An optimization method for sustainable traffic control in urban areas

The optimization of traffic signalization in urban areas is formulated as a problem of finding the cycle length, the green times and the offset of traffic signals that minimize an objective function of performance indices. Typical approaches to this optimization problem include the maximization of traffic throughput or the minimization of vehicles’ delays, number of stops, fuel consumption, etc. Dynamic Traffic Assignment (DTA) models are widely used for online and offline applications for efficient deployment of traffic control strategies and the evaluation of traffic management schemes and policies. We propose an optimization method for combining dynamic traffic assignment and network control by minimizing the risk of potential loss induced to travelers by exceeding their budgeted travel time as a result of deployed traffic signal settings, using the Conditional Value-at-Risk model. The proposed methodology can be easily implemented by researchers or practitioners to evaluate their alternative strategies and aid them to choose the alternative with less potential risk. The traffic signal optimization procedure is implemented in TRANSYT-7F and the dynamic propagation and route choice of vehicles is simulated with a mesoscopic dynamic traffic assignment tool (DTALite) with fixed temporal demand and network characteristics. The proposed approach is applied to a reference test network used by many researchers for verification purposes. Numerical experiments provide evidence of the advantages of this optimization method with respect to conventional optimization techniques. The overall benefit to the performance of the network is evaluated with a Conditional Value-at-Risk Analysis where the optimal solution is the one presenting the least risk for ‘guaranteed’ total travel times.     

A modified reinforcement learning algorithm for solving coordinated signalized networks

This study proposes Reinforcement Learning (RL) based algorithm for finding optimum signal timings in Coordinated Signalized Networks (CSN) for fixed set of link flows. For this purpose, MOdified REinforcement Learning algorithm with TRANSYT-7F (MORELTRANS) model is proposed by way of combining RL algorithm and TRANSYT-7F. The modified RL differs from other RL algorithms since it takes advantage of the best solution obtained from the previous learning episode by generating a sub-environment at each learning episode as the same size of original environment. On the other hand, TRANSYT-7F traffic model is used in order to determine network performance index, namely disutility index. Numerical application is conducted on medium sized coordinated signalized road network. Results indicated that the MORELTRANS produced slightly better results than the GA in signal timing optimization in terms of objective function value while it outperformed than the HC. In order to show the capability of the proposed model for heavy demand condition, two cases in which link flows are increased by 20% and 50% with respect to the base case are considered. It is found that the MORELTRANS is able to reach good solutions for signal timing optimization even if demand became increased.     

Safer signalized junction design and self-optimizing control

The UK Transport Research Laboratory has long had a Worldwide reputation for contributions to the field of traffic signal control, especially as originators of the TRANSYT and SCOOT signal coordination methods. This article describes some less widely known work. Accident risk at urban junctions and on road links between them is related to a wide variety of factors including: traffic and pedestrian flows, signal control parameters, geometry, and other layout features. Comprehensive studies have derived, and are continuing to derive, quantitative risk relationships for use in off-line software. Those for individual signalized cross-roads have already been incorporated in the TRL's program OSCADY to assist junction design. Now, an area-wide safety model incorporating the CONTRAM traffic assignment program is being actively developed to provide a tool for evaluation of network traffic management schemes. For on-line signal control at individual junctions, the MOVA system has been developed to provide a delay-minimizing or capacity-maximizing control logic as appropriate. ‘Before and after’ comparisons with the UK's previous fully vehicle-actuated signal system are presented, including both delay and safety aspects.     

Dynamic network traffic control

This study developed a dynamic traffic control formulation designated as dynamic intersection signal control optimization (DISCO). Traffic in DISCO is modeled after the cell-transmission model (CTM), which is a convergent numerical approximation to the hydrodynamic model of traffic flow. It considers the entire fundamental diagram and captures traffic phenomena such as shockwaves and queue dynamics. As a dynamic approach, the formulation derives dynamic timing plans for time-variant traffic patterns. We solved DISCO based on a genetic algorithm (GA) approach and applied it to a traffic black spot in Hong Kong that is notorious for severe congestion. For performance comparisons, we also applied TRANSYT to the same scenarios. The Results showed that DISCO outperformed TRANSYT for all the scenarios tested especially in congested traffic. For the congested scenarios, DISCO could reduce delay by as much as 33% when compared with TRANSYT. Even for the uncongested scenarios, DISCO’s delays could be smaller by as much as 23%.     

An iterative group-based signal optimization scheme for traffic equilibrium networks

This paper presents an iterative scheme for a combined signal optimization and assignment problem, using a traffic model from the well-known procedure TRANSYT. The signal settings are optimized by means of a group-based technique, in which the signal timings are specified by the common cycle time, the start time and duration of the period of right of way for each signal group in the network. The optimization problem was formulated as an integer program and solved by a set of heuristics. Given the optimized signal settings determined from the group-based technique, a path-based assignment algorithm is employed to obtain the equilibrium traffic pattern using the sensitivity information for TRANSYT model and a Frank-Wolf method. Based on the equilibrium flow pattern, the group-based optimization algorithm is then used to determine a better set of signal timings. The procedure is repeated until certain convergence criteria are satisfied. A numerical example is employed to demonstrate the benefits obtained from this iterative scheme. Encouraging results are obtained.     

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.     

Microscopic simulation of transit operations: policy studies with the MISTRANSIT application programming interface

Abstract

Microscopic traffic simulators are the most advanced tools for representing the movement of vehicles on a transport network. However, the energy spent in traffic microsimulation has been mainly oriented to cars. Little interest has been devoted to more sophisticated models for simulating transit systems. Commercial software has some options to incorporate the operation of transit vehicles, but they are insufficient to properly consider a real public transport system. This paper develops an Application Programming Interface, called MIcroscopic Simulation of TRANSIT (MISTRANSIT), using the commercial microsimulator PARAllel MICroscopic Simulation. MISTRANSIT makes advances in three ways: public transport vehicles can have new characteristics; passengers are incorporated and traced as individual objects; and specific models represent the interaction between passengers and vehicles at stops. This paper presents the modelling approach as well as various experiments to illustrate the feasibility of MISTRANSIT for studying policy operations of transit systems.     

Integrated optimization of bus priority operations in connected vehicle environment

Most previous works associated with transit signal priority merely focus on the optimization of signal timings, ignoring both bus speed and dwell time at bus stops. This paper presents a novel approach to optimize the holding time at bus stops, signal timings, and bus speed to provide priority to buses at isolated intersections. The objective of the proposed model is to minimize the weighted average vehicle delays of the intersection, which includes both bus delay and impact on nearby intersection traffic, ensuring that buses clear these intersections without being stopped by a red light. A set of formulations are developed to explicitly capture the interaction between bus speed, bus holding time, and transit priority signal timings. Experimental analysis is used to show that the proposed model has minimal negative impacts on general traffic and outperforms the no priority, signal priority only, and signal priority with holding control strategies (no bus speed adjustment) in terms of reducing average bus delays and stops. A sensitivity analysis further demonstrates the potential of the proposed approach to be applied to bus priority control systems in real‐time under different traffic demands, bus stop locations, and maximum speed limits. Copyright © 2016 John Wiley & Sons, Ltd.     

Multi-modal traffic signal control with priority,signal actuation and coordination

Both coordinated-actuated signal control systems and signal priority control systems have been widely deployed for the last few decades. However, these two control systems are often conflicting with each due to different control objectives. This paper aims to address the conflicting issues between actuated-coordination and multi-modal priority control. Enabled by vehicle-to-infrastructure (v2i) communication in Connected Vehicle Systems, priority eligible vehicles, such as emergency vehicles, transit buses, commercial trucks, and pedestrians are able to send request for priority messages to a traffic signal controller when approaching a signalized intersection. It is likely that multiple vehicles and pedestrians will send requests such that there may be multiple active requests at the same time. A request-based mixed-integer linear program (MILP) is formulated that explicitly accommodate multiple priority requests from different modes of vehicles and pedestrians while simultaneously considering coordination and vehicle actuation. Signal coordination is achieved by integrating virtual coordination requests for priority in the formulation. A penalty is added to the objective function when the signal coordination is not fulfilled. This “soft” signal coordination allows the signal plan to adjust itself to serve multiple priority requests that may be from different modes. The priority-optimal signal timing is responsive to real-time actuations of non-priority demand by allowing phases to extend and gap out using traditional vehicle actuation logic. The proposed control method is compared with state-of-practice transit signal priority (TSP) both under the optimized signal timing plans using microscopic traffic simulation. The simulation experiments show that the proposed control model is able to reduce average bus delay, average pedestrian delay, and average passenger car delay, especially for highly congested condition with a high frequency of transit vehicle priority requests.     

Network equilibrium for congested multi‐mode networks with elastic demand

This paper proposes an elastic demand network equilibrium model for networks with transit and walking modes. In Hong Kong, the multi‐mode transit system services over 90% of the total journeys and the demand on it is continuously increasing. Transit and walking modes are related to each other as transit passengers have to walk to and from transit stops. In this paper, the multi‐mode elastic‐demand network equilibrium problem is formulated as a variational inequality problem where the combined mode and route choices are modeled in a hierarchical logit structures and the total travel demand for each origin‐destination pair is explicitly given by an elastic demand function. In addition, the capacity constraint for transit vehicles and the effects of bi‐directional flows on walkways are considered in the proposed model. All these congestion effects are taken into account for modeling the travel choices. A solution algorithm is developed to solve the multi‐mode elastic‐demand network equilibrium model. It is based on a Block Gauss‐Seidel decomposition approach coupled with the method of successive averages. A numerical example is used to illustrate the application of the proposed model and solution algorithm.     

Modelling supported driving as an optimal control cycle: Framework and model characteristics

Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper puts forward a receding horizon control framework to model driver assistance and cooperative systems. The accelerations of automated vehicles are controlled to optimise a cost function, assuming other vehicles driving at stationary conditions over a prediction horizon. The flexibility of the framework is demonstrated with controller design of Adaptive Cruise Control (ACC) and Cooperative ACC (C-ACC) systems. The proposed ACC and C-ACC model characteristics are investigated analytically, with focus on equilibrium solutions and stability properties. The proposed ACC model produces plausible human car-following behaviour and is unconditionally locally stable. By careful tuning of parameters, the ACC model generates similar stability characteristics as human driver models. The proposed C-ACC model results in convective downstream and absolute string instability, but not convective upstream string instability observed in human-driven traffic and in the ACC model. The control framework and analytical results provide insights into the influences of ACC and C-ACC systems on traffic flow operations.     

Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation

This paper examines the impact of having cooperative adaptive cruise control (CACC) embedded vehicles on traffic flow characteristics of a multilane highway system. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce traffic congestion resulting from the acceleration/deceleration of the operating vehicles. An agent-based microscopic traffic simulation model (Flexible Agent-based Simulator of Traffic) is designed specifically to examine the impact of these intelligent vehicles on traffic flow. The flow rate of cars, the travel time spent, and other metrics indicating the evolution of traffic congestion throughout the lifecycle of the model are analyzed. Different CACC penetration levels are studied. The results indicate a better traffic flow performance and higher capacity in the case of CACC penetration compared to the scenario without CACC-embedded vehicles.     

Transit-network design methodology for actual-size road networks

The main purpose of this study is to design a transit network of routes for handling actual-size road networks. This transit-network design problem is known to be complex and cumbersome. Thus, a heuristic methodology is proposed, taking into account the major concerns of transit authorities such as budget constraints, level-of-service standards and the attractiveness of the transit routes. In addition, this approach considers other important aspects of the problem including categorization of stops, multiclass of transit vehicles, hierarchy planning, system capacity (which has been largely ignored in past studies) and the integration between route-design and frequency-setting analyses. The process developed starts with the construction of a set of potential stops using a clustering concept. Then, by the use of Newton gravity theory and a special shortest-path procedure, a set of candidate routes is formed, categorized by hierarchy (mass, feeder, local routes). In the last step of the process a metaheuristic search engine is launched over the candidate routes, incorporating budgetary constraints, until a good solution is found. The algorithm was tested on the actual-size transit network of the city of Winnipeg; the results show that under the same conditions (budget and constraints) the proposed set of routes resulted in a reduction of 14% of total travel time compared to the existing transit network. In addition the methodology developed is compared favorably with other studies using the transit network of Mandl benchmark. The generality of the methodology was tested on the recent real dataset (pertaining to the year 2010) of the larger city of Chicago, in which a more efficient and optimized scheme was proposed for the existing rail system.     

A model of speed profiles for traffic calmed roads

The influence of traffic calming measures on the speed of unimpeded vehicles has been investigated by evaluating differences in speed profiles obtained from various combinations of traffic calming measures. A case study has been conducted in the City of York (UK) focusing on traffic calming measures such as speed humps (flat-topped and round topped), speed cushions and chicanes implemented in sequence. Vehicles' passing times were simultaneously recorded at 16 points along each traffic calmed link. From these data a speed profile for each individual vehicle could be derived. An empirical model was developed using multiple regression analysis techniques based on data collected at three calibration sites. Speeds along these links were described as a function of the input speed, the type of measure and the distance between measures. The speed profile model was shown to be a good representation for the data from the calibration sites. It efficiently predicted speeds of unimpeded vehicles over a given combination of traffic calming measures in sequence. The validation process, based on data collected at three validation sites, also indicated that the model provided a good representation of the observed profiles at these sites, with the exception of the prediction of the effects of the chicanes on speeds. This type of measure was shown to produce diverse impacts on speeds which depended on the detailed design. While the model is a useful design tool, recommendations have been made for further enhancement to it.     

Modelling passengers,buses and stops in traffic microsimulation: review and extensions

In the last decade, significant research efforts and technology have been dedicated to the development of microsimulation tools for a better representation of traffic systems. As a result, several commercial packages appeared and they are used nowadays in the detailed modelling of different transportation systems and operations for specific project evaluations and local designs, mostly within the urban context. After reviewing the specialized literature, we realized that most of these microsimulation tools are oriented to the movement of cars, leaving the public transportation systems as a complement, just for a realistic representation of the transportation system as a whole, but always oriented to simulate cars. In this paper, the objective is to provide guidelines on how to incorporate the necessary entities and components for a proper simulation of public transport systems in a microsimulation environment. Thus, the different approaches to simulate transit systems at a microlevel are discussed, highlighting the necessity of including stops, passengers and transit vehicles explicitly as entities within the microsimulation environment, for modelling transfer operations, control strategies, etc. Several examples are then provided to quantify the impact of such representations, for different cases and potential simulation platforms. Copyright © 2010 John Wiley & Sons, Ltd.     

On the capacity of isolated, curbside bus stops

The maximal rates that buses can discharge from bus stops are examined. Models were developed to estimate these capacities for curbside stops that are isolated from the effects of traffic signals. The models account for key features of the stops, including their target service levels assigned to them by a transit agency. Among other things, the models predict that adding bus berths to a stop can sometimes return disproportionally high gains in capacity. This and other of our findings are at odds with information furnished in professional handbooks.     

A bi‐level programming approach — Optimal transit fare under line capacity constraints

The fare of a transit line is one of the important decision variables for transit network design. It has been advocated as an efficient means of coordinating the transit passenger flows and of alleviating congestion in the transit network. This paper shows how transit fare can be optimized so as to balance the passenger flow on the transit network and to reduce the overload delays of passengers at transit stops. A bi‐level programming method is developed to optimize the transit fare under line capacity constraints. The upper‐level problem seeks to minimize the total network travel time, while the lower‐level problem is a stochastic user equilibrium transit assignment model with line capacity constraints. A heuristic solution algorithm based on sensitivity analysis is proposed. Numerical example is used to illustrate the application of the proposed model and solution algorithm.     

Ridership estimation procedure for a transit corridor with new bus rapid transit service

Ridership estimation is a critical step in the planning of a new transit route or change in service. Very often, when a new transit route is introduced, the existing routes will be modified, vehicle capacities changed, or service headways adjusted. This has made ridership forecasts for the new, existing, and modified routes challenging. This paper proposes and demonstrates a procedure that forecasts the ridership of all transit routes along a corridor when a new bus rapid transit (BRT) service is introduced and existing regular bus services are adjusted. The procedure uses demographic data along the corridor, a recent origin–destination survey data, and new and existing transit service features as inputs. It consists of two stages of transit assignment. In the first stage, a transit assignment is performed with the existing transit demand on the proposed BRT and existing bus routes, so that adjustments to the existing bus services can be identified. This transit assignment is performed iteratively until there is no adjustment in transit services. In the second stage, the transit assignment is carried out with the new BRT and adjusted regular bus services, but incorporates a potential growth in ridership because of the new BRT service. The final outputs of the procedure are ridership for all routes and route segments, boarding and alighting volumes at all stops, and a stop‐by‐stop trip matrix. The proposed ridership estimation procedure is applicable to a new BRT route with and without competing regular bus routes and with BRT vehicles traveling in dedicated lanes or in mixed traffic. The application of the proposed procedure is demonstrated via a case study along the Alameda Corridor in El Paso, Texas. Copyright © 2015 John Wiley & Sons, Ltd.     

Mitigating negative impacts of near-side bus stops on cars

Bus stops are often placed short distances upstream of signalized intersections. Buses that dwell at one of these so-called near-side stops can impede queued cars upstream from discharging through the intersection during green times. Residual car queues can form at the intersection as a result. The smaller the distance between a stop and its intersection, the greater the problem can be.Models are formulated to address this problem using kinematic wave theory. The models can be used to determine where to place a near-side stop to achieve a target level of residual car queueing. In addition, the models are used herein to develop a scheme for mitigating residual car queues by briefly detaining some buses from reaching the stop. The scheme can be applied selectively, so that the times that detained buses depart from the stop are not postponed. The buses are therefore not delayed over the longer run. Analysis indicates that this bus-holding scheme can significantly reduce car delays and queueing. Our models for placing stops and holding buses are shown to be robust to systematic and random changes in car flow.