# A Path Recommendation Method Considering Individual Driving Preferences
## 2 Factors Influencing Individual Preferences
### Individual Attributes  
Individual driver attributes have a significant role in the path selection preferences of drivers. These preferences are influenced by various factors, including gender, age, driving experience, occupation, and personality. Differences in path preferences can be observed in terms of sensitivity to path travel time stability, tendency to stick to historical paths, path difficulty, and preference for traffic conditions. In this study, instead of relying on questionnaires, we utilized ALPR data to determine individual driver attributes. To quantify drivers with specific attributes, we introduced a counting function, denoted as \(CT_{7}(\varphi(R))\), which calculates the number of times the condition \(\varphi(R)\) is satisfied for all travel trajectories \(R\) of the same driver under the same OD pair for seven consecutive days. Assuming that the driver associated with the same license plate number remains consistent in the detection data, we can quantify drivers based on each attribute, as follows. 1. Stability of travel time  
Drivers who prioritize stable travel time have a higher demand for reliable travel time and place certain requirements on the arrival time or travel duration under the same OD pair. This preference is often observed when considering regular travel behaviors such as commuting or going to school. The identification of drivers who prioritize stable travel time is determined as follows:  
\[CT_{7}(t_{arrive}^{max}-t_{arrive}<\gamma\text{ or }T_{L}^{max}-T_{arrive}<\gamma) \geq\beta, \tag{11}\]  
where \(t_{arrive}^{max}\) and \(T_{L}^{max}\) represent the latest arrival time and maximum travel duration, respectively, for the same OD pair over seven consecutive days; \(t_{arrive}\) and \(T_{arrive}\) represent the arrival time and travel duration for a specific trip, respectively; and \(\gamma\) and \(\beta\) are the respective time and count thresholds. The expression \(CT_{7}(t_{arrive}^{max}-t_{arrive}<\gamma\text{ or }T_{L}^{max}-T_{arrive}<\gamma)\) represents the count of occurrences where the time difference between the latest arrival time and the current arrival time, or the difference between the maximum travel duration and the current travel duration is less than \(\gamma\) within all travel trajectories of a driver for the same OD pair over seven consecutive days. Based on relevant research [25], the values chosen for \(\gamma\) and \(\beta\) in this study were 15 min and 2 times, respectively. In other words, drivers who had a count greater than or equal to two for occurrences where the floating difference in arrival time or travel duration for the same OD pair over seven consecutive days was less than 15 min were considered to possess the attribute of travel time stability. The strength of this attribute is determined by the value on the left side of Equation (11). 2. Historical Inertia  
Historical inertia, in the context of a driver's path choice between OD pairs, exemplifies the stability exhibited by experienced drivers who possess a certain level of familiarity with the travel path. These seasoned drivers boast a wealth of knowledge regarding traffic information and possess a heightened sense of confidence in their own judgment. Consequently, they are less inclined to deviate from their established travel paths. A driver who would be regarded as being with historical inertia should meet the following condition:  
\[CT_{7}(L=L_{this})\geq\beta. \tag{12}\]  
where \(L_{this}\) denotes the path with the highest number of trips for a specific driver over a 7-day period, while \(L\) represents a specific trip path. Additionally, \(\beta\) was assigned a value of 2 in this study. It is important to note that we considered drivers as having exhibited historical inertia if they repeated the same trip path under the same OD pair at least twice within a span of seven consecutive days. 3.