Dynamic Speed Adaptation for Path Tracking Based on Curvature Information and Speed Limits.

Hierarchical Bayesian modeling to evaluate the impacts of intelligent speed adaptation considering individuals’ usual speeding tendencies: A correlated random parameters approach

Formal Models for Intelligent Speed Validation and Adaptation

Adapting ISA system warnings to enhance user acceptance

As a new approach, intelligent speed adaptation (ISA) systems are being developed to provide drivers with assistance for controlling their driving speeds. In this study, ISA impacts were investigated through micro-simulation. The simulation results show that ISA has positive impacts on safety in terms of reducing speeds and speed variations. Applying ISA can harmonizing vehicle speeds between and within lanes, which results in reductions of the number of lane changes and short time-to-collision events. However, journey times could be increased because of speed decreases. This is part of the work of STARDUST, an EU project aimed at assessing the extent to which advanced driver assistance systems (ADAS) and automated vehicle guidance (AVG) systems can contribute to sustainable urban development. The main objective of this simulation study was to assess what impacts intelligent speed adaptation (ISA) have on traffic performances.

Smart cities integrate data collection and communication technologies to operate more efficiently in order to provide better services to citizens, improved road traffic situation, better economic development, etc. However, safety still a main concern of road traffic as road crashes pose serious threats to road users causing death and injury all over the world. Road traffic safety is the process of implementing measures to reduce the number of crashes, death and severe injuries. In this paper, using Machine Learning (ML) algorithms, Off-line, we train and test the Intelligent and Dynamic Adaptation Model (IDAM) on the road traffic data collected for 14 years of car crashes in United Kingdom (UK). IDAM then on-line determines the optimal speed limit for each road segment based on many predictors such as weather, road type, light condition, and many others, stated later. We train and test IDAM using three different machine learning algorithms: Artificial Neural Network (ANN), Decision Tree (DT), and Linear Regression (LR) with Stochastic Gradient Descent (SGD). Using the testing dataset, IDAM achieves prediction accuracy of around 96%. Implemented in an operation algorithm, IDAM can continuously adapt the road speed limit to an optimal value as the predictors change on-line.

ROAD SAFETY: A MAJOR PUBLIC HEALTH ISSUE

Intelligent speed adaptation: Preliminary results of on-road study in Penang, Malaysia

The long-term effect of intelligent speed adaptation on driver behaviour

• The performance of Adaptive Cruise Control (ACC) is limited on road curves. • The Intelligent Speed Adaptation for Visibility (V-ISA) adjusts speed based on road conditions. • A driving simulation study assessed the influence of ACC and V-ISA on driver behaviour. • Integrating ACC and V-ISA significantly improved longitudinal driving performance. • The system achieved high system acceptance with no added mental workload. Advanced Driver Assistance Systems (ADAS) have become an integral part of modern vehicles, significantly changing the driving experience. Adaptive Cruise Control (ACC) assists drivers in maintaining a constant speed and a safe following distance; however, it does not moderate the speed along curves when sight limitations occur, thus compromising safety. To address these challenges, this study integrates the Intelligent Speed Adaptation for Visibility (V-ISA) system with ACC. The V-ISA system dynamically adjusts the vehicle speed based on real-time visibility conditions, thereby enhancing safety on road curves where sight distance is restricted. Additionally, this study evaluates the impact of the ACC + V-ISA system on driver performance, specifically focusing on speed management, lateral vehicle control, and driver experience with assistance systems. The study was conducted in a simulated environment with forty-five participants. The results revealed that the ACC + V-ISA system effectively reduced vehicle speed on curves with limited visibility. The ability of the system to regulate speed according to prevailing road conditions highlights its potential to improve road safety. Moreover, the findings suggest that using the V-ISA system integrated with ACC maintains user acceptance and satisfaction while imposing no additional mental workload compared to using ACC alone. These insights are crucial for the future design of ADAS and autonomous vehicles and emphasize the importance of introducing this system into vehicles. LED bar colour

On the basis of the characteristic of traffic simulation technique, which is intuitionistic, exact, agile and can be tested repetitively, this paper deal with the relation between the Intelligent Speed Adaptation (ISA) and the driving safety. Different percentage of ISA vehicles and their speed distribution were constructed to simulate the traffic flow based on Vissim. Velocities of vehicles in different percentage of ISA were recorded to evaluate traffic rates. Mean speed and standard deviation of speed decreased as percentage of ISA vehicles increased according to the simulation result. Considering accident rate is determined mostly by deviation of speed, accident rate may decrease about 27% if all vehicles adopt ISA. As a conclusion, ISA is a hopeful proactive technology.

Speeding is a major problem in road safety. Intelligent Speed Adaptation (ISA) is a potential solution, but the moral acceptability of ISA has been called into question both in the popular media and in academic discussions. In this article, a moral case is made for making warning and limiting versions of ISA obligatory in all cars. The practice of car driving involves frequent speeding, which imposes unacceptable risks of harm on other road users. In this article, I argue that ISA can therefore be justified on the basis of the harm it prevents, as is the current criminalisation of speeding. I defend obligatory ISA against three objections. First, ISA is likely to introduce some additional risk for drivers. However, drivers should accept these risks to reduce the risks from driving for other parties to an acceptable level. Second, although limiting ISA reduces drivers' options for moral agency and exercising self‐restraint to some extent, this consequence is defensible. Third, accepting ISA does not commit us to accepting an entire range of other behaviour‐regulating technologies.

How much benefit does Intelligent Speed Adaptation deliver?—An analysis of its potential contribution to safety and environment

Compared to the motorway network, rural and urban roads are very unsafe. Advanced Driver Assistance Systems can be used to increase traffic safety, thereby improving the conditions for effective deployment of the underlying network for integrated traffic management. In this study, we have identified ADA systems that are expected to have a high impact on traffic safety by coupling characteristics of accidents to the functionality of different ADA systems. Based on the results of this study, Intelligent Speed Adaptation (ISA) and Intersection Crash Avoidance systems appeared most likely to substantially improve the safety on non-motorway roads. ISA was selected for further analysis due to the likelihood of timely deployment of the system. Microscopic simulation model was used to quantify the impacts on traffic safety for an urban highway with controlled intersections near the Dutch city of Delft. Depending on the penetration level, the results of the simulation study showed that the decrease in the total number of accidents ranges from 4% to 19%.

Desirability of advanced driver assistance from road safety perspective: the case of ISA

Towards setting credible speed limits: Identifying factors that affect driver compliance on urban roads