An assessment of ISA impacts through micro-simulation

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

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%.

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

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

Adapting ISA system warnings to enhance user acceptance

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

Intelligent speed adaptation (ISA) has the potential to improve road traffic safety significantly. Large-scale implementation of ISA, however, is hampered by large uncertainties, such as the level of compliance (LC), reliability of the technology, unexpected costs and so on. We suggest an adaptive policymaking approach for implementing ISA. We propose five steps: (1) specify the policy problem, (2) assemble a basic policy, (3) specify the rest of the policy, (4) learn from real world experience with the basic policy and (5) adjust the implemented policy. We demonstrate, as a proof of concept, how to design a basic ISA policy and how to gain knowledge over time about the behaviour of the system in order to resolve some of the uncertainties and improve the policy. By monitoring the percentage of speeding drivers to detect changes in the LC, the policy can be adapted to unfolding events. Hence, by using the adaptive approach, policymakers can proceed with implementing ISA despite the large uncertainties.

In this paper I perform an analysis of vehicle lane changes and how they relate to fastest path determination. I converted live discrete loop detector data from the California Department of Transportation into continuous data to be utilized by vehicles in a vehicle-to-vehicle-to-infrastructure (V2V2I) intelligent transportation system (ITS) architecture. The continuous data was then used by FreeSim (http://www.freewaysimulator.com) to simulate live traffic conditions. As the time to traverse the edges in the transportation network were being constantly updated, additional vehicles were inserted into the network to determine travel times and fastest paths from a source node to a destination node. The output shows that faster and more accurate paths can be found if lane data is obtained rather than just summary data of loop detectors. Further, if vehicles can be routed along paths with optimal lane changes to decrease the total travel time, a savings of approximately 33% of the travel time can be experienced. It is also shown that the number of lane changes needed in the fastest path with regards to lanes is lower than the number of lane changes needed for other candidate fastest paths, and highways with less congestion require fewer lane changes.

An ex ante impact assessment of advanced driver assistance systems was conducted with focus on autonomous intelligent cruise control and intelligent speed adaptation. The effects of these systems on efficiency, reliability, driving comfort, and safety were addressed by microsimulation for different penetration levels and bottleneck layouts. The deployment of cruise control improves bottleneck capacity. The bottleneck reliability, however, deteriorates in most cases. No significant changes in traffic safety, expressed by the time drivers are exposed to small time-to-collision values, could be established. From the simulation experiments it appears that intelligent speed adaptation has no effect on capacity and provides no substantial contribution to bottleneck reliability. Contrary to expectations, no significant safety benefits could be established using the study’s assessment approach.

A critical concern of autonomous vehicles is safety. Different approaches have tried to enhance driving safety to reduce the number of fatal crashes and severe injuries. As an example, Intelligent Speed Adaptation (ISA) systems warn the driver when the vehicle exceeds the recommended speed limit. However, these systems only take into account fixed speed limits without considering factors like road geometry. In this paper, we consider road curvature with speed limits to automatically adjust vehicle’s speed with the ideal one through our proposed Dynamic Speed Adaptation (DSA) method. Furthermore, ‘curve analysis extraction’ and ‘speed limits database creation’ are also part of our contribution. An algorithm that analyzes GPS information off-line identifies high curvature segments and estimates the speed for each curve. The speed limit database contains information about the different speed limit zones for each traveled path. Our DSA senses speed limits and curves of the road using GPS information and ensures smooth speed transitions between current and ideal speeds. Through experimental simulations with different control algorithms on real and simulated datasets, we prove that our method is able to significantly reduce lateral errors on sharp curves, to respect speed limits and consequently increase safety and comfort for the passenger.

Most traffic accidents occur at unsignalized intersections, mainly due to inappropriate behavior of non-priority vehicles. The authors have developed an advanced Intelligent Speed Adaptation (ISA) system with GPS/GIS to provide warning to stop failure vehicles at unsignalized intersections. In this study, experiments related to driver attitudes toward stop sign warning were carried out. At a drivers training course, drivers attitudes were tested using a vehicle equipped with the warning system in order to ascertain appropriate timing of warnings when approaching intersections. The drivers evaluation and willingness-to-pay for the warning system were also analyzed using an interview survey answered by testers.

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