## 7 Conclusions  
This study explored the conflict risk in the diverging area of a toll plaza for different ETC and MTC vehicle-following patterns. Four patterns were compared according to the combination of vehicle toll collection types: ETC-ETC, ETC-MTC, MTC-MTC, and MTC-ETC. The extended time to collision (ETTC) was used to measure the conflict risk for each vehicle-following pattern. Using random parameters ordered logit models with heterogeneity in means, the effects of traffic condition characteristics, driving behavior characteristics, and roadway characteristics were evaluated using vehicle trajectory data obtained from a toll plaza diverging area in Nanjing, China. The major conclusions are concluded as follows:  
1. Vehicle-following patterns with the same toll collection types (ETC-ETC, MTC-MTC) have a higher percentage of severe conflict risk. This indicates that although the mixture of vehicles with different toll collection types leads to an increase in vehicle conflicts in the toll plaza diverging area, it does not mean that the severity of the conflict risk would increase. Therefore, in the toll plaza diverging area, attention should be paid to conflicts not only between vehicles with different toll collection types, but also between vehicles with the same toll collection type. 2. The random parameters ordered logit models with heterogeneity in means outperform the conventional random parameters ordered logit models and produce more insightful results. Different models of different vehicle-following patterns have different random parameters, indicating that heterogeneity exists in different combinations. The effects of the speed standard deviation of the following vehicle within 3 s (TVSTD), the standard deviation of ETTC of all vehicles in sub-segment (ZEST), and the average traffic volume of the sub-segment (ZVOL) on the conflict risks considerably vary across vehicle-following patterns. In addition, lane-marking indicator (L\({}_{\text{M}}\)), the number of vehicles with ETTC less than 4 s in sub-segment (ZNPETTC), and the mix measure of MTC and ETC vehicles in sub-segment (ZMIX) are associated with the means and the variances of these random parameters. More flexible management measures, such as variable speed limits (VSL) and dynamic message signs (DMS) should be implemented instead of the fixed speed limits and signs to further enhance the safety at toll plazas. 3. Interesting results are observed in the coefficients of driving behavior-related characteristics. In ETC-ETC and MTC-ETC models, all effects of variables related to the initial lane (L\({}_{\text{INIT}}\)2, L\({}_{\text{INIT}}\)3, L\({}_{\text{INIT}}\)4) are significant. When the initial lanes of the following ETC vehicles are L\({}_{\text{INIT}}\)2, L\({}_{\text{INIT}}\)3, or L\({}_{\text{INIT}}\)4, the conflict risk increases. Thus, guiding ETC vehicles to change lanes in advance to the inner side of the main road before they are entering the diverging area could effectively reduce the conflict risks in the diversion area. 4. The utilization of random parameters ordered logit models with heterogeneity in means and variances can more comprehensively and accurately reveal the mechanisms of different factors affecting the conflict risks of vehicles with different toll collection types. The findings of this study are significant for assessing the traffic safety situation at toll plazas and formulating corresponding conflict mitigation measures. Nonetheless, this study could be improved in a few ways. First, the scope of this study is restricted to a single toll plaza in Nanjing, China. Additionally, the weather is limited to sunny days with clear vision. More scenarios such as rainy days or foggy days should be considered. Additionally, how the characteristics of drivers, such as age, gender, and interacting with other contributing factors which may have significant effects on conflict risks should be further explored. The authors suggest further research on these topics. Conceptualization, L.X. and D.Z. ; methodology, L.X. and Y.F.