# Drive on a Greener Way: A Case Study on Navigating Cross-Regional Traffic Networks in South China
## 1 Introduction  
Navigation and route planning are important problems. Navigation refers to finding the best route given a particular road network, traffic conditions, and origin-destination (OD). Navigation is already common. In April 2021, Amap's average number of daily active drivers exceeded 100 million. However, in general, in a vehicle navigation system, the shortest route is often not the optimal path for the driver [1]. Drivers have different navigation needs, so in addition to the shortest and fastest routes, it is essential to find the best route that aligns with specific goals. In the process of road transport, green driving is an important strategic goal, and sustainable mobility is the means to achieving this. Sustainability is determined by a complex set of factors that are largely influenced by traffic route choices. Therefore, sustainable route planning is conducive to the promotion of sustainable mobility when the OD has been determined [2]. Environmental factors are an important evaluation index ofsustainable mobility. In the literature [3], the weight of environmental factors is second only to accessibility. Carbon emissions are an important environmental assessment index [4]. China's transport accounts for 10% of the total carbon emissions. Therefore, selecting the most sustainable route option, with the least carbon emissions, should be prioritized. Few studies have focused on the planning of the most sustainable route. On one hand, shortest and fastest route planning differs from most sustainable route planning. The route planning problem involves the minimization of costs for the driver [5]. From the driver's perspective, existing research mainly focuses on shortest and fastest route planning, the influence of adjusting prices on route planning, and the analysis of driver route choices at key locations, such as toll stations. For example, for a certain OD [6], a vehicle routing algorithm is used to reduce the travel time. Sustainable mobility is evaluated solely from the driver's perspective, considering aspects such as increases in the average speed [1]. Road factors are added to the model as traffic characteristics, such as slope [7]. On the other hand, these methods cannot find the most sustainable route. None of the existing methods can be applied to this problem. First, it is difficult to quantify the carbon emissions generated by sustainable mobility. The types and characteristics of roads can affect carbon emissions from traffic. Increasing the durability of roads helps to reduce carbon emissions [8], and one can evaluate the sustainability of roads by considering the materials used for road maintenance and in the road structure. Many factors affect carbon emissions, and these factors have complex relationships. Both vehicles and roads impact carbon emissions. For example, driving too slowly will increase fuel consumption and, thus, carbon emissions. In the assessment of carbon emissions, vehicle and road factors also interact. For example, excessive traffic will increase the number of carbon-containing materials required for road maintenance, thus increasing carbon emissions. Second, the navigation results should be produced in near-real time. The traffic flow changes frequently. When the traffic flow changes to a certain extent, it will affect the state of traffic, which, in turn, will affect the carbon emissions generated by traffic. Therefore, it is necessary to update the traffic state in near-real time, as well as the optimal route. To sum up, the research problem concerns the lack of sustainable mobility carbon emission assessment methods and the most sustainable route planning methods that integrate vehicles and roads. To solve these problems, first, we propose a sustainable mobility evaluation model. The carbon footprint life cycle assessment (LCA) method is used to calculate the carbon emissions from vehicles and roads during periods of traffic.