The deployment of Long Combination Vehicles (LCVs) is underway in Sweden. LCVs are heavy vehicles exceeding the conventional length limit of 25.25 meters, as stipulated by Swedish regulations. These vehicles offer several advantages, including reduced operational costs, enhanced fuel efficiency, and lower CO2 emissions per ton-kilometer. However, despite their benefits, questions remain regarding their on-road performance. While simulation studies have provided some insights, there is a notable gap in the analysis of LCV performance using real-world traffic data.

This study evaluates the performance of LCVs using naturalistic driving data (NDD) through the application of Performance-Based Standards (PBS) measures. PBS is a regulatory framework for assessing heavy vehicles, including LCVs, based on specific metrics with quantified performance thresholds. The PBS measures used in this study are rearward amplification, low-speed swept path, high-speed transient offtracking, and high-speed steady-state offtracking. These metrics assess various aspects of vehicle stability and the space occupied during different driving scenarios. Additionally, the steering reversal rate is utilized to estimate the cognitive workload of drivers in low-speed scenarios. Two LCV configurations are used for the analysis: an A-double, which consists of a tractor-semitrailer-dolly-semitrailer or tractor-semitrailer-full trailer, and a DuoCAT, comprising a truck hauling two center-axle trailers. These vehicles are driven across different parts of Sweden for the data collection in different seasons. Four driving scenarios are examined: lane changes, maneuvering through roundabouts, turning in intersections, and negotiating tight curves.

This study fills a critical gap in the literature by assessing the real-world performance of LCVs using naturalistic driving data. The findings confirm that both A-double and DuoCAT configurations meet safety standards in a variety of driving scenarios, with each vehicle type showing distinct strengths. The results of this study can be utilised by many stakeholders, such as vehicle manufacturers, infrastructure development firms and the government for optimizing vehicle designs, maintaining and designing road networks or for making new policies.