Vehicular tra c systems are of growing concern and interest globally and modelling arbitrarily complex tra c systems is a hard problem. In this article we review some of the tra c simulation software applications, their features and characteristics as well as the issues these applications face. Additionally, we introduce some algorithmic ideas, underpinning data structural approaches and quanti able metrics that can be applied to simulated model systems

2nd Symposium on Management of Future motorway and urban Traffic Systems (MFTS 2018): Booklet of abstracts: Ispra, 11-12 June 2018

The Symposium focuses on future traffic management systems, covering the subjects of traffic control, estimation, and modelling of motorway and urban networks, with particular emphasis on the presence of advanced vehicle communication and automation technologies. As connectivity and automation are being progressively introduced in our transport and mobility systems, there is indeed a growing need to understand the implications and opportunities for an enhanced traffic management as well as to identify innovative ways and tools to optimise traffic efficiency. In particular the debate on centralised versus decentralised traffic management in the presence of connected and automated vehicles has started attracting the attention of the research community. In this context, the Symposium provides a remarkable opportunity to share novel ideas and discuss future research directions.JRC.C.4-Sustainable Transpor