Unequipped Vehicles Research Articles

Advisory versus automated dynamic eco-driving at signalized intersections: lessons learnt from empirical evidence and simulation experiments

Research in the field of dynamic eco-driving has been primarily coupled with connected and automated vehicles which are equipped with automation functions that can accurately execute energy-efficient speed advice. Advisory dynamic eco-driving that entails driver adaptation to energy-efficient speed advice has received lesser attention although mixed traffic is expected to prevail in the forthcoming decades. This study developed a decision tree model based on real-world data collected during the pilot deployment of an advisory speed advice service along an urban arterial corridor to emulate driver adaptation to speed advice. The decision tree model was integrated into the control logic of an enhanced velocity planning algorithm to replicate the behavior of manually driven connected vehicles along dynamic eco-driving service zones in a microscopic traffic simulation environment. The conducted simulation analysis encompassed scenarios with varying penetration rates of advisory dynamic eco-driving technology, automated dynamic eco-driving technology and manually driven unequipped vehicles. Evaluation of simulation scenarios was based on the estimation of several environmental, traffic efficiency and surrogate safety measures. Simulation results indicated that performance of advisory dynamic eco-driving depends on driver adaptation to speed advice and ranges between that of manually driven unequipped vehicles and its automated counterpart. Moreover, geometrical and operational characteristics of intersection approaches comprising dynamic eco-driving service zones can influence driver adaptation to speed advice. Environmental, safety and traffic efficiency benefits are maximized in the case of vehicle fleets fully equipped with automated dynamic eco-driving systems.

Field effectiveness of general motors advanced driver assistance and headlighting systems

This study examined the field effectiveness of General Motors advanced driver assistance and headlighting systems. A total of 8,311,707 Model Year 2013–2019 vehicles were matched to police-reported crashes from 12 states. The quasi-induced exposure method was used to compare system-relevant and system-irrelevant (control) crash counts for equipped and unequipped vehicles. Logistic regression was used to adjust for ten covariates. Results indicated fusion/radar Automatic Emergency Braking, camera Automatic Emergency Braking, and Forward Collision Alert systems reduced rear-end striking crashes by 45%, 38%, and 20%, respectively. When restricting data to crashes in which someone in the General Motors striking vehicle was injured, these reductions were elevated to 59%, 54%, and 31%, respectively, providing evidence of additional crash mitigation benefits. Similarly, the Lane Keep Assist with Lane Departure Warning and Lane Departure Warning (alone) systems provided 12% and 10% reductions in lane departure crashes, respectively, with corresponding benefits in the injury analysis increasing to 19% and 18%, respectively. The Lane Change Alert with Side Blind Zone Alert system reduced lane change crashes by 16%. Reverse Automatic Braking, Rear Cross Traffic Alert, Rear Park Assist, and Rear Vision Camera (where each of these systems generally included all of the preceding systems) produced, respectively, an 82%, 55%, 36%, and 24% reduction in backing crashes. For Front Pedestrian Braking, a non-significant 14% reduction was observed for the limited set of available pedestrian crash cases. Intellibeam (auto high beam headlighting), High-Intensity Discharge headlights, and the combination of these two systems provided 26%, 11%, and 32% reductions (relative to halogen headlights) in a combined set of (unlighted) nighttime animal, pedestrian, and bicyclist crashes, respectively. These results provide widespread evidence of the substantial crash avoidance and injury reduction opportunities afforded by the production systems evaluated, as well as identify untapped system opportunities for moving toward a zero crashes vision.

Should drivers be informed about the equipment of drivers with green light optimal speed advisory (GLOSA)?

Previous research demonstrated that green light optimal speed advisory (GLOSA) affects driving behavior at signalized intersections: On the one hand, drivers assisted with GLOSA show more energy-efficient and eco-friendly driving. Following unequipped vehicles’ drivers (UVDs) also adapt their driving behavior to the assisted one. On the other hand, safety issues can be found in encounters with UVDs who also perceive assisted driving behavior negatively. Therefore, in a multi-driver simulator study (N = 60 participants sorted in groups of n = 2 UVDs), we tested whether informing UVDs about the GLOSA of an assisted driver results in more behavioral adaptation of UVDs to the assisted driving behavior, less safety issues, and less frustration of UVDs. Two UVDs followed a lead vehicle driven by a confederate. The confederate was equipped with GLOSA and knew when traffic lights switched from green to red and, consequently, slowed down when approaching a green traffic light. The degree of information UVDs received was manipulated: The group “no information” did not receive any information. The group “information” knew about the equipment of the assisted confederate with GLOSA and the group “detailed information” received additional information about its functionality and benefit. Results show that UVDs of the group “detailed information” adapted their driving behavior to the assisted driver. However, these UVDs also showed smaller minimum time-to-collision (TTC) values indicating safety issues. Results are discussed and implications made with regard to providing information to UVDs and to further investigate these challenges in the context of autonomous vehicles.

Safety analysis of the eco-approach and departure application at a signalized corridor

Various intelligent transportation systems and strategies for reducing vehicle fuel consumption and emissions have been developed. Energy and emissions could be reduced with the compromise of travel time in some environment-focused Connected Vehicle (CV) applications, which highlighted performance measures in terms of mobility and sustainability. Nevertheless, few studies have focused on safety assessment of such CV applications. In this study, a CV-based eco-driving application, namely, Eco-Approach and Departure (EAD), is selected as an example. A microscopic safety analysis tool, Surrogate Safety Assessment Model (SSAM), is utilized to assess the safety influence of EAD application in multiple scenarios. Further analysis is performed from two perspectives: (1) application users, i.e., EAD-equipped vehicles versus unequipped vehicles; and (2) traffic operators, i.e., overall traffic performance with and without the introduction of EAD. For each perspective, conflict statistics (e.g., frequency, time-to-collision distribution), overall and by type, are analyzed. Results indicate EAD is beneficial in improving the safety performance of equipped vehicles. The influence of EAD on overall traffic is scenario dependent, and a high penetration rate shows positive effects on network-wide safety benefits for most scenarios.

Region-based prescriptive route guidance for travelers of multiple classes

The performance and complicated interactions of different classes of travelers on regional urban networks are presented and analyzed. A new multi-class extension of a regional dynamic traffic model, the Network Transmission Model is proposed. The classes in question correspond to travelers using autonomous vehicles, conventional vehicles, equipped with Route Guidance and Information Systems, and unequipped vehicles. Each class is represented by a different routing method. Incremental Route Planning, an innovative predictive simulation-based routing method, Proxy Regret Matching, a non-predictive strategic learning-based method and Multinomial Logit-based Routing for 1st, 2nd and 3rd class respectively. All routing methods include a Public Transit Diversion mechanism and are assumed to provide prescriptive route guidance, with pre-trip information dissemination for every departing vehicle. We consider the possibility of non-compliance for conventional vehicles equipped with Route Guidance and Information Systems. We also consider 2 possible scenarios for autonomous vehicles that affect their travel time prediction accuracy. We simulate regional traffic dynamics for simultaneous application of all aforementioned routing methods, employing a market penetration scheme for each class of travelers. We analyze results regarding the overall network performance for various combinations of traveler class market penetration rates and non-compliance rates. We come to the conclusion that autonomous vehicles will not only provide benefits for 1st class travelers, but for all traveler classes on the network.

Is vehicle automation enough to prevent crashes? Role of traffic operations in automated driving environments for traffic safety

Automated driving systems (ADSs) are expected to prevent traffic accidents caused by driver carelessness on freeways. There is no doubt regarding this safety benefit if all vehicles in the transportation system were equipped with ADSs; however, it is implausible to expect that ADSs will reach 100% market penetration rate (MPR) in the near future. Therefore, the following question arises: ‘Can ADSs, which consider only situations in the vicinity of an equipped vehicle, really contribute to a significant reduction in traffic accidents?’ To address this issue, the interactions between equipped and unequipped vehicles must be investigated, which is the purpose of this study. This study evaluated traffic safety at different MPRs based on a proposed index to represent the overall rear-end crash risk of the traffic stream. Two approaches were evaluated for adjusting longitudinal vehicle maneuvers: vehicle safety-based maneuvering (VSM), which considers the crash risk of an equipped vehicle and its neighboring vehicles, and traffic safety-based maneuvering (TSM), which considers the overall crash risk in the traffic stream. TSM assumes that traffic operational agencies are able to monitor all the vehicles and to intervene in vehicle maneuvering. An optimization process, which attempts to obtain vehicle maneuvering control parameters to minimize the overall crash risk, is integrated into the proposed evaluation framework. The main purpose of employing the optimization process for vehicle maneuvering in this study is to identify opportunities to improve traffic safety through effective traffic management rather than developing a vehicle control algorithm that can be implemented in practice. The microscopic traffic simulator VISSIM was used to simulate the freeway traffic stream and to conduct systematic evaluations based on the proposed methodology. Both TSM and VSM achieved significant reductions in the potential for rear-end crashes. However, TSM obtained much greater reductions when the MPR was greater than 50%. This study should inspire transportation researchers and engineers to develop effective traffic operations strategies for automated driving environments.

Development and Evaluation of High-Speed Differential Warning Application Using Vehicle-to-Vehicle Communication

Connected vehicle (CV) technology has shown great potential in enhancing safety, mobility, and environmental sustainability of roadway transportation systems by enabling vehicles and infrastructure to exchange real-time information through wireless communications. The information available through CV technology has been used to develop a variety of onboard driver assistance tools and applications. This paper presents an innovative, safety-focused CV application called the high-speed differential warning (HSDW). The application identifies potential hazards resulting from high-speed differentials between HSDW-equipped vehicles (ego-vehicles) and surrounding remote vehicles and then provides alerts to drivers of ego-vehicles to help them take appropriate actions. In this research, real-world scenarios and parameters of the HSDW application are first identified. A driver response strategy for each scenario is then developed in consonance with findings from a public survey on the HSDW application. Next, a comprehensive evaluation of various scenarios is conducted with a well-calibrated Paramics traffic microscopic simulation tool set up for a real-world traffic network. Finally, the safety performance of HSDW-equipped vehicles, unequipped vehicles, and overall traffic is analyzed with the surrogate safety assessment model. Results demonstrate that the proposed HSDW application improves the safety performance of ego-vehicles without compromising the mobility and environmental sustainability performance of the overall traffic.

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.

Does assisted driving behavior lead to safety-critical encounters with unequipped vehicles’ drivers?

With Intelligent Transport Systems (e.g., traffic light assistance systems) assisted drivers are able to show driving behavior in anticipation of upcoming traffic situations. In the years to come, the penetration rate of such systems will be low. Therefore, the majority of vehicles will not be equipped with these systems. Unequipped vehicles’ drivers may not expect the driving behavior of assisted drivers. However, drivers’ predictions and expectations can play a significant role in their reaction times. Thus, safety issues could arise when unequipped vehicles’ drivers encounter driving behavior of assisted drivers. This is why we tested how unequipped vehicles’ drivers (N=60) interpreted and reacted to the driving behavior of an assisted driver. We used a multi-driver simulator with three drivers. The three drivers were driving in a line. The lead driver in the line was a confederate who was followed by two unequipped vehicles’ drivers. We varied the equipment of the confederate with an Intelligent Transport System: The confederate was equipped either with or without a traffic light assistance system. The traffic light assistance system provided a start-up maneuver before a light turned green. Therefore, the assisted confederate seemed to show unusual deceleration behavior by coming to a halt at an unusual distance from the stop line at the red traffic light. The unusual distance was varied as we tested a moderate (4m distance from the stop line) and an extreme (10m distance from the stop line) parameterization of the system. Our results showed that the extreme parametrization resulted in shorter minimal time-to-collision of the unequipped vehicles’ drivers. One rear-end crash was observed. These results provided initial evidence that safety issues can arise when unequipped vehicles’ drivers encounter assisted driving behavior. We recommend that future research identifies counteractions to prevent these safety issues. Moreover, we recommend that system developers discuss the best parameterizations of their systems to ensure benefits but also the safety in encounters with unequipped vehicles’ drivers.

Handling Cut-In Vehicles in Strings of Cooperative Adaptive Cruise Control Vehicles

Cooperative adaptive cruise control (CACC) systems are a candidate to improve highway capacity by shortening headways and attenuating traffic disturbances. Although encouraging results have been obtained until now, a wide range of traffic circumstances has to be investigated in order to get reliable CACC systems driving on real roads. Among them, handling both vehicle-to-vehicle (V2V) communications-equipped and unequipped vehicles merging into the string of CACC vehicles is a commonly mentioned challenge. In this article, an algorithm for managing the transitions in response to cut-ins from V2V- or non-V2V-equipped vehicles is developed and tested using a string of four CACC vehicles. A CACC controller is implemented in four production Infiniti M56s vehicles and tested in real traffic, where non-V2V-equipped vehicles can cut in. The effects of a vehicle performing a cut-out are also investigated. Then responses to cut-ins by equipped and nonequipped vehicles are simulated for longer strings of vehicles using car-following models for both the production adaptive cruise control (ACC) system and the newly developed CACC controller. Results demonstrate that the CACC system is able to handle cut-in vehicles without causing major perturbations, while also reducing significantly the impact of this maneuver on the following vehicles, improving traffic flow.

Automated Driving and its Effect on the Safety Ecosystem: How do Compatibility Issues Affect the Transition Period?

Different components of automated vehicles are being made available commercially as we speak. Much research has been conducted into these components and many of these have been studied with respect to their effects on safety, but the transition period from non-automated driving to fully automated vehicles raises safety related issues dealing with mixed traffic situations. More in-depth knowledge should be gained in (the safety of) the behaviour of drivers of unequipped vehicles, enabling automated vehicles to predict and adequately respond to potentially unsafe behaviour, a concept we call backwards compatibility. Also, automated vehicle system design tends to be from an optimal system performance perspective which leads to driving patterns such as driving in the centre of a lane. Other (human) road users however likely exhibit driving behaviour in line with different rationales which allow for suboptimal driving patterns. As of yet, it remains unclear whether these patterns contain indications about the intentions of a driver and if or how other road users anticipate these. This could have two consequences with regard to mixed traffic situations. First of all, other road users might miss important cues from the behaviour of the automated vehicle (what we call forward incompatibility). Secondly, the occupant of an automated vehicle might expect human-like behaviour from the automated vehicle in safety-critical situations, lowering acceptance if this does not meet expectations. The current paper considers these issues and states that we need more insight in how road users use other road users’ behaviour to anticipate safety critical events, especially in the transition period towards fully automated vehicles.

Driving next to automated vehicle platoons: How do short time headways influence non-platoon drivers’ longitudinal control?

Advanced driver assistance systems (ADAS) are taking over an increasing part of the driving task and are supporting the introduction of semi- and fully automated vehicles. As a consequence, a mixed traffic situation is developing where vehicles equipped with automated systems taking over the lateral and longitudinal control of the vehicle will interact with unequipped vehicles (UV) that are not fitted with such automated systems. Different forms of automation are emerging and it appears that regardless of which form is going to become popular on our roads, there is a consensus developing that it will be accompanied by a reduction in time headway (THW). The present simulator study examined whether a ‘contagion’ effect from the short THW held in platoons on the UV drivers would occur. Thirty participants were asked to follow a lead vehicle (LV) on a simulated motorway in three different traffic conditions: surrounding traffic including (1) platoons with short following distance (THW=0.3s), (2) large following distance (THW=1.4s) or (3) no platoons at all. Participants adapted their driving behaviour by displaying a significant shorter average and minimum THW while driving next to a platoon holding short THWs as when THW was large. They also spent more time keeping a THW below a safety threshold of 1s. There was no carryover effect from one platoon condition to the other, which can be interpreted as an effect that is not lasting in time. The results of this study point out the importance of examining possibly negative behavioural effects of mixed traffic on UV drivers.

The Effect of IntelliDrive on the Efficiency of Highway Transportation Systems

Recently, the IntelliDrive initiative has been proposed by the US Department of Transportation (USDOT) to enhance on-road safety and efficiency. In this study, we provide a mathematical framework which predicts the effect of such technologies on the efficiency of multilane highway systems prior to their real-life deployment. Our study shall encompass mixed traffic conditions in which a variety of assisted, automated and unequipped vehicles coexist. We show that intervehicular communications improves the flow of vehicles by reducing the perception-reaction (P-R) times of drivers and, in some cases, allowing for more efficient lane-changing operations. As we shall see, unlike the latter, the former effect of IntelliDrive on driver P-R time is always there, regardless of the specific traffic conditions.

Preventing Automotive Pileup Crashes in Mixed-Communication Environments

Recent news illustrates the frequent occurrence of pileup crashes on highways. A predominant reason for the occurrence of such crashes is that current vehicles (including those equipped with an automatic cruise control system) do not provide drivers with advance information of events occurring far ahead of them. The use of intervehicular communication to provide advance warnings to enhance automotive safety is therefore being actively discussed in the research community. In this paper, we investigate scenarios wherein only a subset of the vehicles in a multivehicle stream is equipped with such advance-warning capabilities. These vehicles (which are equipped with the capability to receive far-ahead information) are arbitrarily distributed among other unequipped vehicles that are capable of receiving only local near-neighbor information. It is seen that there are conditions wherein even a partial equipage of the system can be beneficial to both equipped and unequipped vehicles in a mixed-vehicle stream. We demonstrate this through both simulations and a theoretical analysis. We also developed a prototype of an advance-warning system and conducted road tests to test the concept. These road tests have demonstrated the system's performance to be satisfactory, subject to good communication links, for the class of scenarios tested.

Impact of Active Speed Limiters on Traffic Flow and Safety

Speed limiters, which control the maximum speeds of vehicles so equipped, have been proposed in recent years as speed management tools. A simulation-based evaluation is described of the impact of a wide installation of speed limiters on traffic flow characteristics and on safety. Microscopic traffic simulation is used; it models the driving behavior of individual vehicles in detail and so captures not only the impact of speed limiters on equipped vehicles but also the interaction between equipped and unequipped vehicles and the resulting impact on the latter. In the experiment, the impact is evaluated of preset speed limiters for two limiter-set speeds, 100 km/h and 120 km/h, at various desired speed distributions and congestion levels. The simulation results show that speed limiters can reduce average traffic speeds up to 10% and that the variability of traffic speeds may also be lowered. Consequently, a significant reduction in accident rates might be achieved.

STAND-ALONE COLLISION WARNING SYSTEMS BASED ON INFORMATION FROM ON-BOARD SENSORS: Evaluating Performance Relative to System Penetration Rate

This paper looks at stand-alone collision warning systems that are based on information from on-board sensors and evaluates their safety performance relative to system penetration rate. The authors developed an autonomous microscopic traffic simulator for collision warning systems, including both forward vehicle collision warning systems and side collision warning systems, then evaluated such systems through simulation. Safety performance from the perspective of drivers was evaluated using the average distance driven without an accident for both system-equipped and unequipped vehicles. Safety performance from the perspective of road administrators was evaluated using the average interval between accidents. The average distance driven without an accident for system-equipped vehicles, compared to that for a system in which no system-equipped vehicles exist, increases greatly beginning from a low rate of penetration, suggesting that increased rates of penetration are attended by even greater effectiveness. With regard to the average distance driven without an accident for unequipped vehicles, too, increased rates of penetration are attended by increased safety performance due to the collision avoidance effect of warnings produced by system-equipped vehicles. In terms of safety performance from the perspective of road administrators, that is, the average interval between accidents, evaluations indicated that safety performance increases dramatically when the penetration rate exceeds 60%. The above findings illustrate the effect of system penetration rate on the safety performance of stand-alone collision warning systems that are based on information from on-board sensors.

DEVELOPMENT OF A DYNAMIC TRAFFIC SIMULATION MODEL IN A NEAR SYSTEM OPTIMAL ROUTE GUIDANCE SYSTEM

This paper presents the development of a Dynamic Traffic Simulation model as the heart of a comprehensive Route Guidance System (RGS) with behavioral and information supply components. An event-based dynamic traffic simulation model was built to account for the dynamics of traffic flow. The complex and changing state of traffic under both recurring and incident-related congestion(s) have been captured by analyzing traffic in multiple time periods. It also has the capability to predict traffic in advance for both the RGS-equipped and unequipped vehicles. The model developed in this research was validated on two networks. The first was a hypothetical network consisting of nine nodes and eleven links, and the second was a real-life network from southwestern Maryland that consists of 44 nodes and 132 links. A comparative analysis of the measures of effectiveness, such as total travel time, total vehicle miles of travel(VMT), travel time per VMT, average speed, fuel consumption, and environmental emissions, revealed that the performance of the developed RGS is significantly better than the performance under existing non-RGS conditions. Several conclusions were drawn from this research. It was shown that under congestion conditions, the RGS with an appropriate mix of information supply strategies can be considered as a surrogate for capacity enhancement. A more realistic representation of the traffic system, including traffic flow and network attributes, has also been captured in the framework for RGS. Moreover, the modular construction of the program wherein different modules can be integrated or removed fairly easily allows the developer to reconfigure the program to perform specific functions or achieve certain performance characteristics. The RGS developed in this project can be used in conjunction with improving freight operations, network evaluation, transit information systems, emergency response vehicles and logistics operations.