Speed Advisory Research Articles

A trajectory smoothing method at signalized intersection based on individualized variable speed limits with location optimization

Traffic signals on urban highways force vehicles to stop frequently and thus causes excessive travel delay, extra fuel consumption and emissions, and increased safety hazards. To address these issues, this paper proposes a trajectory smoothing method based on Individual Variable Speed Limits with Location Optimization (IVSL-LC) in coordination with pre-fixed traffic signals. This method dynamically imposes speed limits on some identified Target Controlled Vehicles (TCVs) with Vehicle to Infrastructures (V2I) communication ability at two IVSL points along an approaching lane. According to real-time traffic demand and signal timing information, the trajectories of each approaching vehicle are made to run smoothly without any full stop. Essentially, only TCVs’ trajectories need to be controlled and the other vehicles just follow TCVs with Gipps’ car-following model. The Dividing RECTangles (DIRECT) algorithm is used to optimize the locations of the IVSLs. Numerical simulation is conducted to compare the benchmark case without vehicle control, the individual advisory speed limits (IASL) and the proposed IVSL-LC. The result shows that compared with the benchmark, the IVSL-LC method can greatly increase traffic efficiency and reduce fuel consumption. Compared with IASL, IVSL-LC has better performance across all traffic demand levels, and the improvements are the most under high traffic demand. Finally, the results of compliance analysis show that the effect of IVSL-LC improves as the compliance rate increases.

Enhancement of safety and comfort of cyclists at intersections

Cyclist safety is increasingly becoming a societal problem in Europe, as shown by road safety statistics. Frequent stops for red traffic lights at intersections are experienced by cyclists as a major inconvenience. This study introduces a green wave concept for cyclists, with focus on the traffic management and control aspects under cooperative intelligent transport systems applications. It especially addresses increasing stability of the adaptive control system, to overcome the drawbacks of both actuated and traditional adaptive control (which are too unpredictable for a green wave speed advice). In addition, solutions for avoiding increased delays for other traffic are investigated, as generally result from a classic green wave approach (with only fixed-time control) and traditional adaptive control. This study introduces an adaptive control algorithm for a real-time model-predictive controller and implements a plan-deviation cost function to address stabilisation. Simulation results show that the developed method increases stability of the adaptive control system, limits extra delays for other traffic and yields a high success rate for the green wave concept.

Leader and Leaderless Multi-Layer Consensus With State Obfuscation: An Application to Distributed Speed Advisory Systems

Two new distributed speed advisory systems (SASs) are introduced in this paper. The systems implement consensus algorithms that guide a set of vehicles toward a common driving speed. A major innovation is that consensus is achieved over a multi-layer network, in which parallel network topologies of connected vehicles are superimposed. The reason for the use of these parallel networks is that, in this way, the state obfuscation is possible, with the benefit that common driving speed is attained with no vehicle knowing the exact state of other vehicles. Convergence of the SASs is formally proved and two new results for the consensus of multi-layer networks modeled via stochastic differential equations are introduced. The SASs are also validated via simulation and via a hardware-in-the-loop setup, in which a real vehicle interacts with simulated entities.

Field tests of a dynamic green driving strategy based on inter-vehicle communication

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.

3D virtual intersection sight distance analysis using lidar data

Sight distance analyses require careful and detailed field measurements to facilitate proper engineering decision making regarding the removal of obstructions, establishment of regulatory and advisory speed limits, and the location of new access points, among numerous other purposes. However, conventional field measurements for these analyses present safety concerns because they require personnel to be in or adjacent to traffic lanes. They can also be time consuming, costly, and labor intensive. Furthermore, the predominantly two-dimensional (2D) methods involve simplifying assumptions such as a “standard” vehicle heights and lengths without considering the wide range of vehicles and drivers present on the road. Recently, many transportation agencies worldwide have begun to acquire mobile lidar data to map their roadway assets. These data provide a rich three-dimensional (3D) environment that enables one to virtually visit a site at any frequency and efficiently evaluate sight distances from the safety of the office. This study investigates advanced safety analysis methodologies for drivers’ sight distance based on high resolution lidar data. The developed simulation method enables users to virtually evaluate available sight distances in a 3D context considering a variety of objects, vehicle types, and multi-modal forms of transportation (e.g., bicycle, pedestrian). The feasibility of this technique was analyzed with a case study at an intersection located in Corvallis, Oregon, USA. The experimental results demonstrated the ability of the proposed methodology to capture significantly more detail on visibility constraints when compared with conventional measurements as well as provide more flexibility in the analysis.

Exploring GLOSA systems in the field: Technical evaluation and results

Green Light Optimal Speed Advisory (GLOSA) systems are believed to be able to lower CO2 emissions, fuel consumption, and travel times by avoiding unnecessary stopping at intersections. Approaching vehicles are given speed recommendations based on current and future traffic light signal phase timings. These systems have been widely evaluated by means of simulation and, while most research focuses on the impact assessment of GLOSA along with environmental influences, minor attention was drawn to the holistic technical evaluation of included sub-modules and implementations.In this extended version of our IEEE VNC 2016 publication, we present a holistic concept for the technical evaluation of IEEE 802.11p-based GLOSA systems. We first give a comprehensive survey on GLOSA systems and studies all around the world and identify remaining problems. We introduce metrics to cover the whole spectrum of GLOSA operations and particularly focus on (modeling) problems we encountered in the field that are often not taken into consideration in simulation studies. We demonstrate how this concept can be used to evaluate the real-world GLOSA system tested in the European Commission co-funded field trial DRIVE C2X. Results derived from Field Operational Test (FOT) data show that our metrics are well-suited to assess the performance of the GLOSA system, and also to identify sources of potential problems or bottlenecks.Based on our findings, we argue that most GLOSA simulation studies are too optimistic in terms of communication performance. Lastly, we give recommendations on how real-world GLOSA systems can be further improved to support a sufficient level of performance.

Advantage of cooperative traffic light control algorithms

Based on the presentation at ITS Europe Congress Glasgow 2016. Contemporary traffic light control (TLC) systems rely on sensors for detection of traffic which are costly in purchase, installation and maintenance. Emerging cooperative technology offers an attractive alternative where only one road side unit per intersection is required, instead of several infrastructure sensors per lane. However, studies showed that traffic control with cooperative detection requires a penetration rate of at least 20% to function effectively. To show the potential of cooperative traffic control, this study presents three algorithms: (i) the SWARM control algorithm, which is designed to work with very low penetration rates; (ii) an extension to the adaptive control algorithm, ImFlow, which uses cooperative data for enhanced queue modelling; and (iii) an ImFlow extension to stabilise green planning to enable green light optimal speed advice. The results from micro-simulation show a 7.8% improvement for stops and delay time over traditional adaptive control for SWARM, and 14.9% for Cooperative ImFlow. Adding planning stabilisation reduced the average perceived change for end users from 9.0-2.3%, without performance loss for the overall traffic flow. This shows the large potential of cooperative traffic control.

Deployment and Field Evaluation of In-Vehicle Traffic Signal Advisory System (ITSAS)

This research evaluates the impact of In-vehicle Signal Advisory System (ITSAS) on signalized arterial. ITSAS provides individual drivers equipped with a mobile communication device with advisory speed information enabling to minimize the time delay and fuel consumption when crossing intersection. Given the instantaneous vehicular driving information, such as position, speed, and acceleration rate, ITSAS produces advisory speed information by taking into consideration the traffic signal changes at a downstream intersection. The advisory speed information includes not only an optimal speed range updated every 300-ft for individual drivers but also a descriptive message to warn drivers stop to ensure safety at the downstream intersection. Unlike other similar Connected Vehicles applications for intersection management, ITSAS does not require Roadside Equipment (RSE) to disseminate the advisory speed information as it is designed to exploit commercial cellular network service (i.e., 3G and 4G-LTE). Thus, ITSAS can be easily plugged into existing traffic control management system to rapidly conduct its implementation without significant additional cost. This research presents the field evaluations of ITSAS on a signalized corridor in New Jersey, which discovered significant travel time savings for the equipped vehicle.

Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation

Conceptually, a Green Light Optimal Speed Advisory (GLOSA) system suggests speeds to vehicles, allowing them to pass through an intersection during the green interval. In previous papers, a single speed is computed for each vehicle in a range between acceptable minimum and maximum values (for example between standstill and the speed limit). This speed is assumed to be constant until the beginning of the green interval, and sent as advice to the vehicle. The goal is to optimise for a particular objective, whether it be minimisation of emissions (for environmental reasons), fuel usage or delay. This paper generalises the advice given to a vehicle, by optimising for delay over the entire trajectory instead of suggesting an individual speed, regardless of initial conditions – time until green, distance to intersection and initial speed. This may require multiple acceleration manoeuvres, so the advice is sent as a suggested acceleration at each time step. Such advice also takes into account a suitable safety constraint, ensuring that vehicles are always able to stop before the intersection during a red interval, thus safeguarding against last-minute signal control schedule changes. While the algorithms developed primarily minimise delay, they also help to reduce fuel usage and emissions by conserving kinetic energy. Since vehicles travel in platoons, the effectiveness of a GLOSA system is heavily reliant on correctly identifying the leading vehicle that is the first to be given trajectory advice for each cycle. Vehicles naturally form a platoon behind this leading vehicle. A time loop technique is proposed which allows accurate identification of the leader even when there are complex interactions between preceding vehicles. The developed algorithms are ideal for connected autonomous vehicle environments, because computer control allows vehicles’ trajectories to be managed with greater accuracy and ease. However, the advice algorithms can also be used in conjunction with manual control provided Vehicle-to-Infrastructure (V2I) communication is available.

Feedback control speed harmonization algorithm: Methodology and preliminary testing

The capacity drop phenomenon, which reduces the maximum bottleneck discharge rate following the onset of congestion, is a critical restriction in transportation networks that produces additional traffic congestion. Consequently, preventing or reducing the occurrence of the capacity drop not only mitigates traffic congestion, but can also produce environmental and traffic safety benefits. In addressing this problem, the paper develops a novel bang-bang feedback control speed harmonization (SH) or Variable Speed Limit (VSL) algorithm, that attempts to prevent or delay the breakdown of a bottleneck and thus reduce traffic congestion. The novelty of the system lies in the fact that it is both proactive and reactive in responding to the dynamic stochastic nature of traffic. The system is proactive because it uses a calibrated fundamental diagram to initially identify the optimum throughput to maintain within the SH zone. Furthermore, the system is reactive (dynamic) because it monitors the traffic stream directly upstream of the bottleneck to adjustment the metering rate to capture the dynamic and stochastic nature of traffic. The steady-state traffic states in the vicinity of a lane-drop bottleneck before and after applying the SH algorithm is analyzed to demonstrate the effectiveness of the algorithm in alleviating the capacity drop. We demonstrate theoretically that the SH algorithm is effective in enhancing the bottleneck discharge rate. A microscopic simulation of the network using the INTEGRATION software further demonstrates the benefits of the algorithm in increasing the bottleneck discharge rate, decreasing vehicle delay, and reducing vehicle fuel consumption and CO2 emission levels. Specifically, compared with the base case without the SH algorithm, the advisory speed limit increases the bottleneck discharge rate by approximately 7%, reduces the overall system delay by approximately 20%, and reduces the system-wide fuel consumption and CO2 emission levels by 5%.

A comparison of different configurations of a Centrally Guided Train Operation System in Dutch Railway Operations

Although Dutch train operation is one of the safest in the European Union, safety remains one of the top priorities. On a yearly basis, an estimated 7 million red signal approaches occur on the Dutch railway network for the largest train operating company NS Reizigers. These red signals alert a driver to prepare to stop the train, possibly because the next section of the track is occupied by another train. Out of these 7 million red signal approaches, 3 million red signal approaches are estimated to be caused by small deviations from the planning. As a result of this continuous focus on safety aspects, ProRail, the Dutch rail infrastructure manager, and NSR started a project to empower train drivers with more information on the current situation and near future related to their trains. In a simulation study four train driving strategies were compared in two areas in the network. These strategies, ranked in order of increasing level of driver information quality, are: first is driving at highest allowed speed, second is following the timetable without advisory speed information, third is using advisory speed information without changing train orders, and fourth is using advisory speed information with the possibility of changing train orders. At each location the timetable has been exposed to three increasing levels of disturbance scenarios. Results show that the advisory speeds strategy (third) reaps a large part of the safety benefits that the fourth (limited Centrally Guided Train Operation) strategy is able to achieve.

Evaluation of Operational Effects of I-66 Active Traffic Management System

In September 2015, the Virginia Department of Transportation instituted an active traffic management system on I-66 in Northern Virginia. I-66 is a major commuter route into Washington, D.C., that experiences significant recurring and nonrecurring congestion. The active traffic management system sought to manage existing capacity dynamically and more effectively with hard shoulder running, advisory variable speed limits, lane use control signs, and queue warning systems. An initial before-and-after analysis of the system’s operational effectiveness was performed with probe-based travel time data from the provider, INRIX, and used records from the active traffic management’s traffic operations center. On weekdays, statistically significant improvements were often observed during off-peak periods, but conditions did not improve during peak periods. Weekends showed the greatest improvements, with travel times and travel time reliability measures improving by 10% to 14%. Segment-level analysis revealed that most of the benefits were attained because of the use of hard shoulder running outside of the peak periods, which created additional capacity on I-66. Benefits due to advisory variable speed limits were inconclusive because of limited data.

Urban traffic control: present and the future

ABSTRACTFaced with the great stride of Information and Communication Technology (ICT), in particular in the utilization of the Internet and advances in data gathering methods, the application of the ICT in Transport and Traffic is getting ever more pervasive and is providing more opportunities in managing and controlling traffic more efficiently, equitably, flexibly and more dynamic in detecting and responding to varying traffic demand and environmental concerns. ICT is one of the best tools in assisting network management and control to achieve the most desirable network performance for these goals. As the behaviour of the road users can be influenced by the information received through V2X communication, how to incorporate the behavioural change especially with regard to speed advisory into the future control system is discussed in this paper. This paper first shows two real examples in China in coordinating traffic control to general green waves in large and complex networks to reduce journey time and fuel consumption, it then moves to briefly describe the simTD project conducted in Germany and the VS-PLUS controller used in the project. VS-PLUS is a parameterized control method, very flexible in meeting a variety of management and control objectives and to configure to deal with diverse traffic conditions. Its flexibility keeps it open to build a higher level of intelligence. Finally, the paper proposes to include vehicle speed as an endogenous parameter in optimizing traffic control and then introduces a Urban Traffic Control system configuration using the system jointly developed from a partnership between the Key Laboratory for the Ministry for Public Security of China for Optimal System Integration and Control at the Anhui Keli Information Industry Co. Ltd and the Verkehrs-Systeme AG of Switzerland.

Does surrounding traffic benefit from an assisted driver with traffic light assistance system?

Traffic light assistance systems enable drivers more energy and time efficient driving behavior at signalized intersections. However, most vehicles will not be equipped with such systems in the next years. These unequipped vehicles’ drivers (UVDs) may benefit from assisted drivers, if they would adapt their behavior. This paper outlines how UVDs (N=60) interpreted and reacted to a driver with traffic light assistance system. We used a multi-driver simulator with three drivers driving in a car-following scenario. The lead driver was not a participant, but a confederate who was followed by two UVDs. The confederate was apparently equipped either with or without a traffic light assistance system. The traffic light assistance system consisted of two functionalities: a Green Light Optimal Speed Advisory and a start-up assistance system with two different parametrizations. These functionalities aimed at preventing unnecessary changes in speed and reducing the start-up lost time after signal change. The results showed that UVDs benefited from the driving behavior of the confederate with traffic light assistance system. However, the assisted driving behavior was hardly understood and partly rated as aversive by the UVDs. We discuss how to enhance behavioral adaptation of UVDs. We also outline which negative consequences may result from encounters of driver with systems and UVDs. We assume that how UVDs react towards drivers with systems may be one factor contributing to a successful launch of such systems.

Arrival and Departure Aircraft Scheduling with Turbulence Interaction Concept

This paper studies the problem of optimal aircraft takeoff and landing sequencing at congested airports. The objective is to minimize the makespan for all the aircraft to land at or depart from the airport. This paper presents a novel approach to deal with aircraft separation constraints. The separation time is considered as the combination of the turbulence generated by the preceding aircraft and the ability of the succeeding aircraft to resist turbulence. With this novel concept, the separation constraints are more flexible with aircraft types and are linear with the decision variables. When the sequencing matrix is used as the decision variable, the required number of separation constraints grows linearly with the number of aircraft instead of the quadratic growth with existing formulations. The current formulation also considers the problem of minimizing the deviation from scheduled arriving and departing times. The result provides the speed advisories for each aircraft to air traffic controllers. With the current optimization process, the final result can meet both optimal sequence and minimal time variation requirements. Finally, several simulation results are used to demonstrate the effectiveness of this approach.

Speed Advisory and Signal Offsets Control for Arterial Bandwidth Maximization and Energy Consumption Reduction

The problem of maximizing bandwidth along an arterial is addressed here by use of two combined control actions: traffic light offsets and recommended speeds. The optimization problem has been enriched in order to account for traffic energy consumption and network travel time, thus avoiding impractical or undesirable solutions. A traffic microscopic simulator has been used to assess the performance of the proposed technique in terms of energy consumption, travel time, idling time, and number of stops. The correlation of theoretical bandwidth with known traffic performance metrics is studied, and an analysis of the Pareto optimum has been carried out to help the designer choose a tradeoff in the multiobjective optimization. Finally, an evaluation of the traffic performance at different levels of traffic demand aims at showing the best operation conditions of the proposed strategy. A demand-dependent optimization is proposed.

Optimal Speed Advisory: a Vehicular Networks Application focused on decreasing CO2 emissions

Whilst the number of vehicles moving through the streets growths exponentially, the high density vehicular flow is now a mobility and a public health problem for governmental institutions and people, since the time of travel, gasoline consumption, and greenhouse gas (GHG) emissions have suffered an important increase. Hereby, several research projects aim to reduce the impact of this increase using new technological platforms like the so-called Vehicular Networks (VN), which are focused on the establishment of wireless connections between automobiles and/or fixed infrastructure. In this context, and aiming to reduce the potential carbon footprint of the vehicles, we have developed an application for the simulation of a VN using two software applications: SUMO and OMNeT++. The application we developed sends information packets directly to the cars about the adequate speed in a given area, optimizing the fuel usage and reducing the GHG emissions. Results show that when vehicles follow the speed (previously studied), the gasoline consumption and the GHG emissions present a considerable decrease compared to the vehicles not running at that speed.

Vehicular-Communications-Based Speed Advisory System for Electric Bicycles

Smart transportation, which is an important dimension of smart cities, includes both intelligent and “green” transportation solutions. Cycling, as one of the most sustainable forms of transportation, is and should be an important component of smart cities. Electric bicycles, which are the most popular electric vehicles, subscribe to this type of transportation. They have several advantages when compared with traditional bicycles but have issues that relate to battery-limited capacity and long periods of charging as well. Consequently, energy-efficient solutions for electric bicycles are of very high research interest. Research on vehicular-communications-based energy-efficient solutions for electric vehicles is still in the early stages. Among electric vehicles, electric bicycles distinguish themselves as a special class as they have different characteristics and road-related requirements. This paper proposes a novel vehicular-communications-based speed advisory system for electric bicycles. The solution recommends strategic riding (i.e., the appropriate speed) when bicycles are approaching a signaled intersection to avoid high-power-consumption scenarios. The proposed approach includes a fuzzy-logic-based wind-aware speed adaptation policy, as, among all the other vehicles, bicycles are mostly affected by wind. Experimental results based on a real testbed and extensive simulation-based testing demonstrate that, by using the proposed solution, significant energy savings are recorded. In addition, an analysis on comfort-related metrics shows that the proposed solution can also contribute to improving the cycling experience.

A Distributed and Privacy-Aware Speed Advisory System for Optimizing Conventional and Electric Vehicle Networks

One of the key ideas to make intelligent transportation systems work effectively is to deploy advanced communication and cooperative control technologies among vehicles and road infrastructures. In this spirit, we propose a consensus-based distributed speed advisory system that optimally determines a recommended common speed for a given area in order that the group emissions, or group battery consumptions, are minimized. Our algorithms achieve this in a privacy-aware manner; that is, individual vehicles do not reveal in-vehicle information to other vehicles or to infrastructure. A mobility simulator is used to illustrate the efficacy of the algorithm, and hardware-in-the-loop tests involving a real vehicle are given to illustrate user acceptability and ease of deployment.

Evaluation of variable advisory speed limits in congested work zones

ABSTRACTThe effectiveness of variable “advisory” speed limit (VASL) systems in congested urban work zones was investigated. Except for one publication, all previous studies focused on regulatory speed limit systems. This study used a comprehensive set of performance measures to investigate VASL effectiveness. Four congested work zones with lanes reduced from four to three lanes on Interstate 270 in St. Louis, Missouri, were selected for empirical and simulation analysis. The empirical analysis showed that VASL were effective in slowing down drivers gradually as they approached the work zone, thus reducing any sudden speed changes. Simulation analysis showed that operationally, the use of VASL resulted in: a 39% to 53% decrease in average queue length, a 7% to 11% reduction in throughput, a 4% to 8% increase in travel time. The use of VASL achieved a decrease in the standard deviation of speeds at the taper and 1-mile upstream of the work zone. The maximum speed differences also decreased up to 10 mph with VASL. A new VASL algorithm investigated in the study showed significant improvements in mobility and safety performance compared to the original field algorithm. The new algorithm made promising improvements in safety—a 30% reduction in rear-end conflicts and a 20% reduction in lane changing conflicts as compared to the without VASL condition. The new VASL algorithm also decreased the queue length, further improving the overall safety in congested work zones. Thus, it is possible to design a VASL system that improves traffic and safety in congested work zones.